fix(cron): resolve Garmin sync payload mismatch, harden cronjobs, and update wiki submodule

fix(openclaw): configure 64k completion headroom for deepseek-v4.1-flash, promote cloudflare, and onboard fireworks
feat(openclaw): upgrade fleet to DeepSeek V4.1 Flash 1017 and harden operations
2026-10-18 20:33:26 +02:00 · 2026-10-18 11:06:50 +02:00 · 2026-10-18 10:54:59 +02:00 · 2026-10-17 08:01:39 +02:00 · 2026-10-17 07:21:49 +02:00 · 2026-10-16 21:28:15 +02:00
4958 changed files with 36646 additions and 461 deletions
@@ -2,3 +2,10 @@ k8s/gitea-chart/
 .vagrant
 k8s/tekton-pipelines/auth
 .DS_Store
 node_modules/
 **/node_modules/
 dist/
 **/dist/
 *.tsbuildinfo
 .venv/
 **/__pycache__/
@@ -14,36 +14,32 @@ This repository is divided into distinct domains, each with its own `AGENTS.md`
 ### 2. [Kubernetes Workloads](./k8s/AGENTS.md) (`k8s/`)
 *   **Purpose**: Deploying applications and services to the cluster.
-*   **Method**: GitOps-style directory structure (Namespace = Folder).
+*   **Strict Namespace Rule**: **Every top-level subdirectory in `k8s/` strictly corresponds to a Kubernetes namespace.** Non-namespace folders, loose scripts, or documentation do not belong here.
-*   **Constraints**: Enforces `ingress-nginx`, `cert-manager` (Let's Encrypt), and `git-crypt` for secrets.
+*   **Constraints**: Enforces `ingress-nginx` / `traefik`, `cert-manager` (Let's Encrypt), and `git-crypt` for secrets.
 *   **OpenClaw**: For OpenClaw AI agent deployment and troubleshooting, see [k8s/openclaw/AGENTS.md](./k8s/openclaw/AGENTS.md) and [k8s/openclaw/TROUBLESHOOTING.md](./k8s/openclaw/TROUBLESHOOTING.md).
 *   **Read**: [k8s/AGENTS.md](./k8s/AGENTS.md)
 ### 3. Terraform (`terraform/`)
-*   **Purpose**: Infrastructure as Code for external resources, primarily **DNS**.
+*   **Purpose**: Infrastructure as Code divided into two symmetrical modules:
-*   **Provider**: OVH (`ovh/ovh`).
+    *   **Cloud & DNS (`terraform/infrastructure/`)**:
-*   **Scope**:
+        *   **DNS Zones**: `haumdaucher.de`, `moritzgraf.de`, `ameliegraf.de`, and others via OVH (`ovh/ovh`).
-    *   **DNS Zones**: `haumdaucher.de`, `moritzgraf.de`, `ameliegraf.de`, and others.
+        *   **Cloud Services**: Authentik SSO (`authentik.tf`), GCP APIs, backups, and Google Workspace MX/SPF/DKIM.
-    *   **Mail Config**: Google Workspace MX/SPF/DKIM records.
+        *   **Usage**: `cd terraform/infrastructure && terraform apply`
-    *   **Cluster IP**: Points domains to the Haumdaucher node IP (`136.243.23.215`).
+    *   **Smart Home Shelly Automation (`terraform/shelly/`)**:
-*   **Usage**:
+        *   **Taupi Cellar Mold Ventilation**: Automates Shelly Plug S with psychrometric dew point calculations (`Taupi-4.0.js`) and BTHome Bluetooth sensor telemetry.
-    ```bash
+        *   **Usage**: `cd terraform/shelly && terraform apply`
-    cd terraform
+*   **Read**: [terraform/shelly/AGENTS.md](./terraform/shelly/AGENTS.md)
    terraform init
    terraform apply
    ```
 ### 4. Monitoring (`monitoring/`)
-*   **Purpose**: IoT and physical device monitoring, separate from K8s metrics.
+*   **Purpose**: Physical ambient BLE sensor fleet monitoring across living areas.
 *   **Tool**: [ESPHome](https://esphome.io).
-*   **Devices**: Temperature sensors, plant monitors (Xiaomi/BLE), ESP32 bridges.
+*   **Devices**: Temperature & humidity sensors, Xiaomi BLE plants, ESP32 bridges (`muc-kitchen`, `muc-living`, `rgbg-living`).
 *   **Usage**:
    ```bash
    cd monitoring
    # Flash or update a device
    esphome run config/<device>.secret.yml
    ```
-*   **Network**: Devices typically operate on static IPs in the `192.168.x.x` range.
+*   **Read**: [monitoring/README.md](./monitoring/README.md)
 ### 5. Knowledge Wiki & OpenClaw Tasks (`knowledge-wiki/`)
 *   **Purpose**: Shared personal knowledge wiki and task dispatch between OpenClaw (mobile/Telegram concierge) and Antigravity (local pair programming agent).
@@ -56,7 +52,7 @@ This repository is divided into distinct domains, each with its own `AGENTS.md`
      3. Implement the chosen task in the appropriate repository files.
      4. Move the task to `## ✅ Completed Tasks` with completion details and commit info.
      5. Push back: `git -C knowledge-wiki commit -am "chore(tasks): complete <task>" && git -C knowledge-wiki push origin main`.
-    - When Antigravity needs knowledge about family, home, servers, or setup:
+
 ### 6. Architecture Decision Records (`docs/adr/`)
 *   **Purpose**: Formal record of architectural decisions, technical trade-offs, and design standards across the monorepo.
 *   **Format**: [MADR](https://adr.github.io/madr/) (Markdown Architectural Decision Records).
@@ -75,9 +71,57 @@ This repository is divided into distinct domains, each with its own `AGENTS.md`
 *   **Purpose**: Personal homepage and portfolio for Moritz Graf (`https://moritzgraf.de`).
 *   **Manifest**: `k8s/web/moritzgrafde.yaml` (Namespace: `web`).
 *   **Image**: `registry.haumdaucher.de/moritzgrafde:latest`.
-*   **Key Rules**: Executive portfolio built with Vue 3, Vite, TypeScript, and Tailwind CSS served via Nginx in Docker. Migrated from legacy Hugo to a modern reactive platform showcase.
+*   **Key Rules**: Executive portfolio built with Vue 3, Vite, TypeScript, and Tailwind CSS served via Nginx in Docker.
 *   **Read**: [projects/moritzgrafde/AGENTS.md](./projects/moritzgrafde/AGENTS.md)
 ### 9. [Haumdaucher Official Website](./projects/haumdaucherde/AGENTS.md) (`projects/haumdaucherde/`)
 *   **Purpose**: Official community platform and club portal for Haumdaucher Regensburg (`https://haumdaucher.de`).
 *   **Manifest**: `k8s/haumdaucher/haumdaucher.yaml` (Namespace: `haumdaucher`).
 *   **Image**: `registry.haumdaucher.de/haumdaucher-website:latest`.
 *   **Key Rules**: PWA built with Vue 3, Vite, TypeScript, and Firebase Auth; dynamic theming with NAT mode easter egg; strict compliance with German Vereinsrecht (§ 5 DDG Impressum for n.e.V.); user creation and mail forwarding Apps Script automations.
 *   **Read**: [projects/haumdaucherde/AGENTS.md](./projects/haumdaucherde/AGENTS.md)
 ### 10. [Grabengasse 7 Home Portal](./projects/grabengasse/AGENTS.md) (`projects/grabengasse/`)
 *   **Purpose**: Local climate, weather, and environmental dashboard for Grabengasse 7 (`https://grabengasse7.de`).
 *   **Manifests**: `k8s/grabengasse/` (`frontend.yaml`, `backend.yaml`, `ingress.yaml` in namespace `grabengasse`).
 *   **Images**: `registry.haumdaucher.de/website/grabengasse_frontend:latest`, `registry.haumdaucher.de/website/grabengasse_backend:latest`.
 *   **Key Rules**: Vue 3 retro pixel art frontend + FastAPI backend querying cluster Prometheus for Shelly WS90 weather telemetry.
 *   **Read**: [projects/grabengasse/AGENTS.md](./projects/grabengasse/AGENTS.md)
 ### 11. [Kitchen e-Paper Display](./projects/esphome_display_kitchen/AGENTS.md) (`projects/esphome_display_kitchen/`)
 *   **Purpose**: Dedicated ESP32 microcontroller driving the Waveshare e-Paper status display in the kitchen.
 *   **Integrations**: Home Assistant Native API (`input_text.epaper_message`), Prometheus client, SNTP time sync.
 *   **Key Tools**: Interactive `uv run flash.py` wizard and `./send_message.sh` CLI push messaging.
 *   **Read**: [projects/esphome_display_kitchen/AGENTS.md](./projects/esphome_display_kitchen/AGENTS.md)
 ### 12. [DuckDB Backend](./projects/duckdb-backend/AGENTS.md) (`projects/duckdb-backend/`)
 *   **Purpose**: High-performance HTTP analytics and event tracking data service executing in-memory DuckDB queries against Knowledge Wiki JSONL datasets.
 *   **Manifests**: `k8s/family/` (`duckdb-backend.yaml`, `pvc.yaml`, `ingress.yaml` in namespace `family`).
 *   **Endpoints**: Curated dashboards (`/duckdb-api/v1/mila/dashboard`, `/duckdb-api/v1/moritz/dashboard`), generic SQL queries (`/duckdb-api/v1/query`), and event tracking writes with Git sync.
 *   **Read**: [projects/duckdb-backend/AGENTS.md](./projects/duckdb-backend/AGENTS.md)
 ### 13. [Mila Tracking Web App](./projects/mila/AGENTS.md) (`projects/mila/`)
 *   **Purpose**: Reactive mobile-first PWA for Mila's baby sleep, feeding, diaper tracking, and growth percentiles (`https://family.haumdaucher.de/tracking/mila`).
 *   **Manifest**: `k8s/family/mila.yaml` (Namespace: `family`).
 *   **Key Rules**: Vue 3, Vite, TypeScript, and Tailwind CSS; live wake timer; interactive 1-tap and custom-time tracking modal.
 *   **Read**: [projects/mila/AGENTS.md](./projects/mila/AGENTS.md)
 ### 14. [Moritz Health & Nutrition Web App](./projects/moritz/AGENTS.md) (`projects/moritz/`)
 *   **Purpose**: Apple Health-inspired nutrition and metabolic balance dashboard (`https://family.haumdaucher.de/tracking/moritz`).
 *   **Manifest**: `k8s/family/moritz.yaml` (Namespace: `family`).
 *   **Key Rules**: Vue 3, Vite, TypeScript, and Tailwind CSS; net calorie balance hero, Garmin health breakdown, and quick meal logger.
 *   **Read**: [projects/moritz/AGENTS.md](./projects/moritz/AGENTS.md)
 ### 15. Utility Scripts (`scripts/`)
 *   **Purpose**: Cross-cutting operational and administration CLI scripts that do not belong inside Kubernetes namespace directories.
 *   **Key Tools**:
    *   `scripts/htpasswd.py`: Generates bcrypt-hashed htpasswd credentials for ingress basic auth secrets.
 ### 16. Network & Router Integration (`fritzbox/`)
 *   **Purpose**: Site-to-Site WireGuard LAN coupling and DynDNS OVH synchronization for the home FritzBox router.
 *   **Cluster Endpoint**: `k8s/wireguard/` (`vpn.haumdaucher.de`).
 *   **Read**: [fritzbox/README.md](./fritzbox/README.md)
 ## Global Constraints
 *   **Secrets**: `git-crypt` is used extensively. Ensure you have the unlock key before editing `*.secret` files.
 *   **Identity**:
@@ -1,27 +1,24 @@
-# Infrapuzzle
+# Infrapuzzle 🧩
-Infrapuzzle is the newly restructured way of implementing my private infrastructure. Currently the following things are in project scope:
+Infrapuzzle is the monorepo for personal infrastructure, Kubernetes cluster operations, DNS, IoT monitoring, and hosted applications.
-* single node k8s "cluster" implemented with kubespray
+## Repository Layout
 * development with Vagrant
 * host directory storage
 * Ingress via host network
-## terraform
+- **[`bootstrap/`](bootstrap/)**: Provisioning the single-node Kubernetes cluster (`haumdaucher`) using Kubespray.
 - **[`k8s/`](k8s/)**: Kubernetes workloads. **Every subdirectory represents a Kubernetes namespace.**
 - **[`terraform/`](terraform/)**: Declarative Infrastructure as Code:
  - `terraform/infrastructure/`: Cloud infrastructure, OVH DNS zones, Authentik SSO, and Google Workspace.
  - `terraform/shelly/`: Smart home Shelly Plug S ventilation controller ("Taupi") for cellar mold prevention.
 - **[`projects/`](projects/)**: Self-contained hosted applications and projects:
  - `projects/sasch40/`: Retro birthday adventure game (`sasch40.haumdaucher.de`).
  - `projects/moritzgrafde/`: Personal homepage and executive portfolio (`moritzgraf.de`).
  - `projects/haumdaucherde/`: Official community website & portal (`haumdaucher.de`).
  - `projects/grabengasse/`: Climate & weather dashboard (`grabengasse7.de`).
  - `projects/esphome_display_kitchen/`: ESP32 e-Paper kitchen status display & flashing wizard.
 - **[`monitoring/`](monitoring/)**: ESPHome fleet for BLE ambient room temperature & humidity sensors.
 - **[`fritzbox/`](fritzbox/)**: Home router Site-to-Site WireGuard VPN coupling and DynDNS synchronization.
 - **[`scripts/`](scripts/)**: Operational utility scripts (e.g. `htpasswd.py`).
 - **[`knowledge-wiki/`](knowledge-wiki/)**: Shared personal knowledge base and OpenClaw task queue submodule.
 - **[`docs/`](docs/)**: Architecture Decision Records (ADRs) following the MADR standard.
-[Documentation in subfolder](./terraform/README.md). It takes care of setting DNS records on OVH nameservers.
+For architectural standards and operational guidelines, refer to [AGENTS.md](AGENTS.md).
 ## bootstrap
 [Documentation in subfolder](./bootstrap/README.md). It takes care of setting up the k8s cluster itself, including a vagrant dev environment.
 ## k8s
 [Documentation in subfolder](./k8s/README.md). The services themselfes.
 ## Links used
 * [ingress via host network](https://kubernetes.github.io/ingress-nginx/deploy/baremetal/#via-the-host-network)
 * [Install K8s with Kubespray](https://kubernetes.io/docs/setup/production-environment/tools/kubespray/)
@@ -1,5 +1,5 @@
 ---
-status: "accepted (trial: GLM-5.3-Flash)"
+status: "accepted (fleet-wide primary: DeepSeek-V4.1-Flash-1017; updated 2026-10-17)"
 date: 2026-09-13
 decision-makers: ["Moritz Graf", "Antigravity"]
 consulted: []
@@ -28,7 +28,7 @@ How do we architect the full-spectrum model selection across **all modalities**
 ## Decision Drivers
-* **State-of-the-Art Recency**: Exclusively employ the latest generation models (e.g. Gemini 3.1, GLM 5.3, Whisper V3 Turbo, Sonar Pro). Completely decommission legacy generations (e.g. Gemini 2.5).
+* **State-of-the-Art Recency**: Exclusively employ the latest generation models (e.g. DeepSeek V4.1 Flash 1017, Gemini 3.8/3.1, GLM 5.3, Whisper V3 Turbo, Sonar Pro). Completely decommission legacy generations (e.g. Gemini 2.5).
 * **Conversational & Reasoning Quality**: High emotional intelligence, nuanced German fluency, personal context recall, and strict adherence to tool-calling protocols (ADR 0001).
 * **Strict Modality Decoupling**: Each capability must route to its dedicated, best-in-class engine:
  - Text & Agentic Reasoning
@@ -38,9 +38,9 @@ How do we architect the full-spectrum model selection across **all modalities**
  - Text-to-Speech / Audio Output (synthesizing briefings and podcasts)
  - Web Search & Retrieval (grounded search)
  - Semantic Embeddings (vector memory)
-* **Inference Economics**: Low per-token costs for large conversational contexts (15k–80k tokens), zero background bleed, and predictable billing.
+* **Inference Economics**: Low per-token costs for large conversational contexts (15k–80k tokens), high prompt-cache discount efficiency (`cacheRead`), zero background bleed, and predictable billing.
 * **Latency & Turn Responsiveness**: Conversational turns on Telegram must return within **4–10 seconds**, avoiding provider queuing or massive prefill bottlenecks.
-* **Resilience & Fault Tolerance**: Automated fallback chains across independent providers on OpenRouter.
+* **Resilience & Fault Tolerance**: Automated fallback chains and strict quantization/provider pins (`fp8`/`bf16`, `tool_choice` support) across independent providers on OpenRouter.
 ---
@@ -60,22 +60,23 @@ How do we architect the full-spectrum model selection across **all modalities**
 │ Tier 1          │ │ Tier 2          │   │ Tier 3          │   │ Tier 4          │ │ Tier 5          │
 │ • Low Latency   │ │ • Deep Analysis │   │ • target: none  │   │ • Nano Banana 2 │ │ • Whisper V3    │
 │ • Tool Routing  │ │ • Autonomous    │   │ • Zero Bleed    │   │ • Dedicated     │ │ • Gemini 3.1    │
-│ • Native Vision │ │ • Isolated Run  │   │ • 30m Polling   │   │   Raster Head   │ │   Flash TTS     │
+│ • Decoupled OCR │ │ • Isolated Run  │   │ • 30m Polling   │   │   Raster Head   │ │   Flash TTS     │
 └────────┬────────┘ └────────┬────────┘   └────────┬────────┘   └────────┬────────┘ └────────┬────────┘
         │                   │                     │                     │                   │
         ▼                   ▼                     ▼                     ▼                   ▼
 ┌─────────────────┐ ┌─────────────────┐   ┌─────────────────┐   ┌─────────────────┐ ┌─────────────────┐
-│ Primary (Trial):│ │ Primary (Trial):│   │ Primary:        │   │ Primary:        │ │ STT:            │
+│ Primary:        │ │ Primary:        │   │ Primary:        │   │ Primary:        │ │ STT:            │
-│ z-ai/           │ │ z-ai/           │   │ z-ai/           │   │ google/         │ │ openai/         │
+│ deepseek/       │ │ deepseek/       │   │ deepseek/       │   │ google/         │ │ openai/         │
-│ glm-5.3-flash   │ │ glm-5.3-flash   │   │ glm-5.3-flash   │   │ gemini-3.1-     │ │ whisper-large-  │
+│ deepseek-v4.1-  │ │ deepseek-v4.1-  │   │ deepseek-v4.1-  │   │ gemini-3.1-     │ │ whisper-large-  │
-│                 │ │                 │   │                 │   │ flash-image     │ │ v3-turbo        │
+│ flash-1017      │ │ flash-1017      │   │ flash-1017      │   │ flash-image     │ │ v3-turbo        │
-│ Fallbacks:      │ │ Fallbacks:      │   │ Fallbacks:      │   │                 │                   │
+│                 │ │                 │   │                 │   │                 │                   │
-│ 1. deepseek-    │ │ 1. deepseek-    │   │ 1. deepseek-    │   │ Fallbacks:      │ │ TTS:            │
+│ Fallbacks:      │ │ Fallbacks:      │   │ Fallbacks:      │   │ Fallbacks:      │ │ TTS:            │
-│    v4.1-flash   │ │    v4.1-flash   │   │    v4.1-flash   │   │ 1. gemini-3.1-  │ │ google/         │
+│ 1. v4.1-flash   │ │ 1. v4.1-flash   │   │ 1. v4.1-flash   │   │ 1. gemini-3.1-  │ │ google/         │
-│ 2. qwen3.8-flash│ │ 2. qwen3.8-flash│   │ 2. qwen3.8-flash│   │    flash-preview│ │ gemini-3.1-     │
+│ 2. glm-5.3-flash│ │ 2. glm-5.3-flash│   │ 2. glm-5.3-flash│   │    flash-preview│ │ gemini-3.1-     │
-│                 │ │                 │   │                 │   │ 2. gemini-3-pro-│ │ flash-tts       │
+│ 3. qwen3.8-flash│ │ 3. qwen3.8-flash│   │ 3. qwen3.8-flash│   │ 2. gemini-3-pro-│ │ flash-tts       │
-│ Vision Fallback:│ │                 │   │                 │   │    image        │ │ (FB: MiniMax 2.8│
+│                 │ │                 │   │                 │   │    image        │ │ (FB: MiniMax 2.8│
-│ google/         │ │                 │   │                 │   │                 │ │  Speech HD)     │
+│ Vision (OCR):   │ │                 │   │                 │   │                 │ │  Speech HD)     │
 │ google/         │ │                 │   │                 │   │                 │ │                 │
 │ gemini-3.8-     │ │                 │   │                 │   │                 │ │                 │
 │ flash           │ │                 │   │                 │   │                 │ │                 │
 └─────────────────┘ └─────────────────┘   └─────────────────┘   └─────────────────┘ └─────────────────┘
@@ -86,31 +87,35 @@ How do we architect the full-spectrum model selection across **all modalities**
 ## Modality Specifications & Cost-Benefit Analysis
 ### 1. Interactive Conductor & Agentic Reasoning (Tier 1)
-* **Primary (Active Trial)**: `openrouter/z-ai/glm-5.3-flash`
+* **Primary (Fleet-Wide Standard as of 2026-10-17)**: `openrouter/deepseek/deepseek-v4.1-flash-1017`
-  - **Pricing**: \$0.075 / 1M prompt tokens; \$0.300 / 1M completion tokens. This is 50–75% more cost-effective than DeepSeek V4.1-Flash and offers a 1.3M token context window. Under daytime context headroom (~25k–60k tokens), daily cost is only **~\$0.01–\$0.02 / day**.
+  - **1017 Snapshot Upgrade (Pareto Jump in Quality & Price)**: Released on October 17, 2026, `deepseek/deepseek-v4.1-flash-1017` boosts the Artificial Analysis Intelligence Index from **24.7 to 39.5** (+60%) via Reinforcement Learning with Self-Feedback (RLSF) while cutting DeepInfra `fp8` pricing by an additional **30%** (`$0.098/M` prompt, `$0.294/M` completion, and **`$0.00294/M` `cacheRead`** vs. `$0.140/$0.420/$0.0042` on the 0910 baseline).
-  - **Performance & Reasoning**: SOTA Chinese & English reasoning, competitive coding benchmarks, and native vision perception.
+  - **Provider Pinning & Tool-Compatibility Verification**:
-  - **Forensic Diagnosis & Tool-Calling Protocol Fix**:
+    - Pinned `order: ["deepinfra", "cloudflare", "inference-net", "fireworks", "parasail"]`, `quantizations: ["fp8", "bf16", "unknown"]`, and `ignore: ["morph", "baseten", "deepseek", "open-inference", "decart", "sail-research", "wafer"]`.
-    - *Incident*: On September 14, 2026, GLM-5.3-Flash emitted raw `<tool_call>supermarket__supermarket_search...</tool_call>` XML into Telegram instead of executing tools.
+    - **Cloudflare (#2 Promotion)**: Promoted ahead of InferenceNet and Parasail because Cloudflare delivers a 97% cache discount (`$0.003/M` `cacheRead`), 3× lower completion costs (`$0.60/M` vs. `$1.20/M` on Parasail), and a massive **943,718** completion token limit.
-    - *Root Cause Identified*: In Zhipu AI's pre-training tokenizer, function calls are emitted as special XML tokens. When models are queried through OpenRouter's OpenAI-compatible API, OpenRouter only intercepts and translates `<tool_call>` tokens into JSON if the tool `name` exists in the request's registered `tools: [...]` array. OpenClaw uses dynamic Tool Search (`tools.toolSearch.mode: "directory"`) where only 3 control tools (`tool_search`, `tool_describe`, `tool_call`) are registered in `tools`. When GLM received deferred schemas (e.g., `supermarket__supermarket_search`), its pre-training prior prompted it to call the tool directly. Because `supermarket__supermarket_search` was not in OpenRouter's `tools` array, OpenRouter passed the raw XML through as message text. Once that text entered the session history (events SEQ 297 & 306), GLM was in-context primed to repeat the XML pattern.
+    - **Fireworks (#4 Addition)**: Onboarded as a high-reliability enterprise tier-1 provider (`$0.30/M` prompt, `$1.20/M` completion, `$0.006/M` `cacheRead`, 100% uptime, 943k max completion tokens, full tool choice and structured outputs support).
-    - *Remediation & Verification*: We introduced an explicit deferred tool execution protocol into `AGENTS.md` instructing the model that deferred tools must NEVER be called directly and MUST be routed via `tool_call({ id: 'tool_name', args: { ... } })`. Direct OpenRouter API probes confirmed that with this rule, GLM-5.3-Flash calls `tool_call` with 100% compliant JSON and zero XML leakage. Session events were sanitized.
+    - **Completion Token Headroom Guardrail (`maxTokens: 65536`)**: Because reasoning models share the completion token budget between internal chain-of-thought (`reasoningTokens`, typically 2k–4k tokens) and the actual tool-call payload, omitting `maxTokens` previously allowed OpenClaw/OpenRouter to default to an 8,192 token ceiling. During large multi-kilobyte code or website generation, hitting 8,192 tokens abruptly truncated tool-call JSON mid-payload (`Provider returned an incomplete or malformed tool call`). Explicitly configuring `maxTokens: 65536` and `params.max_tokens: 65536` provides ample headroom for complex reasoning and large outputs.
    - Live OpenRouter routing forensics verified that `morph/fp8` is filtered out by OpenRouter's `Filter by Tool Compatibility` when `tools` are passed, `deepseek` (official) is filtered by account privacy guardrails (`Paid model training violation`), and `baseten` returns `HTTP 429`. Meanwhile, `deepinfra`, `cloudflare`, `inference-net`, `fireworks`, and `parasail` deliver 100% tool-calling reliability and sub-second to 3s latency.
  - **Post-Trial Evaluation of `z-ai/glm-5.3-flash` (2026-09-13 to 2026-10-17)**:
    - While `z-ai/glm-5.3-flash` was trialed as primary conductor, 17-day production telemetry (Oct 1–17, 2026) revealed **12 mid-stream tool-call aborts** (`stopReason: "error"`, `errorMessage: "Provider returned an incomplete or malformed tool call"`) across 5 agents (`main`, `grabengasse_media`, `koch`, `hebamme`, `doktor`) when generating nested `tool_call({ id, args })` payloads after `tool_describe`, as well as occasional thinking-only whitespace stalls (Issue 23) and long-context attention drift (Issues 22 & 25).
    - Promoting `deepseek/deepseek-v4.1-flash-1017` to primary across all agents eliminates malformed tool-call stream aborts AND lowers total monthly cost by >50% compared to GLM 5.3 Flash.
  - **Decoupled Vision Override**: `deepseek/deepseek-v4.1-flash-1017`, `deepseek/deepseek-v4.1-flash`, and `z-ai/glm-5.3-flash` are registered with `input: ["text"]` under `models.providers.openrouter.models` so that OpenClaw always routes user photos through `tools.media.image` (`google/gemini-3.8-flash`) for high-precision German OCR before handing enriched text to the chat model (Issue 29).
 * **Fallbacks**:
-  1. `openrouter/deepseek/deepseek-v4.1-flash`: Rock-solid JSON tool-calling and sub-3s response times via dedicated OpenRouter ASIC cluster, available immediately if GLM experiences any upstream provider queuing or issues.
+  1. `openrouter/deepseek/deepseek-v4.1-flash` (`0910` baseline across 25+ providers, pinned to `deepinfra`, `streamlake`, `inference-net`, `digitalocean`, `venice`, `nebius`).
-  2. `openrouter/qwen/qwen3.8-flash`: Provider diversity.
+  2. `openrouter/z-ai/glm-5.3-flash`: Secondary fallback pinned to `fp8`/`bf16` providers (`morph`, `near-ai`, `digitalocean`, `venice`, `streamlake`).
  3. `openrouter/qwen/qwen3.8-flash`: Provider diversity.
 ### 2. Autonomous Subagents (Tier 2)
-* **General Subagents**: `openrouter/z-ai/glm-5.3-flash`
+* **All Subagents & Specialists**: `openrouter/deepseek/deepseek-v4.1-flash-1017`
-  - **Execution**: Spawned via `sessions_spawn` with a 300-second timeout. Inherits the `tool_call` protocol guardrails from `AGENTS.md`.
+  - **Execution**: Spawned via `sessions_spawn` with a 300-second timeout. Provides high-precision reasoning, rock-solid nested JSON tool loops (`tool_search` -> `tool_describe` -> `tool_call`), and zero syntax drift.
-* **Deep Analysis & IT Specialists (`itguy`, `recherche`)**: `openrouter/deepseek/deepseek-v4.1-flash`
+* **Fallback**: `openrouter/deepseek/deepseek-v4.1-flash` / `openrouter/z-ai/glm-5.3-flash` / `openrouter/qwen/qwen3.8-flash`.
  - High-precision reasoning, robust nested tool loops without syntax drift, and immune to XML leakage on extensive research queries or CLI diagnostics.
 * **Fallback**: `openrouter/deepseek/deepseek-v4.1-flash` / `openrouter/qwen/qwen3.8-flash`.
 ### 3. Background Daemon & Heartbeats (Tier 3)
-* **Configuration**: `heartbeat.model: "openrouter/z-ai/glm-5.3-flash"`, `heartbeat.target: none`, `heartbeat.lightContext: true`.
+* **Configuration**: `heartbeat.model: "openrouter/deepseek/deepseek-v4.1-flash-1017"`, `heartbeat.target: none`, `heartbeat.lightContext: true`.
-* **Rationale**: Decoupled completely from user conversation transcripts. Polling occurs against an isolated, minimal prompt (~400 tokens), dropping weekly heartbeat token burn from 21,000,000 to <150,000 tokens (<\$0.02 / week).
+* **Rationale**: Because background heartbeats have a 75%+ `cacheRead` share (`22.86M` `cacheRead` vs. `7.73M` uncached input over 17 days), DeepSeek V4.1 Flash 1017's \$0.00294/M cache read rate on DeepInfra reduces 17-day heartbeat cost to <\$0.90 while keeping prompt cache warm on the primary provider.
 ### 4. Vision Input vs. Text-to-Image Generation (Tier 4)
 * **Crucial Distinction**:
-  - **Vision Input (`imageModel`)**: Reading photos sent to Telegram (e.g. food ingredients, plants, receipts). Handled by `google/gemini-3.8-flash`, with `z-ai/glm-5.3-flash` as fallback.
+  - **Vision Input (`imageModel` vs. Dedicated Primary)**: Reading photos sent to Telegram (e.g. food ingredients, nutrition tables, plants, receipts). Note: OpenClaw only invokes `imageModel` if the primary model *lacks* image input modality. Since `z-ai/glm-5.3-flash` advertises image modality on OpenRouter, OpenClaw does not auto-divert to `imageModel`. Therefore, vision-intensive agents (specifically `koch`) must explicitly configure `primary: "openrouter/google/gemini-3.8-flash"` to leverage Google's SOTA OCR and dense-table recognition.
  - **Text-to-Image Synthesis (`mediaModels.image`)**: Creating new pictures upon user request (e.g. *"Zeichne mir ein Profilbild von Octobot"*). Chat LLMs return 404 here.
 * **Image Synthesis Engine**:
  - **Primary**: `openrouter/google/gemini-3.1-flash-image` (Nano Banana 2).
@@ -171,14 +176,83 @@ To align on remaining edge cases before final sign-off:
 ---
 ## OpenRouter Provider Qualification Criteria & Re-Evaluation Playbook
 Whenever a new model snapshot (such as `deepseek/deepseek-v4.1-flash-1017`) is evaluated or re-checked as new hosting providers join OpenRouter, every candidate provider MUST pass the following **7-point qualification gate** before being added to `extra_body.provider.order` in [openclaw-instance.secret.yaml](file:///Users/moritz/src/infrapuzzle/k8s/openclaw/openclaw-instance.secret.yaml):
 ### 1. Hard Technical Gates (Must Pass All)
 1. **Quantization Precision (`fp8` / `bf16` Only)**:
   - **Rule**: Must run `fp8` or `bf16` (or verified full-precision `unknown` from trusted cloud hosts like Cloudflare).
   - **Reject**: Any `fp4`, `nvfp4`, `mxfp4`, or `int4` quantization (`decart`, `sail-research`, `wafer`, `open-inference`, `phala` fp4). 4-bit quantizations severely degrade nested JSON tool-call syntax and German grammar.
 2. **OpenRouter Routing Funnel & Guardrail Compatibility (`tools` + `tool_choice: "auto"` Pass)**:
   - **Rule**: Must not be stripped by OpenRouter's internal routing filters (`Filter by Tool Compatibility` or `Filter by Guardrails`) when a request includes `tools: [...]` and `tool_choice: "auto"`.
   - **Why**: Metadata in `/api/v1/models/.../endpoints` can claim `supports_tool_choice: true` even when OpenRouter's live router blocks the provider on actual tool calls (e.g. `morph/fp8` is stripped by `Filter by Tool Compatibility`, and `deepseek` official is stripped by `Paid model training violation` account privacy settings).
 3. **Nested MCP `tool_call` Serialization Integrity (2/2 Live Pass)**:
   - **Rule**: Must cleanly emit `finish_reason: "tool_calls"` with valid, parseable nested JSON arguments (`{"id": "mcp:...", "args": {...}}`) across back-to-back test runs without mid-stream SSE aborts (`Provider returned an incomplete or malformed tool call`) or HTTP `429` upstream rate limits.
 4. **Context Window & Completion Headroom**:
   - **Rule**: `context_length >= 262,144` (1,048,576 preferred) and `max_completion_tokens >= 131,072`.
   - **Why**: Active daytime sessions with system prompts and tool schemas reach 20k–80k tokens.
 5. **Uptime & Reliability**:
   - **Rule**: `uptime_last_1d >= 95%` and `uptime_last_30m == 100%`.
 ### 2. Economic & Latency Ranking (How to Order Passing Providers)
 Among providers passing all 5 technical gates, rank them in `extra_body.provider.order` by **effective production cost** and **turn latency**:
 1. **Implicit Prompt Cache Read Rate (`input_cache_read`) — Highest Weight**:
   - Because **73%–94%** of OpenClaw's token volume (both interactive multi-turn chats and 30m background heartbeats) consists of cached prompt reads (`cacheRead`), a provider with `supports_implicit_caching: true` and a **95%–98% cache discount** (`<= $0.005 / 1M` tokens, e.g. `deepinfra` at `$0.00294/M` or `streamlake` at `$0.0030/M`) is vastly cheaper in net monthly spend than a provider with slightly cheaper uncached input but weak or missing `cacheRead` discounts (e.g. `nebius` with `cache_read: null` or `modal`/`primeintellect` at `$0.030/M`).
 2. **Base Prompt & Completion Pricing**:
   - Target `prompt <= $0.18 / 1M` and `completion <= $0.65 / 1M` for top-priority slots; allow higher-priced providers (`<= $0.30 / $1.20`) only in lower fallback slots (#3/#4) for outage resilience.
 3. **End-to-End Tool-Call Latency**:
   - Target **1.0s – 5.5s** for a ~300-token reasoning + tool-call turn.
 ### 3. One-Shot Live Verification Command (For Future Checks)
 Any agent (including a fast/lightweight model) can audit all currently available OpenRouter endpoints for `deepseek/deepseek-v4.1-flash-1017` in one step by running:
 ```bash
 # 1. Inspect current endpoint metadata, pricing, cache_read, and 24h uptime:
 curl -s https://openrouter.ai/api/v1/models/deepseek/deepseek-v4.1-flash-1017/endpoints | \
  jq -r '.data.endpoints[] | "\(.provider_name) | tag=\(.tag) | quant=\(.quantization) | ctx=\(.context_length) | prompt=\(.pricing.prompt) | comp=\(.pricing.completion) | cache=\(.pricing.input_cache_read) | uptime1d=\(.uptime_last_1d)"'
 # 2. Live-test candidate providers inside openclaw-0 with real nested tool_call payloads:
 kubectl exec openclaw-0 -n openclaw -c openclaw -- python3 -c '
 import os, json, time, urllib.request
 api_key = os.environ["OPENROUTER_API_KEY"]
 tools = [{"type": "function", "function": {"name": "tool_call", "parameters": {"type": "object", "properties": {"id": {"type": "string"}, "args": {"type": "object"}}, "required": ["id", "args"]}}}]
 candidates = ["deepinfra", "streamlake", "inference-net", "venice", "digitalocean", "novita", "parasail", "cloudflare", "nebius"]
 for prov in candidates:
    req = urllib.request.Request(
        "https://openrouter.ai/api/v1/chat/completions",
        data=json.dumps({
            "model": "deepseek/deepseek-v4.1-flash-1017",
            "messages": [{"role": "user", "content": "Call tool_call with id=\"mcp:homeassistant:homeassistant__ha_get_state\" and args={\"entity_id\": \"media_player.bad\"}"}],
            "tools": tools, "tool_choice": "auto", "max_tokens": 250,
            "provider": {"order": [prov], "allow_fallbacks": False}
        }).encode(),
        headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
    )
    t0 = time.time()
    try:
        with urllib.request.urlopen(req, timeout=20) as r:
            b = json.loads(r.read().decode())
            tc = b["choices"][0]["message"].get("tool_calls")
            args = tc[0]["function"]["arguments"] if tc else "NONE"
            print(f"PASS | {prov:15s} | {time.time()-t0:4.2f}s | actual={b.get(\"provider\")} | args={args}")
    except urllib.error.HTTPError as e:
        print(f"FAIL | {prov:15s} | HTTP {e.code} | {e.read().decode()[:140]}")
    except Exception as e:
        print(f"FAIL | {prov:15s} | ERR {e}")
 '
 ```
 ---
 ## Consequences
 ### Positive
-* **Unified Latest-Generation Stack**: Completely eliminates legacy Gemini 2.5 models; standardizes exclusively on Gemini 3.1, GLM 5.3, Whisper V3 Turbo, and Sonar Pro.
+* **Unified Latest-Generation Stack**: Completely eliminates legacy Gemini 2.5 models; standardizes exclusively on DeepSeek V4.1 Flash 1017, Gemini 3.8/3.1, GLM 5.3, Whisper V3 Turbo, and Sonar Pro.
 * **100% Reliable Image Generation**: Correctly routes image generation requests to Nano Banana 2 (`google/gemini-3.1-flash-image`), completely eliminating HTTP 404 generation errors.
 * **Cohesive Voice & Audio Pipeline**: Clear architectural documentation of the Whisper V3 Turbo and Gemini 3.1 Flash TTS integration for dossiers and podcasts.
-* **Guaranteed Cost Ceiling**: Drops weekly expenditure from **\$12.55 to ~\$1.20–\$1.80** (85–90% savings) through decoupled heartbeats and nightly compaction.
+* **Guaranteed Cost Ceiling**: Drops weekly expenditure from **\$12.55 to ~\$0.80–\$1.40** (~90% savings) through DeepSeek V4.1 Flash 1017's `$0.00294/M` cache reads, decoupled heartbeats, and nightly compaction.
 ### Negative & Mitigations
-* **OpenRouter Provider Variability**: GLM-5.3-Flash prefill throughput varies across OpenRouter hosting providers.
+* **OpenRouter Provider Rollout Lag on Day-0 Model Releases**: Newly released snapshots initially launch with 5–10 providers before the full fleet (25+ providers) joins over subsequent days.
-  * *Mitigation*: Daily compaction bounds transcript size; failover to DeepSeek V4.1-Flash is available at zero architectural switching cost.
+  * *Mitigation*: Codified the 7-point provider qualification gate and one-shot test script above, and configured automatic model fallback to the `0910` snapshot (`openrouter/deepseek/deepseek-v4.1-flash`).
@@ -1,20 +0,0 @@
 # AGENTS.md (ESPHome Workspace)
 This directory is a self-contained ESPHome project space utilizing dynamic configuration loaders and an interactive flashing CLI.
 ## Rules & Design Standards
 ### Secret Management
 *   **NEVER** write plaintext Wi-Fi passwords, tokens, or API keys directly in the YAML configurations.
 *   **DO NOT** modify the `.gitignore` to allow checking in `.env` files.
 *   Use ESPHome's `!env_var VAR_NAME` to inject environment variables at compile-time. Any new secrets must be declared in `.env.template` and configured locally in `.env`.
 ### Configuration Standards
 *   Default board architecture is ESP32 (`nodemcu-32s` with `arduino` framework) unless specified.
 *   Naming conventions for configurations: `esdisplay_<name>.yaml` or `sensor_<name>.yaml`.
 *   All displays should use the `time` component with SNTP sync for accurate time rendering.
 *   Prefer importing sensors from Home Assistant over Native API client integrations, as it decouples rendering layouts from automation scripts.
 ### Build and Run Tools
 *   Use `uv run flash.py` to compile, validate, clean, or flash ESPHome configurations.
 *   Avoid triggering direct `esphome` cli calls unless doing isolated validation tests.
@@ -11,8 +11,9 @@ This directory contains the Kubernetes manifests and Helm charts for a single-no
 *   **SSL**: `cert-manager` (LetsEncrypt)
 ## Directory Structure
-*   **Top-level folders**: Each folder corresponds to a Kubernetes **namespace**.
+*   **Strict Namespace Mapping**: **Every top-level subdirectory in `k8s/` MUST correspond strictly to a Kubernetes namespace.**
-    *   Example: `mailu/` contains resources for the `mailu` namespace.
+    *   Example: `mailu/` contains resources for the `mailu` namespace, `grabengasse/` for `grabengasse`, `haumdaucher/` for `haumdaucher`, etc.
    *   **NO non-namespace folders**: Loose utility scripts belong in the root `scripts/` directory, application source code belongs in `projects/`, and general documentation belongs in namespace READMEs or `docs/`.
 *   **Documentation**: `README.md` is the **authoritative source** for deployment commands. Always check it before running commands.
 ## Code Style & Conventions
@@ -678,7 +678,7 @@ kubectl create ns migrate
 # backup on moritzgraf.de
 ssh moritzgraf.de "sudo su - docker -c 'cd /home/docker/mailu && docker-compose stop' && sudo su - root -c 'cd /home/docker && tar czvf mailu.tar.gz ./mailu && mv mailu.tar.gz /home/moritz/ && chown moritz. /home/moritz/mailu.tar.gz' && scp mailu.tar.gz haumdaucher.de:/home/moritz/"
 # terraform change
-cd ../terraform && terraform apply
+cd ../terraform/infrastructure && terraform apply
 # helm apply
 cd ../k8s
 helm upgrade --create-namespace --install mailu mailu/mailu -n mailu -f mailu/mailu.secret.yml
@@ -873,13 +873,13 @@ Grabengasse 7 home website and backend service deployed in the `grabengasse` nam
 # Login to local registry (if not already logged in)
 docker login registry.haumdaucher.de -u moritz -p "PPf10musSh!!"
-# Build and push backend image
+# Build and push images via root projects/grabengasse Makefile
-cd website/grabengasse_backend
+cd projects/grabengasse
-make all
+make build push
-# Build and push frontend image
+# Or build individual components:
-cd ../grabengasse_frontend
+cd projects/grabengasse/frontend && make all
-make all
+cd ../backend && make all
 ```
 ### Deploy to Kubernetes
@@ -170,10 +170,10 @@ The Authentik login screen is customized with a **Haumdaucher** glassmorphism th
  * **Branded Footer**: "HAUMDAUCHER Wurst und Spezialitäten n.e.V." subtle watermark.
 ### Managing Theme via Terraform
-Branding is provisioned via the `authentik_brand` resource in `terraform/authentik.tf` using the stylesheet `terraform/haumdaucher-theme.css`:
+Branding is provisioned via the `authentik_brand` resource in `terraform/infrastructure/authentik.tf` using the stylesheet `terraform/infrastructure/haumdaucher-theme.css`:
 ```bash
-cd terraform
+cd terraform/infrastructure
 terraform apply -target=authentik_brand.haumdaucher
 ```
@@ -22,7 +22,7 @@ This guide covers everything you need to know about managing users in Authentik
 | Question | Answer & Key Mechanism |
 | :--- | :--- |
 | **How to add new users?** | **4 Ways**: (1) Admin Web UI (`Directory > Users`), (2) **Invitations flow** (`Directory > Invitations` - recommended for self-service), (3) **Terraform** (`authentik_user` resource), or (4) **REST API / Python script** for bulk imports. |
-| **Can this be done in Terraform?** | **Yes.** Use `resource "authentik_user"` in `terraform/authentik.tf`. Supports custom attributes via `jsonencode()`, group assignments, and active status. |
+| **Can this be done in Terraform?** | **Yes.** Use `resource "authentik_user"` in `terraform/infrastructure/authentik.tf`. Supports custom attributes via `jsonencode()`, group assignments, and active status. |
 | **Can I change the email sent to the user?** | **Yes.** Configured in **Flows & Stages > Stages > Email Stage**. You can customize the subject line, token expiration, and HTML template (written in Django template syntax with access to user fields and custom attributes). |
 | **Can I limit what a user has access to?** | **Yes.** Through **Policy Bindings** attached to Applications: Group Membership Policies (e.g., `infra-admins` vs `users`), IP/Geo Policies, or Python Expression Policies checking custom attributes (e.g., only active club members). |
 | **How to handle Excel tables with custom attributes?** | Authentik stores arbitrary key-value pairs in `user.attributes` (JSON). You can import an Excel/CSV file with a Python script or Terraform `csvdecode()`, map fields like `haumdaucher_mitgliedsnummer` or `second_email`, and expose them to downstream apps (Nextcloud, Grafana, Gitea) via OIDC Scope Mappings. |
@@ -75,7 +75,7 @@ If you encounter this screen when opening an invite link:
 ### Solution: The Haumdaucher Custom Invitation Flow (`haumdaucher-invitation-flow`)
-We provision a dedicated, streamlined flow in `terraform/authentik.tf`:
+We provision a dedicated, streamlined flow in `terraform/infrastructure/authentik.tf`:
 ```mermaid
 graph LR
@@ -122,7 +122,7 @@ graph LR
 ## 🏗️ Method 2: User Provisioning via Terraform
-You can manage users, groups, and permissions directly in `terraform/authentik.tf`.
+You can manage users, groups, and permissions directly in `terraform/infrastructure/authentik.tf`.
 ### 1. Single User Definition
 ```hcl
@@ -161,7 +161,7 @@ max.mustermann,Max Mustermann,max@example.com,max.privat@gmail.com,HM-2024-042,f
 anna.schmidt,Anna Schmidt,anna@example.com,anna.work@company.de,HM-2024-043,true
 ```
-In `terraform/authentik.tf`:
+In `terraform/infrastructure/authentik.tf`:
 ```hcl
 locals {
  csv_users = csvdecode(file("${path.module}/users.csv"))
@@ -479,7 +479,7 @@ graph TD
 | **haumdaucher.de** | `haumdaucher.de` | ForwardAuth / OIDC | **`Admin`** ✅ | **`Member Access`** ✅ | ❌ *Denied* |
 ### Policy Bindings in Terraform
-All policy bindings are enforced directly in `terraform/authentik.tf`:
+All policy bindings are enforced directly in `terraform/infrastructure/authentik.tf`:
 ```hcl
 # 1. Admin-Only Tools (Restricted strictly to infra-admins)
@@ -0,0 +1,154 @@
 apiVersion: apps/v1
 kind: Deployment
 metadata:
  name: duckdb-backend
  namespace: family
  labels:
    app.kubernetes.io/name: duckdb-backend
    app.kubernetes.io/part-of: family-portal
 spec:
  replicas: 1
  strategy:
    type: Recreate
  selector:
    matchLabels:
      app.kubernetes.io/name: duckdb-backend
  template:
    metadata:
      labels:
        app.kubernetes.io/name: duckdb-backend
        app.kubernetes.io/part-of: family-portal
    spec:
      imagePullSecrets:
        - name: registry-haumdaucher-de
      initContainers:
        - name: git-init
          image: alpine/git:latest
          command: ["/bin/sh", "-c"]
          args:
            - |
              set -e
              export HOME=/tmp
              cd /wiki
              if [ ! -d ".git" ]; then
                echo "Initializing wiki repository on dedicated PVC..."
                REPO_URL="https://${GIT_SYNC_USERNAME}:${GIT_SYNC_PASSWORD}@git.moritzgraf.de/moritz/knowledge-wiki.git"
                git config --global http.sslVerify false
                git config --global --add safe.directory /wiki
                git config --global --add safe.directory '*'
                git init
                git remote add origin "$REPO_URL" || git remote set-url origin "$REPO_URL"
                git fetch origin main
                git checkout -f -B main origin/main
                echo "Clone completed successfully."
              else
                echo "Repository already initialized on PVC, updating..."
                REPO_URL="https://${GIT_SYNC_USERNAME}:${GIT_SYNC_PASSWORD}@git.moritzgraf.de/moritz/knowledge-wiki.git"
                git config --global http.sslVerify false
                git config --global --add safe.directory /wiki
                git config --global --add safe.directory '*'
                git remote set-url origin "$REPO_URL"
                if [ -f .git/shallow ]; then
                  echo "Unshallowing existing repository..."
                  git fetch --unshallow origin main || git fetch origin main
                else
                  git fetch origin main
                fi
                git rebase --abort 2>/dev/null || true
                git merge --abort 2>/dev/null || true
                git reset --hard origin/main
                git clean -fd
              fi
          env:
            - name: GIT_SYNC_USERNAME
              valueFrom:
                secretKeyRef:
                  name: wiki-git-credentials
                  key: git-sync-username
            - name: GIT_SYNC_PASSWORD
              valueFrom:
                secretKeyRef:
                  name: wiki-git-credentials
                  key: wiki-sync-token
          volumeMounts:
            - name: duckdb-wiki-data
              mountPath: /wiki
      containers:
        - name: duckdb-backend
          image: registry.haumdaucher.de/family/duckdb-backend:latest
          imagePullPolicy: Always
          env:
            - name: DATA_DIR
              value: "/wiki/data"
            - name: DUCKDB_DATA_DIR
              value: "/wiki/data"
            - name: WIKI_DIR
              value: "/wiki"
            - name: GIT_REPO_DIR
              value: "/wiki"
            - name: GIT_REPO_URL
              value: "https://git.moritzgraf.de/moritz/knowledge-wiki.git"
            - name: GIT_REMOTE_URL
              value: "https://git.moritzgraf.de/moritz/knowledge-wiki.git"
            - name: GIT_SYNC_USERNAME
              valueFrom:
                secretKeyRef:
                  name: wiki-git-credentials
                  key: git-sync-username
            - name: GIT_SYNC_PASSWORD
              valueFrom:
                secretKeyRef:
                  name: wiki-git-credentials
                  key: wiki-sync-token
            - name: GIT_SYNC_INTERVAL_SECONDS
              value: "60"
            - name: PORT
              value: "8000"
            - name: HOST
              value: "0.0.0.0"
          ports:
            - name: http
              containerPort: 8000
          volumeMounts:
            - name: duckdb-wiki-data
              mountPath: /wiki
          resources:
            requests:
              cpu: 50m
              memory: 128Mi
            limits:
              cpu: 1000m
              memory: 1Gi
          readinessProbe:
            httpGet:
              path: /duckdb-api/v1/healthz
              port: 8000
            initialDelaySeconds: 5
            periodSeconds: 10
          livenessProbe:
            httpGet:
              path: /duckdb-api/v1/healthz
              port: 8000
            initialDelaySeconds: 15
            periodSeconds: 20
      volumes:
        - name: duckdb-wiki-data
          persistentVolumeClaim:
            claimName: duckdb-wiki-data
 ---
 apiVersion: v1
 kind: Service
 metadata:
  name: duckdb-backend
  namespace: family
  labels:
    app.kubernetes.io/name: duckdb-backend
    app.kubernetes.io/part-of: family-portal
 spec:
  type: ClusterIP
  ports:
    - port: 8000
      targetPort: 8000
      name: http
  selector:
    app.kubernetes.io/name: duckdb-backend
@@ -0,0 +1,55 @@
 apiVersion: networking.k8s.io/v1
 kind: Ingress
 metadata:
  name: family-portal
  namespace: family
  annotations:
    kubernetes.io/ingress.class: "traefik"
    cert-manager.io/cluster-issuer: "letsencrypt-prod"
    kubernetes.io/tls-acme: "true"
    traefik.ingress.kubernetes.io/router.middlewares: auth-authentik-forwardauth@kubernetescrd
 spec:
  ingressClassName: traefik
  tls:
    - hosts:
        - family.haumdaucher.de
      secretName: family-haumdaucher-de-tls
  rules:
    - host: family.haumdaucher.de
      http:
        paths:
          - path: /duckdb-api
            pathType: Prefix
            backend:
              service:
                name: duckdb-backend
                port:
                  number: 8000
          - path: /tracking/mila
            pathType: Prefix
            backend:
              service:
                name: mila
                port:
                  number: 80
          - path: /tracking/moritz
            pathType: Prefix
            backend:
              service:
                name: moritz
                port:
                  number: 80
          - path: /outpost.goauthentik.io
            pathType: Prefix
            backend:
              service:
                name: duckdb-backend
                port:
                  number: 8000
          - path: /
            pathType: Prefix
            backend:
              service:
                name: mila
                port:
                  number: 80
@@ -0,0 +1,64 @@
 apiVersion: apps/v1
 kind: Deployment
 metadata:
  name: mila
  namespace: family
  labels:
    app.kubernetes.io/name: mila
    app.kubernetes.io/part-of: family-portal
 spec:
  replicas: 1
  selector:
    matchLabels:
      app.kubernetes.io/name: mila
  template:
    metadata:
      labels:
        app.kubernetes.io/name: mila
        app.kubernetes.io/part-of: family-portal
    spec:
      imagePullSecrets:
        - name: registry-haumdaucher-de
      containers:
        - name: mila
          image: registry.haumdaucher.de/family/mila:latest
          imagePullPolicy: Always
          ports:
            - name: http
              containerPort: 80
          resources:
            requests:
              cpu: 25m
              memory: 32Mi
            limits:
              cpu: 100m
              memory: 128Mi
          readinessProbe:
            httpGet:
              path: /tracking/mila/
              port: 80
            initialDelaySeconds: 5
            periodSeconds: 10
          livenessProbe:
            httpGet:
              path: /tracking/mila/
              port: 80
            initialDelaySeconds: 10
            periodSeconds: 15
 ---
 apiVersion: v1
 kind: Service
 metadata:
  name: mila
  namespace: family
  labels:
    app.kubernetes.io/name: mila
    app.kubernetes.io/part-of: family-portal
 spec:
  type: ClusterIP
  ports:
    - port: 80
      targetPort: 80
      name: http
  selector:
    app.kubernetes.io/name: mila
@@ -0,0 +1,64 @@
 apiVersion: apps/v1
 kind: Deployment
 metadata:
  name: moritz
  namespace: family
  labels:
    app.kubernetes.io/name: moritz
    app.kubernetes.io/part-of: family-portal
 spec:
  replicas: 1
  selector:
    matchLabels:
      app.kubernetes.io/name: moritz
  template:
    metadata:
      labels:
        app.kubernetes.io/name: moritz
        app.kubernetes.io/part-of: family-portal
    spec:
      imagePullSecrets:
        - name: registry-haumdaucher-de
      containers:
        - name: moritz
          image: registry.haumdaucher.de/family/moritz:latest
          imagePullPolicy: Always
          ports:
            - name: http
              containerPort: 80
          resources:
            requests:
              cpu: 25m
              memory: 32Mi
            limits:
              cpu: 100m
              memory: 128Mi
          readinessProbe:
            httpGet:
              path: /tracking/moritz/
              port: 80
            initialDelaySeconds: 5
            periodSeconds: 10
          livenessProbe:
            httpGet:
              path: /tracking/moritz/
              port: 80
            initialDelaySeconds: 10
            periodSeconds: 15
 ---
 apiVersion: v1
 kind: Service
 metadata:
  name: moritz
  namespace: family
  labels:
    app.kubernetes.io/name: moritz
    app.kubernetes.io/part-of: family-portal
 spec:
  type: ClusterIP
  ports:
    - port: 80
      targetPort: 80
      name: http
  selector:
    app.kubernetes.io/name: moritz
@@ -0,0 +1,6 @@
 apiVersion: v1
 kind: Namespace
 metadata:
  name: family
  labels:
    name: family
@@ -0,0 +1,15 @@
 apiVersion: v1
 kind: PersistentVolumeClaim
 metadata:
  name: duckdb-wiki-data
  namespace: family
  labels:
    app.kubernetes.io/name: duckdb-backend
    app.kubernetes.io/part-of: family-portal
 spec:
  accessModes:
    - ReadWriteOnce
  storageClassName: openebs-hostpath
  resources:
    requests:
      storage: 5Gi
@@ -0,0 +1,71 @@
 apiVersion: apps/v1
 kind: Deployment
 metadata:
  name: haumdaucher-website
  namespace: haumdaucher
  labels:
    app: haumdaucher
 spec:
  replicas: 2
  selector:
    matchLabels:
      app: haumdaucher
  template:
    metadata:
      labels:
        app: haumdaucher
    spec:
      imagePullSecrets:
      - name: registry-haumdaucher-de
      containers:
      - name: haumdaucher
        image: registry.haumdaucher.de/haumdaucher-website:latest
        imagePullPolicy: Always
        ports:
        - containerPort: 80
 ---
 apiVersion: v1
 kind: Service
 metadata:
  name: haumdaucher-service
  namespace: haumdaucher
 spec:
  selector:
    app: haumdaucher
  ports:
    - protocol: TCP
      port: 80
      targetPort: 80
  type: ClusterIP
 ---
 apiVersion: networking.k8s.io/v1
 kind: Ingress
 metadata:
  name: haumdaucher-ingress
  namespace: haumdaucher
  annotations:
    cert-manager.io/cluster-issuer: letsencrypt-prod
    kubernetes.io/ingress.class: nginx
    kubernetes.io/tls-acme: "true"
    nginx.ingress.kubernetes.io/force-ssl-redirect: "true"
    nginx.ingress.kubernetes.io/proxy-body-size: "0"
    nginx.ingress.kubernetes.io/proxy-buffering: "off"
    nginx.ingress.kubernetes.io/proxy-request-buffering: "off"
    nginx.ingress.kubernetes.io/ssl-redirect: "true"
 spec:
  ingressClassName: nginx
  rules:
  - host: haumdaucher.de
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: haumdaucher-service
            port:
              number: 80
  tls:
  - hosts:
    - haumdaucher.de
    secretName: haumdaucher-de-tls
@@ -10,15 +10,37 @@ spec:
 apiVersion: traefik.io/v1alpha1
 kind: Middleware
 metadata:
-  name: hosting-legacy-redirect
+  name: hosting-redirect-mila
  namespace: minio
 spec:
  redirectRegex:
-    regex: "^https?://([^/]+)/(mila|moritz|nutrition|sleep)\\.html(.*)"
+    regex: "^https?://([^/]+)/(?:family/)?(mila|sleep)\\.html.*"
-    replacement: "https://${1}/family/${2}.html${3}"
+    replacement: "https://family.haumdaucher.de/tracking/mila/"
-    permanent: false
+    permanent: true
 ---
-# Public Ingress for hosting.haumdaucher.de (Recipes, Public Assets)
+apiVersion: traefik.io/v1alpha1
 kind: Middleware
 metadata:
  name: hosting-redirect-moritz
  namespace: minio
 spec:
  redirectRegex:
    regex: "^https?://([^/]+)/(?:family/)?(moritz|nutrition)\\.html.*"
    replacement: "https://family.haumdaucher.de/tracking/moritz/"
    permanent: true
 ---
 apiVersion: traefik.io/v1alpha1
 kind: Middleware
 metadata:
  name: hosting-redirect-family-root
  namespace: minio
 spec:
  redirectRegex:
    regex: "^https?://([^/]+)/family/?$"
    replacement: "https://family.haumdaucher.de/"
    permanent: true
 ---
 # Public Ingress for hosting.haumdaucher.de (Recipes, Public Assets, Legacy Redirects)
 apiVersion: networking.k8s.io/v1
 kind: Ingress
 metadata:
@@ -29,7 +51,7 @@ metadata:
    cert-manager.io/cluster-issuer: "letsencrypt-prod"
    kubernetes.io/tls-acme: "true"
    traefik.ingress.kubernetes.io/router.priority: "10"
-    traefik.ingress.kubernetes.io/router.middlewares: minio-hosting-legacy-redirect@kubernetescrd,minio-hosting-add-prefix@kubernetescrd
+    traefik.ingress.kubernetes.io/router.middlewares: minio-hosting-redirect-mila@kubernetescrd,minio-hosting-redirect-moritz@kubernetescrd,minio-hosting-redirect-family-root@kubernetescrd,minio-hosting-add-prefix@kubernetescrd
 spec:
  ingressClassName: traefik
  rules:
@@ -48,8 +70,7 @@ spec:
    - hosting.haumdaucher.de
    secretName: hosting-haumdaucher-de-tls
 ---
-# Protected Ingress for /family (Family Dashboards, Nutrition & Sleep Analytics)
+# Protected Ingress for /family (Redirects and Authentik Outpost)
 # Protected by Authentik ForwardAuth
 apiVersion: networking.k8s.io/v1
 kind: Ingress
 metadata:
@@ -60,7 +81,7 @@ metadata:
    cert-manager.io/cluster-issuer: "letsencrypt-prod"
    kubernetes.io/tls-acme: "true"
    traefik.ingress.kubernetes.io/router.priority: "100"
-    traefik.ingress.kubernetes.io/router.middlewares: auth-authentik-forwardauth@kubernetescrd,minio-hosting-add-prefix@kubernetescrd
+    traefik.ingress.kubernetes.io/router.middlewares: minio-hosting-redirect-mila@kubernetescrd,minio-hosting-redirect-moritz@kubernetescrd,minio-hosting-redirect-family-root@kubernetescrd,auth-authentik-forwardauth@kubernetescrd,minio-hosting-add-prefix@kubernetescrd
 spec:
  ingressClassName: traefik
  rules:
@@ -57,7 +57,7 @@ The dashboard is exposed on your custom domain with TLS and basic authentication
 * **Username:** `admin`
 * **Password:** `moritz-z2m-2026`
-*Note: You can change the basic auth password by running the `k8s/htpasswd.py` script on your machine to generate a new bcrypt hash, then updating the `users` value in `k8s/monitoring/zigbee2mqtt.secret.yaml`.*
+*Note: You can change the basic auth password by running the `scripts/htpasswd.py` script on your machine to generate a new bcrypt hash, then updating the `users` value in `k8s/monitoring/zigbee2mqtt.secret.yaml`.*
 ---
@@ -60,8 +60,24 @@ To perform modifications or rotate api keys:
   ./k8s/openclaw/setup-garmin-cron.sh       # Nightly Garmin Connect sync (Daily 03:30)
   ./k8s/openclaw/setup-compaction-cron.sh   # Nightly multi-agent session compaction (Daily 04:45)
   ./k8s/openclaw/setup-itguy-cron.sh        # Weekly health audit (Sun 03:00)
   # Or run declarative reconciler:
   python3 k8s/openclaw/scripts/sync_crons.py
   ```
 ### 🛡️ Everything-as-Code (EaC) Governance for New Crons, Skills & Binaries (ADR 0003)
 To prevent PVC snowflake drift, **every** new automation, skill, CLI binary, or Python dependency added to OpenClaw MUST be persisted as code:
 1. **New Cron Jobs (`Crons-as-Code`)**:
   - **System / Recurring Automations**: Never leave a recurring cron job exclusively inside the pod's SQLite database (`openclaw cron add`). Every permanent automation MUST be codified in `k8s/openclaw/crons.yaml` (or the declarative cron sync scripts) and committed to `infrapuzzle`.
   - **Dynamic / User-Created Reminders**: Conversational or temporary crons created by agents at runtime must be exported to `knowledge-wiki/operations/crons-backup.json` during nightly backup so they survive PVC loss.
 2. **New Skills (`Skills-as-Code`)**:
   - Never leave newly created or agent-authored skills only in `/home/node/.openclaw/skills/`, `workspace*/skills/`, or `skill-workshop/` on the PVC.
   - All custom skills MUST be committed and pushed to the **`mop-skills`** repository (`git.moritzgraf.de/moritz/mop-skills`) so they are version-controlled and synced cleanly via the `git-sync` sidecar.
 3. **New CLI Binaries, Packages & Patches (`Dependencies-as-Code`)**:
   - Never manually drop binaries into `/home/node/.openclaw/bin/` or run ad-hoc `uv pip install` / `npm install -g` on the PVC without codifying them.
   - Every new binary (e.g. `ffmpeg`, `kubectl`, `jq`, `openhue`, `sonos`), Python package in `mcp-venv`, or runtime patch MUST be added to the declarative bootstrap script (`k8s/openclaw/scripts/bootstrap-deps.sh` / `configmap-scripts.yaml`) so a fresh PVC rebuild has 100% tool parity.
 ---
 ### 4. 🗂️ The Three Core Repositories Architecture & Weekly Self-Audit
@@ -32,6 +32,7 @@ This document captures fixed issues, operational quirks, and incident root-cause
 | **2026-10-09** | **Domain State & Reasoning Loop** | Telegram `#Mila` (Topic 22) messages stopped updating database; reasoning loops and timeouts on unclosed night session | `RESOLVED` | Identified unclosed 08.10 night session causing `z-ai/glm-5.3-flash` 4,000-word thinking loop. Closed session, backfilled naps, updated `datastore.py` to warn on open sessions without silent capping, supported stop by ID, and added prompt guardrails. |
 | **2026-10-10** | **Disk I/O & In-Pod Recovery Amnesia** | Telegram `#Recherche` (Topic 117) silent after voice note; probe killed pod; recovery marked wedged session done without replying | `RESOLVED` | Delivered research synthesis, decoupled `recherche.md` into Modus A/B, raised memory limit to 6Gi and probe timeout to 25s, scoped extraPaths to main agent, purged 1.8GB duplicate vector DBs (94% drop), and built automated turn-replay daemon with Telegram notice. |
 | **2026-10-11** | **Automation & Garmin Sync** | Garmin Connect sync stopped updating overnight; cron job missing from OpenClaw; untracked activities folder | `RESOLVED` | Identified `garmin-nightly-mirror` was never registered in OpenClaw; created missing `activities` directory, hardened `setup-garmin-cron.sh` with JSON declaration lookup and `--announce`, registered automation (Daily 03:30 Berlin), and verified full sync through 2026-10-11. |
 | **2026-10-12** | **Compaction Tuning & History Retention** | Session bloat during the day (~58k tokens) in Topic 21; tuning compaction strength to avoid binary choice between 0-token reset and bloat | `RESOLVED` | Configured `keepRecentTokens: 3000`, `recentTurnsPreserve: 2`, `maxActiveTranscriptBytes: 180kb`. Converted Tier A to deep-compaction with fallback, preserving conversational history while shrinking sessions from 30k-127k down to 1k-4k tokens. |
 ---
@@ -799,3 +800,254 @@ This document captures fixed issues, operational quirks, and incident root-cause
  - Always register cron jobs with `--declaration-key` and check existing jobs via JSON rather than table text grep.
  - Document all declarative setup scripts in `AGENTS.md` under `Register / Sync Automations`.
  - Ensure all data directories (`daily`, `sleep`, `activities`) are safely created in `GarminMirrorWriter`.
 ### Issue 25: Self-Quoting Duplicate Meal Logging & Turn Bleed on High-Context Session (Topic 21)
 - **Date**: 2026-10-12
 - **Severity**: Medium (Morning porridge was logged twice on 2026-10-12, inflating daily intake to 1,906 kcal instead of 1,611 kcal; redundant pudding correction was appended to 2026-10-11)
 - **Symptom**:
  Moritz noticed on the personal health dashboard (`moritz.html`) that his morning porridge had been recorded twice.
 - **Root Cause Isolated via Rapid Triage**:
  1. **Extreme Context Bloat**: Session `aff9fd77` in Topic 21 had accumulated **58,856 tokens** across 103 events due to heavy tool results and previous turns.
  2. **External Tool Attention Disorientation**:
     - At 08:41 (SEQ 32–37), the morning porridge was properly logged in 4 individual items (`01M4QDGVY...` to `01M4QDH51...`, ~295 kcal total).
     - At 11:35 (SEQ 39), Moritz sent an audio message reporting 1.5 Brezen mit Butter, Weißwürste, and Händlmaier sweet mustard.
     - The assistant performed an external Perplexity web search for mustard calories, which returned ~16 kB of text.
     - Upon receiving the search result at SEQ 49, `z-ai/glm-5.3-flash` suffered severe attention disorientation: seeing `replyToId: 21` (standard Telegram forum topic metadata) and earlier messages in context, it hallucinated that earlier completed turns were unhandled requests.
  3. **Self-Quoting Duplicate Execution**:
     - In SEQ 51, the model literally copied its own earlier assistant confirmation text from SEQ 37 (`✅ *Morgenporridge (60 g Mischung · 60 ml Hafermilch · 120 ml Wasser · 50 g Kiwi)* geloggt`) and executed `datastore.py add` to log a duplicate 295 kcal composite portion (`01M4QQH2KJ85TB5N2MBM230ZYN`).
     - In SEQ 53, it did the same for yesterday's pudding correction (`01M4QQHMG8S30B43241B10ND3J`, +260 kcal).
 - **Resolution**:
  1. **Deleted Duplicate Events via Datastore CLI**:
     - Deleted duplicate porridge event `01M4QQH2KJ85TB5N2MBM230ZYN` (295 kcal) and duplicate pudding event `01M4QQHMG8S30B43241B10ND3J` (260 kcal) via `datastore.py delete`.
     - Re-rendered all views and published updated dashboards (`render_views.py` & `update_moritz_website.py`). Today's total restored to exact **1.611 kcal** (**75,1 g Protein**).
  2. **Notified Telegram Topic 21**:
     - Sent confirmation message (Message ID `2700`) to Topic 21 detailing the correction and showing the cleaned-up macros.
  3. **Hardened `knowledge-wiki/agents/koch.md`**:
     - Added strict rule: *„KEINE DUPLIKATE ODER SELBST-ZITATE LOGGEN“*. Explicitly forbidden from parsing previous assistant confirmation messages as intake items and forbidden from re-logging earlier completed meals.
  4. **Session Reset**:
     - Safely deleted and archived the bloated 58k-token session via `openclaw sessions delete`.
  5. **Triage Script Optimization**:
     - Updated `openclaw-triage.py` to automatically exclude background `:heartbeat` sessions when querying by topic ID.
 - **How to Avoid Recurrence**:
  - System prompts for transactional logging agents must explicitly forbid treating assistant confirmation messages as intake events.
  - Agents must enforce strict focus on the very last user message at the tail of the transcript.
  - Reset sessions periodically when context grows beyond 30k tokens for simple transactional logging tasks.
 ### Issue 26: Compaction Parameter Tuning & Shift to Deep-Compaction with History Retention
 - **Date**: 2026-10-12
 - **Severity**: Medium (Evaluating why sessions grew to ~58k tokens despite nightly maintenance; eliminating the binary choice between complete 0-token reset and bloated 58k-token sessions)
 - **Symptom**:
  Moritz inquired why Topic 21 had reached ~58k tokens and asked whether nightly maintenance was functioning properly. He requested investigating if compaction could be tuned to aggressively compact while preserving a few recent tokens/history for all agents instead of performing hard 0-token resets.
 - **Root Cause Isolated**:
  1. **Nightly Job Execution Verified**: The nightly maintenance cron (`ce39bbf8-b83f-453e-be53-04e27db27b78`, schedule `45 4 * * * @ Europe/Berlin`) had indeed run successfully at 04:45:00 Berlin (`1791773100019 ms`).
  2. **Intraday Context Inflation**: The 58k tokens were NOT carried over from previous days; they were accumulated within the same day between 07:20 and 11:55 due to base prompt/tools (~18.2k baseline), 10 queries in Turn 1, multiple Perplexity web searches (~16 kB each), and `cat foods.jsonl`.
  3. **Overly Lenient Auto-Compaction Settings**:
     - `keepRecentTokens: 15000`: Left 15k tokens verbatim in memory after compaction.
     - `maxActiveTranscriptBytes: "400kb"`: Did not trigger inline safeguard compaction during the day until files reached 400 kB (~50k+ tokens).
     - `recentTurnsPreserve: 3` (default): Preserved 3 full turns with potentially huge tool outputs verbatim.
  4. **Binary Tier A Trade-off**: Tier A agents (`koch`, `hebamme`, `shopping`) were previously hard-reset to 0 (`openclaw sessions delete`) because state is externalized in DuckDB. While preventing hallucinations, this discarded recent conversational continuity.
 - **Resolution**:
  1. **Tuned Compaction Parameters**:
     - Updated both live configuration (`/home/node/.openclaw/openclaw.json`) and declarative manifest (`k8s/openclaw/openclaw-instance.secret.yaml`):
       - `keepRecentTokens: 3000` (down from 15,000; forces dense LLM summarization).
       - `recentTurnsPreserve: 2` (preserves only the last 2 turns verbatim).
       - `maxActiveTranscriptBytes: "180kb"` (down from 400kb; triggers proactive compaction before intraday sessions exceed ~25k tokens).
  2. **Switched Tier A from Hard-Reset to Deep-Compaction**:
     - Updated `k8s/openclaw/setup-compaction-cron.sh` and `k8s/openclaw/scripts/compact_sessions.py`.
     - Tier A now calls `openclaw sessions compact <key> --agent <agent>` with fallback to `--max-lines 40` if built-in safeguard summarization quality checks fail.
     - Lowered Tier B thresholds: `THRESHOLD_TOKENS = 15000`, `THRESHOLD_TRANSCRIPT_BYTES = 200000` (200 KB), `THRESHOLD_EVENT_COUNT = 30`.
     - Re-registered cron job in OpenClaw (`setup-compaction-cron.sh`).
  3. **Verified Live Reduction**:
     - `koch`: 29,783 $\rightarrow$ **2,098 tokens** (Tier A deep-compacted).
     - `hebamme`: Truncated to 40 lines (Tier A fallback).
     - `fitness`: 101,950 $\rightarrow$ **5,318 tokens**.
     - `recherche`: 127,356 $\rightarrow$ **4,323 tokens**.
     - `grabengasse_media`: 49,447 $\rightarrow$ **3,356 tokens**.
     - `doktor`: 20,259 $\rightarrow$ **1,079 tokens**.
 - **How to Avoid Recurrence**:
  - Keep `keepRecentTokens: 3000` and `maxActiveTranscriptBytes: 180kb` in declarative manifests.
  - Rely on deep-compaction with fallback rather than hard-resets across all topic agents.
 ---
 ### Issue 27: OpenClaw Vision Routing Bypass, GLM-5.3-Flash Image OCR Failure, and Tool-Calling Protocol Hardening
 - **Date**: 2026-10-12
 - **Severity**: High (Photos in Topic 21 #Kochen rejected as "blurry" despite 1080p high quality, turns halted with "The tool run finished, but no final summary was produced", tool errors in recherche/grabengasse)
 - **Symptom**:
  1. The user posted high-resolution photos of food packaging and nutrition labels (e.g. IronMaxx Clear Whey Isolate Zero Kirsche, 1080x1064 px).
  2. Koch agent repeatedly responded that the photo was blurry and illegible.
  3. Internal chain-of-thought hallucinated that the label was a small blurry thumbnail with ~4px text reading "MIRKIC" instead of "KIRSCHE".
  4. The turn completed with `stopReason: "stop"` without emitting any visible text, causing OpenClaw to emit `The tool run finished, but no final summary was produced. I did not repeat any completed actions.`
  5. Ad-hoc Python image manipulation failed due to missing `PIL` (Pillow).
  6. Sporadic tool call errors across topics: `tool_search` wrapped in `tool_call`, `sessions_history` negative offsets, `ask_user` flat parameters, missing `googleapiclient` without `uv run`.
 - **Root Cause**:
  1. **OpenClaw `imageModel` Fallback Behavior**:
     OpenClaw's configuration schema defines `imageModel` as: *"Optional image model used when the primary model lacks image input."*
     Because `z-ai/glm-5.3-flash` advertises `input_modalities: ["text", "image", "video"]` on OpenRouter, OpenClaw considered it image-capable and never routed images to `imageModel: "openrouter/google/gemini-3.8-flash"`.
     GLM-5.3-Flash's actual vision perception on dense German labels is poor, leading it to misread text, conclude it cannot read it, and finish its thinking block without generating any output text.
  2. **Empty Turn Finalization Fallback**:
     When a model finishes with only thinking tokens and zero output text or tool calls, OpenClaw's delivery mirror triggers `settled-finalization-fallback`.
  3. **Python Runtime Deficiencies**:
     Core libraries (`pillow`, `google-api-python-client`, `pypdf`) were not installed in the persistent Python interpreter at `/home/openclaw/.openclaw/.local/python/...`.
 - **Resolution**:
  1. **Dedicated Vision Model for Koch**:
     Configured `koch`'s primary model to `openrouter/google/gemini-3.8-flash` (fallbacks: `glm-5.3-flash`, `deepseek-v4.1-flash`) both live via `openclaw config set` and in `openclaw-instance.secret.yaml`. Gemini 3.8 Flash provides SOTA OCR and dense-table extraction at $0.075 / 1M cached prompt tokens.
  2. **Prompt-Hardening in `knowledge-wiki`**:
     - Updated `knowledge-wiki/agents/koch.md` with strict rules: mandatory visible text output on every turn (no silent thinking stops), Vision-first protocol (transcribe all tables without claiming blurriness).
     - Updated `knowledge-wiki/agents/README.md` with cross-agent tool-calling standards (`tool_search` top-level only, `sessions_history` non-negative offset + `sessionKey`, `ask_user` questions array, `uv run` for Python scripts).
  3. **Pre-installed Python Libraries**:
     Installed `pillow`, `google-api-python-client`, and `pypdf` into the persistent Python environment using `uv pip install --break-system-packages`, and added the command to `openclaw-instance.secret.yaml` for permanent self-healing.
  4. **Retroactive Meal Intake Recovery & Compaction**:
     The user prompt (`540g selbst gemachte Lasagne mit bechqmele sauce`) that was dropped during the unfinalized GLM loop was logged retroactively into DuckDB (`01M4RQT5PFNN7J4307TCRM3E80`, ~864 kcal, ~43.2 g Protein). Daily totals (both portions 540g + 430g and the 30g Clear Whey shake) updated to 3,266 kcal / 177.9 g protein, web dashboards re-rendered, and Topic 21 compacted from 49.6k tokens down to 4.6k tokens.
 - **How to Avoid Recurrence**:
  - For agents that routinely process user photos or document scans, assign dedicated vision models (`google/gemini-3.8-flash`) as the agent's primary model rather than relying on `agents.defaults.imageModel`.
  - Maintain the response guarantee in agent prompts to prevent empty turns when reasoning models encounter uncertainty.
 ---
 ### Issue 28: Topic 20 #Sport Transcript Blindness: GLM-5.3-Flash Reasoning Hallucination on Audio Inbound Attachments
 - **Date**: 2026-10-12
 - **Severity**: Medium (User sent 24s voice note requesting Cable Workout A evaluation from Garmin; transcript was echoed to Telegram but agent claimed no transcript arrived)
 - **Symptom**:
  1. The user recorded a 24s voice note asking for a Garmin evaluation of "Cable Workout A" (history, frequency, progression).
  2. The gateway transcribed the audio correctly via Whisper and echoed it back to Telegram (`messageId: 2739`).
  3. The prompt delivered to the agent contained the full transcript: `[Audio]\nTranscript:\nIch habe gerade ein Workout gemacht, das Cable Workout A...`.
  4. Yet after 78 tool steps and 19.5 minutes of looping, the agent (`fitness`) replied:
     *"Moin mop 👋 Dein Sprachnachricht ist bei mir ohne Transkript angekommen – ich kann nur raten, was drin war. 🎙️"*.
 - **Root Cause**:
  1. **GLM-5.3-Flash Multimodal Confusion**:
     The message context included both the text transcript and the staged `.ogg` attachment in `message.media`.
     In its internal reasoning (`thinking`), GLM-5.3-Flash hallucinated:
     *"Voice message from Moritz. Need transcript — it's not provided this time? The context shows a voice message but no transcript. Hmm, the inbound is voice; transcript usually would be in context. Not visible. Maybe I need to transcribe."*
     The model fixated on the audio file attachment, concluded it had to transcribe the file itself, and completely ignored the actual transcript string right below `[Audio]\nTranscript:`.
  2. **19.5-Minute Looping Failure**:
     The agent attempted to locate local audio tools (`which whisper ffmpeg`), searched memory files, found an unrelated October 7 note about protein powder in the wiki, and spent 78 turns cycling between file reads until giving up with a false negative.
 - **Resolution**:
  1. **Model Upgraded to Gemini 3.8 Flash**:
     Replaced `primary: "openrouter/z-ai/glm-5.3-flash"` with `openrouter/google/gemini-3.8-flash` (fallbacks: `glm-5.3-flash`, `deepseek-v4.1-flash`, `qwen3.8-flash`) for agent `fitness` both live via `openclaw config set` and declaratively in `k8s/openclaw/openclaw-instance.secret.yaml`. Gemini 3.8 Flash natively handles multimodal metadata without overlooking inline text transcripts.
  2. **Garmin Workout Data Synced & Evaluated**:
     Executed `garmin_sync.py` to mirror the latest workouts into `data/garmin/activities/2026-10.jsonl`.
     Retrieved all 3 sessions of Moritz's `SuperSetACable-55mins` (2026-09-28, 2026-10-06, 2026-10-12) and extracted the workout progression data.
 - **How to Avoid Recurrence**:
  - In agent system prompts, reinforce that `[Audio]\nTranscript:\n<text>` already contains the authoritative, finalized speech-to-text result and requires no local audio file re-processing.
 ### Issue 29: Decoupled Vision Perception — Gemini 3.8 Flash Media-Understanding with GLM-5.3-Flash Primary Chat Engine
 - **Symptoms**:
  - Switching the primary agent model completely to `google/gemini-3.8-flash` changed the entire conversational tone and agent persona across all text turns, whereas only high-fidelity OCR and nutrition image perception were desired.
  - When `openrouter/z-ai/glm-5.3-flash` was the primary model, OpenClaw previously routed photos natively to GLM because the OpenRouter model catalog declared multimodal capability (`image`), causing GLM to fail at OCR reading of nutritional labels.
 - **Root Cause & Architectural Discovery**:
  1. OpenClaw checks `activeModelSupportsNativeVision` and `resolveRunModelHasVision`. If the primary model advertises vision on OpenRouter AND no explicit image understanding models are declared in `tools.media.models`, OpenClaw bypasses the `media-understanding` pipeline and passes raw images natively to the chat engine.
  2. Because GLM-5.3-Flash struggled with German nutritional tables, the entire primary model had been switched to Gemini 3.8 Flash, which Moritz explicitly rejected ("Haben wir nun das Modell für den Koch agent komplett auf Gemini 3.8 flash gewechselt? Das wollte ich nicht. Nur für die Bilderkennung bitte.").
 - **Resolution**:
  1. **Reverted Primary Chat Models**:
     Reverted `agents.entries.koch.model.primary` and `agents.entries.fitness.model.primary` back to `openrouter/z-ai/glm-5.3-flash` (with fallbacks `deepseek-v4.1-flash`, `qwen3.8-flash`) in both `openclaw.json` and `openclaw-instance.secret.yaml`.
  2. **Configured Dedicated Media-Understanding Image Engine**:
     Added an explicit `image` capability model under `tools.media.models`:
     ```yaml
     tools:
       media:
         image:
           enabled: true
           preferredModel: "openrouter/google/gemini-3.8-flash"
         models:
           - provider: openrouter
             model: "google/gemini-3.8-flash"
             capabilities: ["image"]
             prompt: "Beschreibe das Bild detailliert auf Deutsch. Wenn Nährwertangaben, Zutaten, Barcode, Verpackungstext oder handschriftliche Notizen zu sehen sind, transkribiere alle Zahlen, Gramm-Angaben und Nährwerte (Kalorien, Eiweiß/Protein, Kohlenhydrate, Fett) vollständig und exakt."
     ```
  3. **Declared Text-Only Override for GLM**:
     Under `models.providers.openrouter.models`, registered `z-ai/glm-5.3-flash` with `input: ["text"]`. This signals to OpenClaw that GLM must never receive raw images natively, forcing automatic routing of all image attachments through Gemini 3.8 Flash media-understanding before handing off enriched text to GLM.
  4. **Updated Persisted SQLite Sessions**:
     Reset `session_nodes` for `agent:koch:telegram:group:-1004326921510:topic:21` and `agent:fitness:telegram:group:-1004326921510:topic:20` to `z-ai/glm-5.3-flash`.
 - **How to Avoid Recurrence**:
  - Always decouple perception tasks (OCR, image description, speech-to-text) into `tools.media` or `imageModel`, keeping primary conversational models focused on reasoning and dialogue without changing the core chat persona.
 ---
 ### Issue 30: GLM-5.3-Flash Malformed Tool Call Stream Aborts (`streamlake/fp8`), Cold HDD Prompt Assembly Stall, and Fleet-Wide Migration to DeepSeek V4.1 Flash
 - **Date**: 2026-10-17
 - **Severity**: High (Topic 164 `#Grabengasse & Media` failed with `Provider returned an incomplete or malformed tool call`; 12 total occurrences across 5 agents in 17 days; 504.5s cold-disk event-loop stall on first morning request)
 - **Symptom**:
  1. At 07:11:02 CEST, Moritz sent a voice note in Topic 164 (`#Grabengasse & Media`, agent `grabengasse_media`): *"Kannst du mir auf dem Sonos in der Küche die Bibi Blocksberg Playlist Der Affe ist los abspielen?"*
  2. The turn stalled for **8 minutes and 24 seconds** (`504,493 ms`) during `system-prompt` assembly (`cpuCoreRatio=0.005`, pure disk I/O wait) before sending the first LLM request at 07:19:26 CEST.
  3. In Turn 1 (`SEQ 175`), `z-ai/glm-5.3-flash` called `tool_search({"query": "sonos spotify play"})`. In Turn 2 (`SEQ 177`), it called `tool_describe({"name": "mcp:spotify:spotify__search"})`.
  4. In Turn 3 (`SEQ 179`, `responseId: gen-1792214444-T46fmmBLqgmCCe0YJp4X`), after generating 326 reasoning tokens (`"Search for 'Bibi Blocksberg Der Affe ist los' using mcp:spotify:spotify__search"`), the upstream OpenRouter provider (`streamlake/fp8`) aborted the stream mid-JSON while serializing nested `tool_call({"id": "mcp:spotify:spotify__search", "args": {...}})` arguments:
     `stopReason: "error"`, `errorMessage: "Provider returned an incomplete or malformed tool call"`.
  5. OpenClaw only retries or triggers model fallbacks on HTTP status errors (`429`, `502`, `503`, `504`) prior to stream start—not when an HTTP `200 OK` SSE stream terminates mid-generation with a malformed tool-call chunk.
 - **Root Cause & Fleet Forensics**:
  1. **`z-ai/glm-5.3-flash` Nested Tool-Call Fragility on `streamlake/fp8` & `siliconflow/fp8`**:
     - Across October 1–17, 2026, `Provider returned an incomplete or malformed tool call` occurred **12 times** across `main` (6×), `grabengasse_media` (3×), `koch` (1×), `hebamme` (1×), and `doktor` (1×)—exclusively on `z-ai/glm-5.3-flash`, always right after `tool_describe` when emitting nested `tool_call` JSON payloads.
  2. **Suboptimal OpenRouter Provider Routing**:
     - `extra_body.provider.order` for `z-ai/glm-5.3-flash` listed `"cloudflare"` first (which does not host `glm-5.3-flash` on OpenRouter), falling through to `streamlake/fp8` (91.7% uptime) and `siliconflow/fp8` (74.1% uptime), and did not block `fp4` (`nvfp4`) quantizations (`phala`, `atlas-cloud`, `parasail`).
  3. **Fleet-Wide Cost & Cache-Hit Economics (`DeepSeek V4.1 Flash` vs. `GLM 5.3 Flash`)**:
     - Over the 17-day period (Oct 1–17, 2026), 73% to 94% of all tokens across interactive agents (`21.93M` `cacheRead` vs. `8.94M` uncached input) and background heartbeats (`22.86M` `cacheRead` vs. `7.73M` uncached input) were prompt cache reads.
     - While `deepseek/deepseek-v4.1-flash` has a slightly higher base uncached prompt rate (`$0.14–$0.15/M` vs. `$0.06–$0.075/M`), its top `fp8` providers (`deepinfra` and `streamlake`, both 100% uptime and full `tool_choice` support) charge **3.5× to 10× less for `cacheRead` tokens** (`$0.0042/M` on DeepInfra, `$0.0030/M` on StreamLake vs. `$0.015–$0.030/M` on GLM 5.3 Flash).
     - Consequently, running the entire fleet (interactive agents + background heartbeats) on `deepseek/deepseek-v4.1-flash` via `deepinfra`/`streamlake` costs **~$2.69 over 17 days (~$4.75/month)** vs. **$4.50 actual on `GLM 5.3 Flash` (~$7.95/month)**—a **~40% net cost reduction** alongside 0 malformed tool calls.
  4. **Cold Rotational HDD Read Stall After Nightly Backups**:
     - Nightly backups (`03:30`) and compaction (`04:45`) evicted the Knowledge Wiki and agent workspace `*.md` files from the Linux kernel page cache, causing the first morning turn's synchronous `system-prompt` loader to block on rotational SATA HDD seeks for 504.5s.
 - **Resolution**:
  1. **Fleet-Wide Migration to `openrouter/deepseek/deepseek-v4.1-flash-1017` (with `deepseek-v4.1-flash` 0910 as first fallback)**:
     - Switched `agents.defaults.model.primary`, `utilityModel`, `heartbeat.model`, `subagents.model`, `memory-core.config.dreaming.model`, and all interactive agent entries (`main`, `fitness`, `koch`, `hebamme`, `travel`, `shopping`, `regensburg`, `recherche`, `doktor`, `itguy`, `grabengasse_media`, `mila_tracker`) to the newly released October 17, 2026 snapshot `openrouter/deepseek/deepseek-v4.1-flash-1017` (Artificial Analysis Intelligence Index 39.5 vs. 24.7 on 0910, and 30% cheaper on DeepInfra at `$0.098/M` prompt, `$0.294/M` completion, `$0.00294/M` `cacheRead`), with `openrouter/deepseek/deepseek-v4.1-flash`, `openrouter/z-ai/glm-5.3-flash`, and `openrouter/qwen/qwen3.8-flash` as fallbacks (`nutrition_tracker` remains on `openrouter/google/gemini-3.8-flash`).
  2. **Preserved Decoupled Vision Perception (Issue 29 Compatibility)**:
     - Registered both `deepseek/deepseek-v4.1-flash-1017` and `deepseek/deepseek-v4.1-flash` with `input: ["text"]` under `models.providers.openrouter.models` in `openclaw-instance.secret.yaml` so OpenClaw continues routing all image attachments through `tools.media.image` (`google/gemini-3.8-flash`) for OCR before passing enriched text to DeepSeek V4.1 Flash.
  3. **Hardened OpenRouter Provider & Quantization Routing (`extra_body.provider`)**:
     - Configured `openrouter/deepseek/deepseek-v4.1-flash-1017` with `order: ["deepinfra", "inference-net", "parasail", "cloudflare"]`, `quantizations: ["fp8", "bf16", "unknown"]`, and `ignore: ["morph", "baseten", "deepseek", "open-inference", "decart", "sail-research", "wafer"]` (live routing tests showed `morph/fp8` is rejected by OpenRouter's `Filter by Tool Compatibility` when `tools` are passed, `deepseek` is blocked by account training-opt-out guardrails, and `baseten` returns HTTP 429).
     - Configured fallback `openrouter/deepseek/deepseek-v4.1-flash` (`0910`) with `order: ["deepinfra", "streamlake", "inference-net", "digitalocean", "venice", "nebius"]` and `quantizations: ["fp8", "bf16", "unknown"]`.
     - Cleaned up `openrouter/z-ai/glm-5.3-flash` fallback routing (`order: ["morph", "near-ai", "digitalocean", "venice", "streamlake"]`, `quantizations: ["fp8", "bf16", "unknown"]`, blocking `fp4`).
  4. **Direct MCP Tool Fastpaths & 1-Turn Sonos Playbook for `grabengasse_media` (Topic 164)**:
     - Added exact MCP tool IDs (`mcp:spotify:spotify__search`, `mcp:spotify:spotify__play`, `mcp:spotify:spotify__transfer_playback`, `mcp:jelly:jelly__jelly_search`, `mcp:jelly:jelly__jelly_request`, `mcp:homeassistant:homeassistant__ha_get_state`, `mcp:homeassistant:homeassistant__ha_call_service`) as well as all verified Sonos entity IDs (`media_player.bad`, `media_player.wohnzimmer`, `media_player.kuche_sonos`, `media_player.kuche_ikea`, `media_player.dining_room`) and Sonos `source_list` favorites (`"Fusion 2026 Sets"`, `"ChilloutTechno"`, `"deephouse"`, `"OberDITSCHI"`, etc.) directly to `openclaw-instance.secret.yaml`, `knowledge-wiki/agents/grabengasse_media.md`, and `/home/openclaw/.openclaw/workspace-grabengasse_media/AGENTS.md`.
     - Eliminates both the 2 MCP discovery turns (`tool_search` + `tool_describe`) and the 2 file-read turns (`read("USER.md")`, `read("MEMORY.md")`, `read("SKILL.md")`).
  5. **Extended Linux Page-Cache Pre-Warming to Knowledge Wiki & Workspace Markdown Files**:
     - Updated `k8s/openclaw/scripts/gateway-preflight.mjs` and `k8s/openclaw/scripts/compact_sessions.py` (which now also runs `prewarm_page_cache()` at the end of the 04:45 nightly run) to pre-read all Knowledge Wiki (`*.md`, `*.jsonl`) and `workspace*/` `*.md` files into RAM, preventing morning `system-prompt` disk freezes.
  6. **SQLite `session_nodes` Trigger (`entry_valid`) & Subagent Vector Re-Indexing Fix (`extraPaths: []`)**:
     - Discovered that SQLite `session_nodes` has an `AFTER UPDATE OF entry_json` trigger (`session_nodes_entry_valid_after_entry_update`) that resets `entry_valid = 0` whenever `entry_json` is modified, throwing `SessionCanonicalKeyMigrationRequiredError` until `UPDATE session_nodes SET entry_valid = 1` is executed.
     - Hardened `k8s/openclaw/scripts/recover_sessions.py` to always enforce `PRAGMA foreign_keys = ON` before deleting trailing error turns, set `entry_valid = 1` across all rows, and reset `attempts = 0` on pending `channel_ingress_events` in `state/openclaw.sqlite`.
     - Explicitly set `memory.search.extraPaths: []` at the top level in `openclaw-instance.secret.yaml` and `dedup_subagent_vectors.py` so `mergeMode: merge` does not leave `extraPaths` active globally in `openclaw.json`, preventing subagents from re-embedding 4,059 wiki chunks on their first turn after startup.
 - **How to Avoid Recurrence**:
  - Always enforce `quantizations: ["fp8", "bf16"]` in OpenRouter `extra_body.provider` for tool-calling agents so OpenRouter never routes to degraded `fp4` (`nvfp4`) endpoints.
  - Whenever updating `entry_json` in `session_nodes` via SQLite, always follow up with `UPDATE session_nodes SET entry_valid = 1` in a separate statement (after the `AFTER UPDATE OF entry_json` trigger fires), and always set `PRAGMA foreign_keys = ON` before deleting from `transcript_events`.
  - Keep Knowledge Wiki and workspace Markdown files in the nightly `prewarm_page_cache()` pass so morning turns hit RAM (`<50ms`) instead of cold rotational disks.
 ---
 ### Issue 31: DeepSeek V4.1 Flash Tool-Call Truncation (8,192 Default Token Limit), Provider Re-Ranking, and Fireworks Addition
 - **Date**: 2026-10-18
 - **Severity**: High (Topic 116 `#Regensburg`, agent `regensburg`, failed with `Provider returned an incomplete or malformed tool call` and wedged in status `failed`)
 - **Symptom**:
  1. Moritz sent an audio message to Topic 116 (`#Regensburg`): *"Ach ja, auf der Website soll dann quasi, also die Karte soll so aussehen, dass quasi die Anzahl an Sternen da steht, direkt auf der Karte... wo sind die besten Dönerladen in der City..."*
  2. The agent prepared the dataset `/tmp/doner_web.json` (45 places, 21 KB) and then invoked `openrouter/deepseek/deepseek-v4.1-flash-1017` to construct the single-page interactive Leaflet map application.
  3. In Turn 160 (`responseId: gen-1792313455-dX7teZlPrKNOMq1BeMCe`), after 3,376 reasoning tokens (`reasoningTokens`), the model streamed the tool call (`exec`) with the HTML/JS website.
  4. At exactly **8,192 output tokens** (`output: 8192`), the stream was abruptly cut off by OpenRouter/Cloudflare (`finish_reason: "length"`).
  5. Because the truncation occurred mid-stream inside the tool-call argument JSON payload, OpenClaw threw:
     `stopReason: "error"`, `errorMessage: "Provider returned an incomplete or malformed tool call"`.
  6. The agent sent `⚠️ openrouter/deepseek/deepseek-v4.1-flash-1017 request failed.` to Telegram and remained stuck in `status: "failed"`.
 - **Root Cause**:
  1. **Missing `maxTokens` / `max_tokens` Configuration**:
     - `models.providers.openrouter.models` registered `deepseek/deepseek-v4.1-flash-1017` without `maxTokens`.
     - When `options.maxTokens` is unset, OpenClaw omits `max_tokens` from `/chat/completions`.
     - OpenRouter / Cloudflare defaults to **8,192 tokens** when `max_tokens` is omitted.
  2. **Reasoning Token Competition**:
     - Unlike standard chat models, DeepSeek V4.1 Flash emits 2,000–3,500 reasoning tokens per complex turn, which count directly against the 8,192 completion limit. This left only ~4,800 tokens for the generated code, causing truncation on large single-page web applications.
  3. **Suboptimal Provider Ordering in ADR 0002**:
     - `order: ["deepinfra", "inference-net", "parasail", "cloudflare"]` had Cloudflare in 4th place behind Parasail.
     - Cloudflare offers `$0.10/M` prompt, `$0.60/M` completion, and `$0.003/M` `cacheRead` (3× cheaper than Parasail), with a **943,718** completion token limit.
 - **Resolution**:
  1. **Configured 64k Completion Headroom (`maxTokens: 65536`)**:
     - Added `maxTokens: 65536` and `contextWindow: 1048576` under `models.providers.openrouter.models` in `openclaw-instance.secret.yaml`.
     - Added `max_tokens: 65536` to both `params` and `params.extra_body` for `deepseek/deepseek-v4.1-flash-1017` and `deepseek/deepseek-v4.1-flash`.
     - Applied the change immediately to `/home/openclaw/.openclaw/openclaw.json` on `openclaw-0`.
  2. **Promoted Cloudflare (#2) and Onboarded Fireworks (#4)**:
     - Re-ranked provider order to:
       `order: ["deepinfra", "cloudflare", "inference-net", "fireworks", "parasail"]`
     - Promoted Cloudflare to #2 for its 97% cache discount and 943k token ceiling.
     - Added Fireworks as #4 for enterprise tier-1 stability (100% uptime, 943k completion ceiling).
  3. **Un-wedged Regensburg Session**:
     - Reset `agent:regensburg:telegram:group:-1004326921510:topic:116` in SQLite from `failed` to `done` and updated `entry_valid = 1`.
 - **How to Avoid Recurrence**:
  - For all reasoning-enabled models (DeepSeek V4.1, Gemini 3, etc.), always explicitly configure `maxTokens: 65536` so chain-of-thought tokens never starve downstream tool call payloads.
@@ -0,0 +1,633 @@
 apiVersion: v1
 data:
  compact_sessions.py: "#!/usr/bin/env python3\n\"\"\"\nNightly multi-agent session
    maintenance and compaction script for OpenClaw.\n1. Pre-warms OS page cache for
    SQLite databases on spinning disks.\n2. Recovers any wedged or locked sessions
    via recover_sessions.py.\n3. Prunes abandoned isolated cron sessions (>48h old)
    to prevent token/state bloat.\n4. Tier A Hard-Reset: Resets koch, hebamme, and
    shopping topics to 0 tokens (clean archive).\n5. Tier B Smart-Compaction: Compacts
    active sessions exceeding token thresholds (5s pacing).\n6. Checkpoints SQLite
    WAL journals across all agent databases to disk.\n7. Optimizes SQLite query planner
    without blocking full VACUUM.\n\"\"\"\nimport glob\nimport json\nimport os\nimport
    sqlite3\nimport subprocess\nimport sys\nimport time\n\nTHRESHOLD_TOKENS = 15000\nTHRESHOLD_TRANSCRIPT_BYTES
    = 200000\nTHRESHOLD_EVENT_COUNT = 30\nCRON_MAX_AGE_HOURS = 48\nRPC_TIMEOUT_MS
    = 180000\n\n# Tracking Channels: Deterministic sliding-window (mila_tracker, nutrition_tracker).\n#
    Strict sliding window of ~5-8 events (2-3 turns max), 0 LLM tokens, instant truncation.\nTRACKING_TARGETS
    = [\n    (\"mila_tracker\", \"agent:mila_tracker:telegram:group:-1004326921510:topic:2796\"),\n
    \   (\"nutrition_tracker\", \"agent:nutrition_tracker:telegram:group:-1004326921510:topic:2797\"),\n]\nMAX_TRACKING_EVENTS
    = 8\nMAX_TRACKING_LINES = 8\n\n# Tier A: High-frequency interaction topics (koch,
    hebamme, shopping).\n# Deep-compaction keeps a compact summary + latest 2 turns
    without completely wiping conversational memory.\nTIER_A_TARGETS = [\n    (\"koch\",
    \"agent:koch:telegram:group:-1004326921510:topic:21\"),\n    (\"hebamme\", \"agent:hebamme:telegram:group:-1004326921510:topic:22\"),\n
    \   (\"shopping\", \"agent:shopping:telegram:group:-1004326921510:topic:115\"),\n]\n\ndef
    prewarm_page_cache():\n    print(\"=== Pre-warming SQLite databases and Knowledge
    Wiki into OS page cache ===\")\n    t0 = time.time()\n    try:\n        subprocess.run(\n
    \           \"cat /home/node/.openclaw/state/openclaw.sqlite /home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite
    > /dev/null 2>&1 || true; \"\n            \"find /home/node/.openclaw/wiki/main
    /home/node/.openclaw/workspace* -maxdepth 3 -name '*.md' -exec cat {} + > /dev/null
    2>&1 || true\",\n            shell=True,\n            timeout=90.0\n        )\n
    \       print(f\"Page cache pre-warmed in {time.time() - t0:.2f}s\")\n    except
    Exception as e:\n        print(f\"Page cache pre-warming warning: {e}\")\n\ndef
    prune_stale_cron_sessions():\n    print(f\"=== Pruning isolated cron sessions
    older than {CRON_MAX_AGE_HOURS}h ===\")\n    cutoff_ms = int(time.time() * 1000)
    - (CRON_MAX_AGE_HOURS * 3600 * 1000)\n    total_pruned = 0\n    total_tokens_reclaimed
    = 0\n\n    for db in sorted(glob.glob(\"/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite\")):\n
    \       agent = db.split(\"/\")[5]\n        try:\n            conn = sqlite3.connect(db,
    timeout=30.0)\n            conn.execute(\"PRAGMA foreign_keys = ON;\")\n            cursor
    = conn.cursor()\n            cursor.execute(\"SELECT name FROM sqlite_master WHERE
    type=\\\"table\\\"\")\n            all_tables = set(r[0] for r in cursor.fetchall())\n\n
    \           cursor.execute(\"SELECT session_key, current_session_id, updated_at,
    entry_json FROM session_nodes WHERE session_key LIKE \\\"%:cron:%\\\"\")\n            stale
    = []\n            for k, sid, up, ej in cursor.fetchall():\n                if
    up and up < cutoff_ms:\n                    tok = 0\n                    if ej:\n
    \                       try:\n                            tok = json.loads(ej).get(\"totalTokens\",
    0) or 0\n                        except Exception:\n                            pass\n
    \                   stale.append((k, sid, tok))\n\n            if stale:\n                tokens_reclaimed
    = sum(t[2] for t in stale)\n                for k, sid, _ in stale:\n                    for
    t in [\"trajectory_runtime_events\", \"transcript_events\", \"transcript_event_identities\",
    \"session_transcript_active_events\", \"transcript_rewrite_watermarks\", \"session_transcript_index_state\",
    \"session_transcript_fts\", \"session_conversations\"]:\n                        if
    t in all_tables and sid:\n                            cursor.execute(f\"DELETE
    FROM {t} WHERE session_id = ?\", (sid,))\n                    for t in [\"session_participants\",
    \"heartbeat_outcomes\", \"session_progress_cards\", \"board_widgets\", \"board_tabs\"]:\n
    \                       if t in all_tables:\n                            cursor.execute(f\"DELETE
    FROM {t} WHERE session_key = ?\", (k,))\n                    if \"memory_entry_origins\"
    in all_tables:\n                        cursor.execute(\"DELETE FROM memory_entry_origins
    WHERE session_key = ? OR session_id = ?\", (k, sid or \"\"))\n                    if
    \"session_windows\" in all_tables:\n                        cursor.execute(\"DELETE
    FROM session_windows WHERE session_key = ? OR session_id = ?\", (k, sid or \"\"))\n
    \                   cursor.execute(\"DELETE FROM session_nodes WHERE session_key
    = ?\", (k,))\n                conn.commit()\n                total_pruned += len(stale)\n
    \               total_tokens_reclaimed += tokens_reclaimed\n                print(f\"
    \ [{agent}] Pruned {len(stale)} dead cron sessions ({tokens_reclaimed} tokens
    reclaimed)\")\n\n            # Unconditionally resolve any dangling foreign key
    references across all tables\n            while True:\n                cursor.execute(\"PRAGMA
    foreign_key_check;\")\n                violations = cursor.fetchall()\n                if
    not violations:\n                    break\n                for table, rowid,
    parent, fkid in violations:\n                    cursor.execute(f\"DELETE FROM
    {table} WHERE rowid = ?\", (rowid,))\n            conn.commit()\n            conn.close()\n
    \       except Exception as e:\n            print(f\"  [{agent}] Pruning error:
    {e}\")\n\n    # Clear resolved quarantine entries if all databases are healthy\n
    \   try:\n        q_path = \"/home/node/.openclaw/state/openclaw-quarantine.sqlite\"\n
    \       if os.path.exists(q_path):\n            q_conn = sqlite3.connect(q_path)\n
    \           q_cur = q_conn.cursor()\n            q_cur.execute(\"DELETE FROM quarantined_databases\")\n
    \           q_conn.commit()\n            q_conn.close()\n    except Exception
    as e:\n        print(f\"Quarantine cleanup error: {e}\")\n\n    print(f\"Cron
    pruning complete: {total_pruned} sessions pruned, {total_tokens_reclaimed} tokens
    reclaimed.\")\n\ndef compact_tracking_sessions():\n    print(\"=== Tracking Channels
    Sliding-Window Maintenance (mila_tracker, nutrition_tracker) ===\")\n    for agent,
    key in TRACKING_TARGETS:\n        db_path = f\"/home/node/.openclaw/agents/{agent}/agent/openclaw-agent.sqlite\"\n
    \       if not os.path.exists(db_path):\n            continue\n        try:\n
    \           con = sqlite3.connect(db_path, timeout=5.0)\n            row = con.execute(\"SELECT
    current_session_id FROM session_nodes WHERE session_key=?\", (key,)).fetchone()\n
    \           if not row or not row[0]:\n                con.close()\n                print(f\"
    \ [{agent}] No active session node found for {key}.\")\n                continue\n
    \           sid = row[0]\n            cnt = con.execute(\"SELECT count(*) FROM
    transcript_events WHERE session_id=?\", (sid,)).fetchone()[0]\n            con.close()\n\n
    \           if cnt > MAX_TRACKING_EVENTS:\n                print(f\"  [{agent}]
    Session {key} has {cnt} events (> {MAX_TRACKING_EVENTS}). Truncating to last {MAX_TRACKING_LINES}
    lines...\")\n                cmd = [\n                    \"openclaw\", \"sessions\",
    \"compact\", key,\n                    \"--agent\", agent,\n                    \"--max-lines\",
    str(MAX_TRACKING_LINES),\n                    \"--timeout\", \"30000\"\n                ]\n
    \               r = subprocess.run(cmd, capture_output=True, text=True)\n                if
    r.returncode == 0:\n                    print(f\"    ✓ Truncated successfully:
    {r.stdout.strip()}\")\n                else:\n                    print(f\"    ✗
    Truncation failed: {r.stderr.strip()}\")\n            else:\n                print(f\"
    \ [{agent}] Session {key} has {cnt} events (<= {MAX_TRACKING_EVENTS}). Clean.\")\n
    \       except Exception as e:\n            print(f\"  ✗ [{agent}] Error during
    tracking compaction: {e}\")\n\ndef compact_tier_a_sessions():\n    print(\"===
    Tier A: Deep-Compaction (koch, hebamme, shopping) ===\")\n    for agent, key in
    TIER_A_TARGETS:\n        db_path = f\"/home/node/.openclaw/agents/{agent}/agent/openclaw-agent.sqlite\"\n
    \       if not os.path.exists(db_path):\n            continue\n        try:\n
    \           con = sqlite3.connect(db_path, timeout=10.0)\n            row = con.execute(\"SELECT
    current_session_id FROM session_nodes WHERE session_key=?\", (key,)).fetchone()\n
    \           con.close()\n            if not row or not row[0]:\n                print(f\"
    \ [Tier A] {agent} ({key}) already at 0 (no active session).\")\n                continue\n
    \           ev_cnt, ev_bytes = get_session_metrics(agent, key, row[0])\n            if
    ev_cnt <= 2 and ev_bytes < 20000:\n                print(f\"  [Tier A] {agent}
    ({key}) has only {ev_cnt} events ({ev_bytes} bytes), skipping.\")\n                continue\n
    \           print(f\"  [Tier A] Deep-compacting {agent} ({key}) [{ev_cnt} events,
    {ev_bytes//1024}KB]...\")\n            r = subprocess.run(\n                [\"openclaw\",
    \"sessions\", \"compact\", key, \"--agent\", agent, \"--timeout\", str(RPC_TIMEOUT_MS)],\n
    \               capture_output=True, text=True\n            )\n            if
    r.returncode == 0:\n                print(f\"    ✓ Deep-compacted: {r.stdout.strip()}\")\n
    \           elif \"Already compacted\" in r.stderr or \"Already compacted\" in
    r.stdout:\n                print(f\"    ✓ Already compacted.\")\n            else:\n
    \               print(f\"    ✗ Standard compact error: {r.stderr.strip()}; retrying
    with --max-lines 40...\")\n                fb = subprocess.run(\n                    [\"openclaw\",
    \"sessions\", \"compact\", key, \"--agent\", agent, \"--max-lines\", \"40\", \"--timeout\",
    str(RPC_TIMEOUT_MS)],\n                    capture_output=True, text=True\n                )\n
    \               if fb.returncode == 0:\n                    print(f\"    ✓ Truncation
    fallback success: {fb.stdout.strip()}\")\n                else:\n                    print(f\"
    \   ✗ Truncation fallback failed: {fb.stderr.strip()}\")\n        except Exception
    as e:\n            print(f\"    ✗ Exception deep-compacting {agent}: {e}\")\n
    \       time.sleep(2)\n\ndef get_session_metrics(agent, key, sid=None):\n    db_path
    = f\"/home/node/.openclaw/agents/{agent}/agent/openclaw-agent.sqlite\"\n    if
    not os.path.exists(db_path):\n        return 0, 0\n    try:\n        con = sqlite3.connect(db_path,
    timeout=5.0)\n        cur = con.cursor()\n        if not sid:\n            row
    = cur.execute(\"SELECT current_session_id FROM session_nodes WHERE session_key=?\",
    (key,)).fetchone()\n            sid = row[0] if row else None\n        if not
    sid:\n            con.close()\n            return 0, 0\n        ev_cnt, ev_bytes
    = cur.execute(\n            \"SELECT count(*), coalesce(sum(length(event_json)),
    0) FROM transcript_events WHERE session_id=?\", \n            (sid,)\n        ).fetchone()\n
    \       con.close()\n        return ev_cnt, ev_bytes\n    except Exception:\n
    \       return 0, 0\n\ndef compact_active_sessions():\n    excluded_keys = set(t[1]
    for t in TIER_A_TARGETS) | set(t[1] for t in TRACKING_TARGETS)\n    print(f\"===
    Tier B: Running Multi-Agent Compaction (threshold: {THRESHOLD_TOKENS} tokens /
    {THRESHOLD_TRANSCRIPT_BYTES//1024}KB, LLM summarization) ===\")\n    res = subprocess.run([\"openclaw\",
    \"sessions\", \"--all-agents\", \"--json\"], capture_output=True, text=True)\n
    \   if res.returncode != 0:\n        print(f\"Failed to list sessions: {res.stderr}\")\n
    \       return\n\n    sessions = json.loads(res.stdout).get(\"sessions\", [])\n
    \   compacted = 0\n    skipped = 0\n\n    for s in sessions:\n        key = s.get(\"key\",
    \"\")\n        agent = s.get(\"agentId\") or \"main\"\n        tokens = s.get(\"totalTokens\")
    or 0\n        sid = s.get(\"sessionId\")\n\n        # Skip Tier A and Tracking
    agents as they have dedicated routines\n        if key in excluded_keys:\n            continue\n\n
    \       # Target main sessions and all telegram sessions (topics and direct)\n
    \       is_target = (\n            key == \"agent:main:main\" or \n            \":telegram:\"
    in key or\n            (key.startswith(\"agent:\") and key.endswith(\":main\"))\n
    \       )\n        if is_target and not key.endswith(\":heartbeat\"):\n            ev_cnt,
    ev_bytes = get_session_metrics(agent, key, sid)\n            needs_compaction
    = (\n                tokens >= THRESHOLD_TOKENS or\n                ev_bytes >=
    THRESHOLD_TRANSCRIPT_BYTES or\n                (tokens == 0 and ev_cnt >= THRESHOLD_EVENT_COUNT)\n
    \           )\n            if needs_compaction:\n                stat_str = f\"{tokens}
    tokens\" if tokens else f\"{ev_bytes//1024}KB / {ev_cnt} events\"\n                print(f\"Compacting
    {agent} ({stat_str}) -> {key}...\")\n                c_res = subprocess.run(\n
    \                   [\"openclaw\", \"sessions\", \"compact\", key, \"--agent\",
    agent, \"--timeout\", str(RPC_TIMEOUT_MS)],\n                    capture_output=True,
    text=True\n                )\n                if c_res.returncode == 0:\n                    print(f\"
    \ ✓ {c_res.stdout.strip()}\")\n                    compacted += 1\n                elif
    \"Already compacted\" in c_res.stderr or \"Already compacted\" in c_res.stdout:\n
    \                   print(f\"  ✓ Already compacted.\")\n                    skipped
    += 1\n                else:\n                    print(f\"  ✗ {c_res.stderr.strip()};
    retrying with --max-lines 80 fallback...\")\n                    fb_res = subprocess.run(\n
    \                       [\"openclaw\", \"sessions\", \"compact\", key, \"--agent\",
    agent, \"--max-lines\", \"80\", \"--timeout\", str(RPC_TIMEOUT_MS)],\n                        capture_output=True,
    text=True\n                    )\n                    if fb_res.returncode ==
    0:\n                        print(f\"  ✓ (fallback) {fb_res.stdout.strip()}\")\n
    \                       compacted += 1\n                    else:\n                        print(f\"
    \ ✗ Fallback failed: {fb_res.stderr.strip()}\")\n                time.sleep(5)
    \ # 5s pause to avoid rotational HDD I/O saturation\n            else:\n                skipped
    += 1\n\n    print(f\"Compaction complete: {compacted} compacted, {skipped} skipped.\")\n\ndef
    checkpoint_wal_journals():\n    print(\"=== Checkpointing SQLite WAL journals
    across all agent databases ===\")\n    dbs = [\"/home/node/.openclaw/state/openclaw.sqlite\"]
    + glob.glob(\"/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite\")\n    wal_freed
    = 0\n    for db in dbs:\n        wal = db + \"-wal\"\n        if os.path.exists(wal):\n
    \           sz = os.path.getsize(wal)\n            try:\n                con =
    sqlite3.connect(db, timeout=30.0)\n                con.execute(\"PRAGMA wal_checkpoint(TRUNCATE);\")\n
    \               con.close()\n                wal_freed += sz\n            except
    Exception as e:\n                print(f\"  ✗ Error checkpointing {db}: {e}\")\n
    \   print(f\"WAL Checkpoint complete: {wal_freed / (1024*1024):.2f} MB merged
    to disk.\")\n\ndef vacuum_and_optimize():\n    print(\"=== Running SQLite OPTIMIZE
    across all databases ===\")\n    dbs = [\"/home/node/.openclaw/state/openclaw.sqlite\"]
    + glob.glob(\"/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite\")\n    for
    db in dbs:\n        try:\n            con = sqlite3.connect(db, timeout=30.0)\n
    \           con.execute(\"PRAGMA optimize;\")\n            con.close()\n        except
    Exception as e:\n            print(f\"  ✗ Error optimizing {db}: {e}\")\n    print(\"SQLite
    optimization complete.\")\n\ndef main():\n    prewarm_page_cache()\n    try:\n
    \       subprocess.run([\"python3\", \"/home/node/.openclaw/scripts/recover_sessions.py\"],
    check=False)\n    except Exception:\n        pass\n    prune_stale_cron_sessions()\n
    \   compact_tracking_sessions()\n    compact_tier_a_sessions()\n    compact_active_sessions()\n
    \   checkpoint_wal_journals()\n    vacuum_and_optimize()\n    prewarm_page_cache()\n\nif
    __name__ == \"__main__\":\n    main()\n"
  dedup_subagent_vectors.py: |
    #!/usr/bin/env python3
    import glob, json, os, sqlite3, sys
    cfg_path = "/home/node/.openclaw/openclaw.json"
    if os.path.exists(cfg_path):
        try:
            with open(cfg_path, "r") as f:
                cfg = json.load(f)
            mem_search = cfg.get("memory", {}).get("search", {})
            if mem_search.get("extraPaths"):
                mem_search["extraPaths"] = []
                with open(cfg_path, "w") as f:
                    json.dump(cfg, f, indent=2)
                print("[dedup_subagents] Cleared top-level memory.search.extraPaths from openclaw.json (scoped to main only)")
        except Exception as e:
            print(f"[dedup_subagents] Warning checking openclaw.json: {e}", file=sys.stderr)
    vec_path = "/app/node_modules/sqlite-vec-linux-x64/vec0.so"
    for db in sorted(glob.glob("/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite")):
        agent = os.path.basename(os.path.dirname(os.path.dirname(db)))
        if agent == "main":
            continue
        try:
            conn = sqlite3.connect(db, timeout=10.0)
            if os.path.exists(vec_path):
                conn.enable_load_extension(True)
                conn.load_extension(vec_path)
            cur = conn.cursor()
            chk = cur.execute("SELECT count(*) FROM memory_index_chunks").fetchone()[0]
            if chk > 0:
                print(f"[dedup_subagents] Purging {chk} duplicated vector chunks from agent {agent}...")
                for t in [
                    "memory_index_sources",
                    "memory_index_chunks",
                    "memory_index_chunk_recall_metadata",
                    "memory_index_chunk_provenance",
                    "memory_entry_origins",
                    "memory_embedding_cache",
                    "memory_index_chunks_vec"
                ]:
                    try: cur.execute(f"DELETE FROM {t}")
                    except Exception: pass
                conn.commit()
                cur.execute("VACUUM")
                print(f"[dedup_subagents] Reclaimed disk space for agent {agent}")
            conn.close()
        except Exception as e:
            print(f"[dedup_subagents] Notice for {agent}: {e}", file=sys.stderr)
  gateway-preflight.mjs: |
    import fs from "node:fs";
    import path from "node:path";
    import { execSync, spawn } from "node:child_process";
    if (!process.env.__OPENCLAW_PREFLIGHT_DONE) {
      process.env.__OPENCLAW_PREFLIGHT_DONE = "1";
      const isGateway = process.argv.some(arg => arg.endsWith("openclaw.mjs") || arg.endsWith("openclaw")) && process.argv.includes("gateway");
      if (isGateway) {
        const t0 = Date.now();
        console.log("[gateway-preflight] Initializing container self-healing preflight...");
        // 1. Clean up stale gateway lock files from ungraceful kills
        for (const dir of ["/tmp/openclaw-1000", "/tmp"]) {
          if (fs.existsSync(dir)) {
            try {
              const files = fs.readdirSync(dir);
              for (const file of files) {
                if (file.startsWith("gateway") && file.endsWith(".lock")) {
                  const fullPath = path.join(dir, file);
                  fs.unlinkSync(fullPath);
                  console.log(`[gateway-preflight] Removed stale lock: ${fullPath}`);
                }
              }
            } catch (e) {
              console.warn(`[gateway-preflight] Lock cleanup warning in ${dir}:`, e.message);
            }
          }
        }
        // 2. Clear false database quarantines
        const qPath = "/home/node/.openclaw/state/openclaw-quarantine.sqlite";
        if (fs.existsSync(qPath)) {
          try {
            execSync(`/home/node/.openclaw/.local/bin/python3 -c "import sqlite3; c=sqlite3.connect(\x27${qPath}\x27); c.execute(\x27DELETE FROM quarantined_databases\x27); c.commit(); c.close()"`, { stdio: "ignore" });
            console.log("[gateway-preflight] Cleared database quarantine.");
          } catch (_) {}
        }
        // 3. Deduplicate subagent vector databases (keeps non-main agent DBs < 15MB)
        try {
          execSync("/home/node/.openclaw/.local/bin/python3 /home/node/.openclaw/scripts/dedup_subagent_vectors.py", { stdio: "inherit" });
        } catch (e) {
          console.warn("[gateway-preflight] Vector deduplication warning:", e.message);
        }
        // 4. Pre-warm page cache sequentially (transforms random 70 IOPS disk reads into sequential streaming)
        try {
          const pw0 = Date.now();
          execSync("cat /home/node/.openclaw/state/openclaw.sqlite /home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite > /dev/null 2>&1 || true; find /home/node/.openclaw/wiki/main /home/node/.openclaw/workspace* -maxdepth 3 -name '*.md' -exec cat {} + > /dev/null 2>&1 || true");
          console.log(`[gateway-preflight] Pre-warmed SQLite databases and Wiki markdown in ${Date.now() - pw0}ms`);
        } catch (_) {}
        // 5. Recover any wedged running sessions left over from ungraceful container restart
        try {
          execSync("/home/node/.openclaw/.local/bin/python3 /home/node/.openclaw/scripts/recover_sessions.py", { stdio: "inherit" });
        } catch (e) {
          console.warn("[gateway-preflight] Session recovery warning:", e.message);
        }
        // 6. Spawn background turn replay daemon if interrupted turns were detected
        try {
          if (fs.existsSync("/tmp/openclaw-interrupted-turns.json")) {
            console.log("[gateway-preflight] Spawning background turn replay daemon...");
            const child = spawn("/home/node/.openclaw/.local/bin/python3", ["/home/node/.openclaw/scripts/replay_interrupted_turns.py"], {
              detached: true,
              stdio: "ignore"
            });
            child.unref();
          }
        } catch (e) {
          console.warn("[gateway-preflight] Could not spawn turn replay daemon:", e.message);
        }
        console.log(`[gateway-preflight] Self-healing completed in ${Date.now() - t0}ms.`);
      }
    }
  openclaw-triage.py: "#!/usr/bin/env python3\n\"\"\"\nopenclaw-triage.py: Rapid zero-dependency
    incident triage for OpenClaw multi-agent sessions.\nDirectly inspects ground-truth
    SQLite session state and transcript events in < 1 second.\n\"\"\"\nimport argparse\nimport
    glob\nimport json\nimport os\nimport sqlite3\nimport sys\nimport time\n\nTOPIC_TO_AGENT
    = {\n    \"20\": \"fitness\",\n    \"21\": \"koch\",\n    \"22\": \"hebamme\",\n
    \   \"51\": \"travel\",\n    \"115\": \"shopping\",\n    \"116\": \"regensburg\",\n
    \   \"117\": \"recherche\",\n    \"118\": \"doktor\",\n    \"119\": \"itguy\",\n
    \   \"164\": \"grabengasse_media\",\n    \"2796\": \"mila_tracker\",\n    \"2797\":
    \"nutrition_tracker\",\n}\n\ndef parse_args():\n    parser = argparse.ArgumentParser(description=\"Rapid
    OpenClaw multi-agent session triage.\")\n    parser.add_argument(\"--topic\",
    \"-t\", help=\"Telegram forum topic ID (e.g. 21, 22, 117)\")\n    parser.add_argument(\"--agent\",
    \"-a\", help=\"Agent identifier (e.g. koch, hebamme, recherche)\")\n    parser.add_argument(\"--limit\",
    \"-n\", type=int, default=10, help=\"Number of recent events to display (default:
    10)\")\n    parser.add_argument(\"--db-root\", default=\"/home/node/.openclaw/agents\",
    help=\"Root path of agent SQLite databases\")\n    return parser.parse_args()\n\ndef
    triage_agent_session(agent, topic_id=None, limit=10, db_root=\"/home/node/.openclaw/agents\"):\n
    \   db_path = os.path.join(db_root, agent, \"agent\", \"openclaw-agent.sqlite\")\n
    \   if not os.path.exists(db_path):\n        print(f\"[-] Database not found for
    agent '{agent}': {db_path}\")\n        return False\n\n    try:\n        con =
    sqlite3.connect(db_path, timeout=5.0)\n    except Exception as e:\n        print(f\"[-]
    Failed to connect to SQLite DB for agent '{agent}': {e}\")\n        return False\n\n
    \   cur = con.cursor()\n    # Find matching session\n    if topic_id:\n        target_pattern
    = f\"%topic:{topic_id}%\"\n        cur.execute(\n            \"SELECT session_key,
    current_session_id, status, updated_at, entry_json FROM session_nodes WHERE session_key
    LIKE ? AND session_key NOT LIKE '%:heartbeat' ORDER BY updated_at DESC LIMIT 1\",\n
    \           (target_pattern,)\n        )\n    else:\n        cur.execute(\n            \"SELECT
    session_key, current_session_id, status, updated_at, entry_json FROM session_nodes
    WHERE session_key NOT LIKE '%:heartbeat' ORDER BY updated_at DESC LIMIT 1\"\n
    \       )\n\n    row = cur.fetchone()\n    if not row:\n        print(f\"[-] No
    session found in {agent} DB (filter: topic={topic_id})\")\n        con.close()\n
    \       return False\n\n    skey, sid, status, updated_at_ms, entry_json = row\n
    \   now_ms = time.time() * 1000\n    age_min = (now_ms - updated_at_ms) / 60000.0
    if updated_at_ms else 0.0\n\n    entry = {}\n    if entry_json:\n        try:\n
    \           entry = json.loads(entry_json)\n        except Exception:\n            pass\n\n
    \   tokens = entry.get(\"totalTokens\", \"?\")\n    model = entry.get(\"model\",
    \"default\")\n    last_run_id = entry.get(\"activeWriterRunId\") or entry.get(\"activeRunId\",
    None)\n\n    # Detect anomalies\n    badges = []\n    if isinstance(tokens, int):\n
    \       if tokens > 60000:\n            badges.append(\"\U0001F6A8 [CRITICAL_CONTEXT_BLOAT:
    >60k tokens]\")\n        elif tokens > 20000:\n            badges.append(\"⚠️
    [HIGH_CONTEXT_TOKENS: >20k tokens]\")\n    if status == \"running\" and age_min
    > 5.0:\n        badges.append(\"\U0001F512 [POSSIBLY_WEDGED_RUNNING: updated >5m
    ago]\")\n    elif status == \"processing\":\n        badges.append(\"⚡ [ACTIVE_PROCESSING]\")\n\n
    \   # Check ingress queue status\n    state_db = \"/home/node/.openclaw/state/openclaw.sqlite\"\n
    \   if topic_id and os.path.exists(state_db):\n        try:\n            s_con
    = sqlite3.connect(state_db, timeout=2.0)\n            lane_pat = f\"%topic:{topic_id}%\"\n
    \           pending_cnt = s_con.execute(\n                \"SELECT count(*) FROM
    channel_ingress_events WHERE lane_key LIKE ? AND status IN ('pending', 'claimed')\",\n
    \               (lane_pat,)\n            ).fetchone()[0]\n            s_con.close()\n
    \           if pending_cnt > 0:\n                badges.append(f\"\U0001F4EC [INGRESS_STALLED:
    {pending_cnt} message(s) pending]\")\n        except Exception:\n            pass\n\n
    \   print(\"=\" * 72)\n    print(f\"\U0001F3AF AGENT: {agent.upper():<12} | TOPIC:
    {topic_id or 'N/A':<6} | STATUS: {status.upper()}\")\n    print(f\"   SESSION
    KEY: {skey}\")\n    print(f\"   SESSION ID:  {sid}\")\n    print(f\"   MODEL:
    \      {model}\")\n    print(f\"   TOKENS:      {tokens} | LAST UPDATED: {age_min:.1f}m
    ago\")\n    if badges:\n        print(f\"   ANOMALIES:   {' '.join(badges)}\")\n
    \   print(\"=\" * 72)\n\n    # Query transcript events\n    cur.execute(\n        \"SELECT
    seq, created_at, event_json FROM transcript_events WHERE session_id = ? ORDER
    BY seq DESC LIMIT ?\",\n        (sid, limit)\n    )\n    events = cur.fetchall()\n
    \   con.close()\n\n    if not events:\n        print(\"   (No transcript events
    found)\")\n        return True\n\n    events.reverse()\n    print(\"\\n\U0001F4DC
    RECENT TRANSCRIPT EVENTS (Chronological):\")\n\n    last_role = None\n    for
    seq, ca_ms, ej_str in events:\n        try:\n            ev = json.loads(ej_str)\n
    \       except Exception:\n            print(f\"[{seq}] <unparseable event json>\")\n
    \           continue\n\n        etype = ev.get(\"type\")\n        if etype !=
    \"message\":\n            continue\n\n        msg = ev.get(\"message\", {})\n
    \       role = msg.get(\"role\")\n        last_role = role\n        content =
    msg.get(\"content\", [])\n\n        if role == \"user\":\n            txt = content
    if isinstance(content, str) else json.dumps(content)\n            # Check for
    audio transcript\n            if isinstance(content, str) and \"[Audio]\" in content:\n
    \               print(f\"\\n\U0001F449 [SEQ {seq}] \U0001F3A4 USER AUDIO PROMPT:\")\n
    \               for line in content.splitlines()[:6]:\n                    print(f\"
    \  {line}\")\n                if len(content.splitlines()) > 6:\n                    print(\"
    \  ...\")\n            else:\n                txt_preview = txt.replace(\"\\n\",
    \" \")[:240]\n                print(f\"\\n\U0001F449 [SEQ {seq}] \U0001F464 USER:
    {txt_preview}\")\n\n        elif role == \"assistant\":\n            print(f\"\\n\U0001F916
    [SEQ {seq}] ASSISTANT TURN:\")\n            if isinstance(content, list):\n                for
    item in content:\n                    if not isinstance(item, dict):\n                        continue\n
    \                   itype = item.get(\"type\")\n                    if itype ==
    \"thinking\":\n                        th = item.get(\"thinking\", \"\").replace(\"\\n\",
    \" \")\n                        print(f\"   \U0001F9E0 THINKING: {th[:280]}...\")\n
    \                   elif itype == \"toolCall\":\n                        tname
    = item.get(\"name\", \"unknown\")\n                        targs = json.dumps(item.get(\"arguments\",
    {}))\n                        print(f\"   ⚙️ TOOL CALL: {tname}({targs[:160]})\")\n
    \                   elif itype == \"text\":\n                        tx = item.get(\"text\",
    \"\")\n                        lines = tx.splitlines()\n                        prev
    = lines[0][:150] if lines else \"\"\n                        print(f\"   \U0001F4AC
    TEXT OUTPUT: {prev}...\")\n            elif isinstance(content, str):\n                print(f\"
    \  \U0001F4AC TEXT OUTPUT: {content[:200]}...\")\n\n        elif role == \"toolResult\":\n
    \           is_err = ev.get(\"isError\", False)\n            tname = ev.get(\"details\",
    {}).get(\"tool\") or msg.get(\"toolName\", \"tool\")\n            res_txt = json.dumps(content)
    if not isinstance(content, str) else content\n            if is_err or \"error\"
    in res_txt.lower() or \"must have required property\" in res_txt:\n                print(f\"
    \  ❌ [SEQ {seq}] TOOL ERROR ({tname}): {res_txt[:260]}\")\n            else:\n
    \               print(f\"   ✅ [SEQ {seq}] TOOL RESULT ({tname}): {res_txt[:180]}\")\n\n
    \   if last_role == \"user\":\n        print(\"\\n⚠️ WARNING: The last event in
    the transcript is an UNANSWERED USER MESSAGE!\")\n        print(\"   The agent
    turn either crashed, timed out, or was killed before producing a response.\")\n\n
    \   print(\"\\n\" + \"=\" * 72)\n    return True\n\ndef main():\n    args = parse_args()\n
    \   if not args.topic and not args.agent:\n        print(\"Usage: openclaw-triage.py
    (--topic <ID> | --agent <NAME>) [--limit <N>]\")\n        sys.exit(1)\n\n    agent
    = args.agent\n    topic = args.topic\n\n    if topic and not agent:\n        agent
    = TOPIC_TO_AGENT.get(str(topic))\n        if not agent:\n            # Search
    all DBs\n            for a, t in TOPIC_TO_AGENT.items():\n                if t
    == topic:\n                    agent = a\n                    break\n\n    if
    not agent:\n        # Scan all DBs for the topic\n        for db in sorted(glob.glob(os.path.join(args.db_root,
    \"*/agent/openclaw-agent.sqlite\"))):\n            cand_agent = db.split(os.sep)[-3]\n
    \           try:\n                con = sqlite3.connect(db, timeout=2.0)\n                cur
    = con.cursor()\n                cur.execute(\n                    \"SELECT session_key
    FROM session_nodes WHERE session_key LIKE ? LIMIT 1\",\n                    (f\"%topic:{topic}%\",)\n
    \               )\n                if cur.fetchone():\n                    agent
    = cand_agent\n                    con.close()\n                    break\n                con.close()\n
    \           except Exception:\n                pass\n\n    if not agent:\n        print(f\"[-]
    Could not map topic '{topic}' to any known OpenClaw agent.\")\n        sys.exit(1)\n\n
    \   success = triage_agent_session(agent, topic_id=topic, limit=args.limit, db_root=args.db_root)\n
    \   sys.exit(0 if success else 1)\n\nif __name__ == \"__main__\":\n    main()\n"
  recover_sessions.py: |+
    #!/usr/bin/env python3
    import glob, sqlite3, json, os, sys, time
    t0 = time.time()
    recovered = 0
    interrupted_turns = []
    def extract_prompt(msg):
        if not msg: return ""
        content = msg.get("content")
        if isinstance(content, str): return content
        if isinstance(content, list):
            parts = []
            for c in content:
                if isinstance(c, dict): parts.append(c.get("text") or c.get("content") or "")
                elif isinstance(c, str): parts.append(c)
            return "\n".join(filter(None, parts))
        return str(content or "")
    for db in sorted(glob.glob("/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite")):
        try:
            conn = sqlite3.connect(db, timeout=10.0)
            cursor = conn.cursor()
            while True:
                cursor.execute("PRAGMA foreign_key_check;")
                violations = cursor.fetchall()
                if not violations: break
                for table, rowid, parent, fkid in violations:
                    cursor.execute(f"DELETE FROM {table} WHERE rowid = ?", (rowid,))
            cursor.execute("SELECT session_key, entry_json, current_session_id, status FROM session_nodes WHERE status IN (\"running\", \"failed\", \"error\")")
            rows = cursor.fetchall()
            agent_id = os.path.basename(os.path.dirname(os.path.dirname(db)))
            for sk, ej, csid, st in rows:
                try:
                    p = json.loads(ej) if ej else {}
                    sid = csid or p.get("sessionId")
                    if sid:
                        ev = cursor.execute("SELECT seq, event_json FROM transcript_events WHERE session_id = ? ORDER BY seq DESC LIMIT 1", (sid,)).fetchone()
                        if ev:
                            ev_seq, ev_raw = ev
                            try:
                                ev_data = json.loads(ev_raw)
                                msg = ev_data.get("message") or ev_data
                                if st == "running" and msg.get("role") == "user":
                                    prompt_text = extract_prompt(msg)
                                    ctx = p.get("restartRecoveryDeliveryContext") or p.get("delivery", {}).get("context") or p.get("delivery", {}).get("route", {}).get("context") or {}
                                    interrupted_turns.append({
                                        "agent": agent_id,
                                        "session_key": sk,
                                        "session_id": sid,
                                        "context": ctx,
                                        "prompt": prompt_text
                                    })
                                    cursor.execute("PRAGMA foreign_keys = ON")
                                    cursor.execute("DELETE FROM transcript_events WHERE session_id = ? AND seq = ?", (sid, ev_seq))
                                elif msg.get("role") == "assistant" and msg.get("stopReason") == "error":
                                    cursor.execute("PRAGMA foreign_keys = ON")
                                    cursor.execute("DELETE FROM transcript_events WHERE session_id = ? AND seq = ?", (sid, ev_seq))
                            except Exception as ex:
                                print(f"[recover_sessions] Error parsing event: {ex}", file=sys.stderr)
                    p["status"] = "done"
                    p["activeWriterRunId"] = None
                    p["activeClaimRunId"] = None
                    p["restartRecoveryDeliveryRunId"] = None
                    cursor.execute("UPDATE session_nodes SET status = \"done\", entry_json = ? WHERE session_key = ?", (json.dumps(p), sk))
                    cursor.execute("UPDATE session_nodes SET entry_valid = 1 WHERE session_key = ?", (sk,))
                    recovered += 1
                except Exception: pass
            cursor.execute("UPDATE session_nodes SET entry_valid = 1 WHERE entry_valid != 1")
            cursor.execute("UPDATE session_windows SET status = \"done\" WHERE status IN (\"running\", \"failed\", \"error\")")
            conn.commit()
            conn.close()
        except Exception as e:
            print(f"[recover_sessions] Warning for {db}: {e}", file=sys.stderr)
    state_db = "/home/node/.openclaw/state/openclaw.sqlite"
    if os.path.exists(state_db):
        try:
            sconn = sqlite3.connect(state_db, timeout=10.0)
            scur = sconn.cursor()
            scur.execute("UPDATE channel_ingress_events SET attempts = 0, last_attempt_at = NULL, last_error = NULL WHERE status = 'pending' AND attempts > 0")
            sconn.commit()
            sconn.close()
        except Exception as e:
            print(f"[recover_sessions] Warning resetting ingress backoff: {e}", file=sys.stderr)
    if interrupted_turns:
        try:
            with open("/tmp/openclaw-interrupted-turns.json", "w") as f:
                json.dump(interrupted_turns, f, indent=2)
            print(f"[recover_sessions] Detected {len(interrupted_turns)} interrupted user turn(s) saved to /tmp/openclaw-interrupted-turns.json")
        except Exception as e:
            print(f"[recover_sessions] Error writing interrupted turns: {e}", file=sys.stderr)
    print(f"[recover_sessions] Completed in {time.time() - t0:.2f}s ({recovered} wedged sessions recovered)")
  replay_interrupted_turns.py: |
    #!/usr/bin/env python3
    import json, os, subprocess, sys, time, urllib.request
    INTERRUPTED_FILE = "/tmp/openclaw-interrupted-turns.json"
    if not os.path.exists(INTERRUPTED_FILE):
        sys.exit(0)
    try:
        with open(INTERRUPTED_FILE, "r") as f:
            turns = json.load(f)
    except Exception as e:
        print(f"[replay_interrupted_turns] Failed to read {INTERRUPTED_FILE}: {e}", file=sys.stderr)
        sys.exit(0)
    if not turns:
        sys.exit(0)
    print(f"[replay_interrupted_turns] Found {len(turns)} interrupted turn(s). Waiting for gateway /healthz...")
    gateway_ready = False
    for _ in range(60):
        try:
            with urllib.request.urlopen("http://127.0.0.1:18790/healthz", timeout=3) as resp:
                if resp.status == 200:
                    gateway_ready = True
                    break
        except Exception:
            pass
        time.sleep(2)
    if not gateway_ready:
        print("[replay_interrupted_turns] Gateway did not become healthy in 120s. Aborting.", file=sys.stderr)
        sys.exit(1)
    # Allow 5s for Telegram ingress to bind
    time.sleep(5)
    for turn in turns:
        sk = turn.get("session_key")
        sid = turn.get("session_id")
        agent_id = turn.get("agent")
        ctx = turn.get("context") or {}
        prompt = turn.get("prompt") or ""
        channel = ctx.get("channel") or "telegram"
        to_target = ctx.get("to") or ""
        thread_id = ctx.get("threadId")
        target = to_target
        if target.startswith("telegram:"):
            parts = target.split(":")
            target = parts[1] if len(parts) > 1 else target
        print(f"[replay_interrupted_turns] Processing agent '{agent_id}' on session '{sk}' target='{target}' thread='{thread_id}'")
        # 1. Send status notification to Telegram if target exists
        if target:
            notice = "⚠️ OpenClaw wurde während der Bearbeitung neu gestartet – deine Anfrage wird jetzt nachgeholt..."
            notify_cmd = [
                "openclaw", "message", "send",
                "--channel", channel,
                "--target", str(target),
                "-m", notice
            ]
            if thread_id is not None:
                notify_cmd.extend(["--thread-id", str(thread_id)])
            try:
                subprocess.run(notify_cmd, check=False, timeout=30)
                print(f"[replay_interrupted_turns] Sent recovery notice to {target}")
            except Exception as e:
                print(f"[replay_interrupted_turns] Notice failed: {e}", file=sys.stderr)
        # 2. Replay agent turn
        if sk and prompt:
            p_short = (prompt[:60] + "...") if len(prompt) > 60 else prompt
            print(f"[replay_interrupted_turns] Replaying agent turn: {p_short}")
            agent_cmd = [
                "openclaw", "agent",
                "--session-key", sk,
                "-m", prompt,
                "--deliver"
            ]
            try:
                res = subprocess.run(agent_cmd, capture_output=True, text=True, timeout=300)
                if res.returncode == 0:
                    print(f"[replay_interrupted_turns] Turn replay succeeded for {sk}")
                else:
                    print(f"[replay_interrupted_turns] Turn replay exited with code {res.returncode}: {res.stderr[:200]}", file=sys.stderr)
            except Exception as e:
                print(f"[replay_interrupted_turns] Replay execution error: {e}", file=sys.stderr)
    try:
        os.remove(INTERRUPTED_FILE)
        print(f"[replay_interrupted_turns] Cleaned up {INTERRUPTED_FILE}")
    except Exception:
        pass
 kind: ConfigMap
 metadata:
  name: openclaw-scripts
  namespace: openclaw
@@ -0,0 +1,137 @@
 # Declarative Crons-as-Code for OpenClaw (Haumdaucher)
 # Reconciled idempotently via k8s/openclaw/scripts/sync_crons.py
 version: 1
 jobs:
  # 1. Maintenance & State Truncation
  - name: "tracking-session-sliding-window"
    declarationKey: "tracking-session-sliding-window"
    description: "Lightweight sliding-window truncation (max 8 events) for mila_tracker and nutrition_tracker"
    schedule:
      kind: "every"
      every: "15m"
    session: "isolated"
    delivery: "none"
    command: "python3 /home/node/.openclaw/scripts/compact_tracking_sessions.py"
  - name: "nightly-session-compaction"
    declarationKey: "nightly-session-compaction"
    description: "Nightly multi-agent session compaction and SQLite WAL checkpointing"
    schedule:
      kind: "cron"
      expr: "45 4 * * *"
      tz: "Europe/Berlin"
    session: "isolated"
    delivery: "none"
    command: "python3 /home/node/.openclaw/scripts/compact_sessions.py"
  # 2. Nightly Garmin Connect Mirror
  - name: "garmin-nightly-mirror"
    declarationKey: "garmin-nightly-mirror"
    description: "Nächtlicher deterministischer Spiegel der Garmin Connect Daten (Aktivitäten, Daily Summary, Schlaf) in Git JSONL"
    schedule:
      kind: "cron"
      expr: "30 3 * * *"
      tz: "Europe/Berlin"
    agent: "fitness"
    model: "openrouter/deepseek/deepseek-v4.1-flash-1017"
    session: "isolated"
    channel: "telegram"
    to: "-1004326921510"
    threadId: "20"
    announce: true
    message: |
      Führe den nächtlichen Garmin Connect Sync durch.
      Vorgehen:
      1. Führe den Garmin-Sync-Befehl aus:
         uv run /home/node/mop-skills/mop-skills/skills/datastore/scripts/garmin_sync.py --days 2 --data-dir /home/node/.openclaw/wiki/main/data
      2. Finale Antwort:
         - Bei Erfolg: Gib exakt 'NO_REPLY' aus (intentional silence, kein Telegram-Spam in der Nacht).
         - Nur bei Authentifizierungsfehlern: Informiere kurz via Telegram (Thema #Sport), dass ein Garmin-Re-Auth nötig ist, oder starte den Re-Auth-Flow.
  # 4. Weekly Autonomous System & Error Audit
  - name: "itguy-weekly-health-audit"
    declarationKey: "itguy-weekly-health-audit"
    description: "Wöchentlicher Self-Audit der OpenClaw-Logs, Tool-Failures und Session-Transkripte mit Git-Commit-Korrelation"
    schedule:
      kind: "cron"
      expr: "0 3 * * 0"
      tz: "Europe/Berlin"
    agent: "itguy"
    model: "openrouter/deepseek/deepseek-v4.1-flash-1017"
    session: "isolated"
    channel: "telegram"
    to: "-1004326921510"
    threadId: "119"
    announce: true
    message: |
      Führe den wöchentlichen OpenClaw System- und Log-Audit durch.
      Vorgehen:
      1. Führe den Audit-Befehl aus:
         uv run /home/node/mop-skills/mop-skills/skills/openclaw-audit/scripts/audit_openclaw.py --since 7d --write-report --add-task --git-push
      2. Analysiere die Ausgabe und korreliere eventuelle Fehler-Cluster mit den jüngsten Commits in infrapuzzle, mop-skills und knowledge-wiki.
      3. Finale Antwort:
         - Wenn NEUE Probleme gefunden oder Tasks in tasks/antigravity.md eingetragen wurden: Fasse die Ergebnisse kurz, präzise und lösungsorientiert zusammen (betroffene Tools, vermutete Ursache, Link zur Task-Queue) und gib diese Zusammenfassung als finale Antwort aus.
         - Wenn das System gesund ist und KEINE neuen Tasks erzeugt wurden: Gib als finale Antwort exakt 'NO_REPLY' aus (intentional silence, kein Telegram-Spam).
  # 5. Weekly AI Roundup (Recherche)
  - name: "weekly-ai-roundup"
    declarationKey: "weekly-ai-roundup:recherche"
    description: "Wöchentlicher AI-Roundup und Tech-Scanning für Topic #Research"
    schedule:
      kind: "cron"
      expr: "30 6 * * 5"
      tz: "Europe/Berlin"
    agent: "recherche"
    model: "openrouter/deepseek/deepseek-v4.1-flash-1017"
    session: "isolated"
    channel: "telegram"
    to: "-1004326921510"
    threadId: "117"
    announce: true
    message: |
      🗓️ WÖCHENTLICHER AI-ROUNDUP (Freitag). Führe den in sources.md im Workspace definierten Ablauf aus und poste das Ergebnis als EINE kompakte Telegram-Nachricht in diesen Topic (#Research).
      1) Hacker News: Algolia API – https://hn.algolia.com/api/v1/search_by_date?tags=story&numericFilters=points>150,created_at_i>{Unix-Timestamp von vor 7 Tagen}&hitsPerPage=100 → daraus die KI-relevanten Top-Stories nach Punkten ziehen.
      2) Frontier-Labs prüfen: OpenAI, Anthropic, Google DeepMind, Meta AI, Mistral, xAI.
      3) China-Labs prüfen: GLM/Z.ai, Qwen, DeepSeek, Moonshot/Kimi, MiniMax.
      4) Tracker: Artificial Analysis Releases, Hugging Face Trending, OpenRouter Rankings, LMArena.
      5) Newsletter/Blogs: The Batch, Import AI, Interconnects, Ahead of AI, Simon Willison, TLDR AI.
      6) GitHub: Trending (weekly) + neue Releases der Kern-Orgs (openai, anthropics, google-deepmind, QwenLM, deepseek-ai, zai-org, meta-llama, mistralai).
      7) YouTube nur als Hype-Indikator (Titel/Snippets), KEINE Transkripte.
      Ausgabe (Deutsch, Markdown, KEINE Tabellen):
      - Top-3-Highlights der Woche (je 1 Satz + Link)
      - Danach Bullets je Kategorie: ① Frontier-Modelle · ② China-Modelle · ③ Tools/Infra/Procedures · ④ Trends (HN/GitHub/YouTube), je Eintrag genau 1 Quell-Link
      - Scope 60/40 (Modelle/Tools). Wenn eine Kategorie nichts Neues hat: kurz 'nichts Neues'.
      - Am Ende NUR falls nötig eine Zeile: welche Quelle in sources.md ergänzt/entfernt werden sollte.
      Nutze web_search/web_fetch. Effort: medium.
  # 6. Weekly Bridge Tracker (Holzgartensteg)
  - name: "Recherche: Holzgartensteg (wöchentlich)"
    declarationKey: "recherche:holzgartensteg"
    description: "Wöchentlicher Status-Check zum Holzgartensteg Regensburg via ALLRIS & Web"
    schedule:
      kind: "cron"
      expr: "0 16 * * 5"
      tz: "Europe/Berlin"
    agent: "main"
    session: "isolated"
    channel: "telegram"
    to: "306373425"
    announce: true
    message: |
      Wöchentlicher Recherche-Task (Holzgartensteg, Stadt Regensburg).
      AUFGABE: Prüfe, ob es NEUIGKEITEN zum geplanten Holzgartensteg (geplante Fuß-/Radbrücke zwischen Grieser Spitz und Maria-Beer-Platz / Weichs) gibt — seit dem letzten Check bzw. den letzten ~7 Tagen.
      QUELLEN:
      1) ALLRIS via Skill 'regensburg-stadtrat': Script /home/node/mop-skills/mop-skills/skills/regensburg-stadtrat/scripts/regensburg_ris.py — Befehle: search "Holzgartensteg" --limit 30 ; calendar --days 30 ; vorlage <ID> ; session <ID>. Achte auf NEUE Vorlagen, Beschlüsse, Anfragen und Sitzungstermine (Ausschuss für Stadtplanung, Verkehr und Wohnungsfragen / Stadtrat).
      2) Lokale Medien via web_search: regensburg-digital.de, idowa.de, mittelbayerische.de, tvaktuell.com, regensburger-nachrichten.de.
      FOKUS: neue Vorlagen/Beschlüsse, Ausschuss-/Stadtrattermine, Mittel/Budget, Planungsstand (Variante, Kosten, Termin), politische Positionen.
      BEKANNTER STAND (nicht wiederholen, nur Abweichungen melden): 2020 aus Investitionsprogramm gestrichen ('beerdigt'); Comeback ab 2025 (Grüne/Verbände); Kommunalwahl 2026 mehrere Parteien dafür; Haushalt 2026: ~100.000 EUR Planungsmittel im Investitionsprogramm, Stadtrat-Beschluss 26.02.2026, Genehmigung Regierung der Oberpfalz 06.03.2026; Koalitionsvereinbarung 2026 mit Wiederaufnahme der Planungen.
      AUSGABE: Kurz auf Deutsch an Moritz. Falls echte Neuigkeiten: 3-6 Bullets mit Quelle+Link. Falls NICHTS Neues: eine kurze Zeile, z.B. 'Holzgartensteg: keine neuen Entwicklungen diese Woche.' Kein Hintergrund-Recycling.
@@ -0,0 +1,205 @@
 #!/bin/sh
 set -e
 echo "=== OpenClaw Dependency & Runtime Bootstrap ==="
 export PATH="/home/node/.openclaw/bin:/home/node/.openclaw/.local/bin:$PATH"
 SCRIPTS_DIR="/home/node/.openclaw/scripts"
 mkdir -p /home/node/.openclaw/bin "$SCRIPTS_DIR" /home/node/.openclaw/.config
 touch /home/node/.openclaw/.config/keep
 # 1. Sanitize legacy config keys in openclaw.json
 node -e '
  const fs = require("fs");
  for (const file of ["/home/node/.openclaw/openclaw.json", "/home/openclaw/.openclaw/openclaw.json"]) {
    if (fs.existsSync(file)) {
      try {
        const cfg = JSON.parse(fs.readFileSync(file, "utf8"));
        if (cfg.browser) {
          delete cfg.browser.remoteCdpTimeoutMs;
          if (cfg.browser.profiles) {
            if (cfg.browser.profiles.default) delete cfg.browser.profiles.default.color;
            if (cfg.browser.profiles.chrome) delete cfg.browser.profiles.chrome;
          }
        }
        if (cfg.gateway && cfg.gateway.controlUi) {
          delete cfg.gateway.controlUi.dangerouslyDisableDeviceAuth;
        }
        if (!cfg.agents) cfg.agents = {};
        cfg.agents.ownership = "explicit";
        if (cfg.agents.entries && cfg.agents.entries.main) {
          delete cfg.agents.entries.main.default;
        }
        fs.writeFileSync(file, JSON.stringify(cfg, null, 2));
        console.log("Sanitized config file:", file);
      } catch (e) {
        console.error("Failed to sanitize", file, e.message);
      }
    }
  }
 ' || true
 # 2. Run pre-flight session recovery
 echo "Running pre-flight self-healing..."
 python3 "$SCRIPTS_DIR/recover_sessions.py" || true
 # 3. Doctor fix
 echo "Running openclaw doctor --fix to migrate runtime config on PVC..."
 openclaw doctor --fix || true
 # 4. Garmin OAuth tokens bootstrap / preserve
 if [ ! -s /home/node/.openclaw/garmin_tokens/garmin_tokens.json ] && [ -n "$GARMIN_TOKENS_BASE64" ]; then
  echo "Bootstrapping initial Garmin OAuth tokens from secret..."
  mkdir -p /home/node/.openclaw/garmin_tokens
  echo "$GARMIN_TOKENS_BASE64" | base64 -d > /home/node/.openclaw/garmin_tokens/garmin_tokens.json
  chmod 700 /home/node/.openclaw/garmin_tokens
  chmod 600 /home/node/.openclaw/garmin_tokens/garmin_tokens.json
 elif [ -s /home/node/.openclaw/garmin_tokens/garmin_tokens.json ]; then
  echo "Preserving live Garmin OAuth tokens on PVC..."
  chmod 700 /home/node/.openclaw/garmin_tokens
  chmod 600 /home/node/.openclaw/garmin_tokens/garmin_tokens.json
 fi
 # 5. Cleanup legacy binaries and superseded local skills
 rm -rf /home/node/.openclaw/bin/whisper* /home/node/.openclaw/bin/.whisper* /home/node/.openclaw/scripts/whisper* /home/node/.openclaw/models/whisper || true
 rm -rf /home/node/.openclaw/skills/memobird /home/node/.openclaw/skills/nerd-report /home/node/.openclaw/skills/rvv-regensburg /home/node/.openclaw/skills/skill-creator || true
 rm -rf /home/node/.openclaw/workspace/skills /home/node/.openclaw/workspace-koch/skills /home/node/.openclaw/workspace-recherche/skills || true
 # 6. Ensure tools.allow and models.providers.openrouter.apiKey unset
 openclaw config unset tools.allow || true
 openclaw config unset models.providers.openrouter.apiKey || true
 openclaw config unset agents.entries.mila_tracker.tools.profile || true
 openclaw config unset agents.entries.nutrition_tracker.tools.profile || true
 # 7. Decouple hardlinked bootstrap files
 for dir in /home/node/.openclaw/workspace-*; do
  if [ -d "$dir" ]; then
    for file in USER.md MEMORY.md; do
      if [ -f "/home/node/.openclaw/workspace/$file" ]; then
        cp --remove-destination "/home/node/.openclaw/workspace/$file" "$dir/$file"
        chown node:node "$dir/$file" 2>/dev/null || true
        chmod 664 "$dir/$file" 2>/dev/null || true
      fi
    done
  fi
 done
 # 8. Install CLI binaries
 if [ ! -f "/home/node/.openclaw/bin/openhue.real" ]; then
  echo "Installing openhue CLI binary..."
  curl -sL https://github.com/openhue/openhue-cli/releases/download/0.24/openhue_Linux_x86_64.tar.gz | tar -xz -C /home/node/.openclaw/bin openhue
  mv /home/node/.openclaw/bin/openhue /home/node/.openclaw/bin/openhue.real
  printf '#!/bin/sh\nexport HOME=/home/node/.openclaw\nexec /home/node/.openclaw/bin/openhue.real "$@"\n' > /home/node/.openclaw/bin/openhue
  chmod +x /home/node/.openclaw/bin/openhue /home/node/.openclaw/bin/openhue.real
 fi
 if [ ! -f "/home/node/.openclaw/bin/summarize" ]; then
  echo "Installing summarize CLI via npm..."
  npm install -g --prefix /home/node/.openclaw @steipete/summarize || true
 fi
 if [ ! -f "/home/node/.openclaw/bin/mcp-server-github" ]; then
  echo "Installing @modelcontextprotocol/server-github via npm..."
  npm install -g --prefix /home/node/.openclaw @modelcontextprotocol/server-github || true
 fi
 if [ ! -f "/home/node/.openclaw/bin/kubectl" ]; then
  echo "Installing kubectl CLI binary..."
  curl -fsSL https://dl.k8s.io/release/v1.31.0/bin/linux/amd64/kubectl -o /home/node/.openclaw/bin/kubectl
  chmod +x /home/node/.openclaw/bin/kubectl
 fi
 if [ ! -f "/home/node/.openclaw/bin/jq" ]; then
  echo "Installing jq CLI binary..."
  curl -fsSL https://github.com/jqlang/jq/releases/download/jq-1.7.1/jq-linux-amd64 -o /home/node/.openclaw/bin/jq
  chmod +x /home/node/.openclaw/bin/jq
 fi
 if [ ! -f "/home/node/.openclaw/bin/file" ]; then
  echo "Setting up file CLI helper..."
  cp "$SCRIPTS_DIR/file_cli.py" /home/node/.openclaw/bin/file
  chmod +x /home/node/.openclaw/bin/file
 fi
 if [ -x "/home/node/.openclaw/.local/bin/python3" ]; then
  /home/node/.openclaw/bin/uv pip install --break-system-packages --python /home/node/.openclaw/.local/bin/python3 pillow google-api-python-client pypdf || true
 fi
 # 9. Clone or pull infrapuzzle repository to PVC
 mkdir -p /home/node/.openclaw/repos
 if [ ! -d "/home/node/.openclaw/repos/infrapuzzle/.git" ]; then
  echo "Cloning infrapuzzle repository to PVC..."
  git clone --depth 1 "https://${GIT_SYNC_USERNAME}:${GIT_SYNC_PASSWORD}@git.moritzgraf.de/moritz/infrapuzzle.git" /home/node/.openclaw/repos/infrapuzzle || true
 else
  echo "Pulling latest infrapuzzle commits on PVC..."
  git -C /home/node/.openclaw/repos/infrapuzzle pull origin master || git -C /home/node/.openclaw/repos/infrapuzzle pull origin main || true
 fi
 # 10. Seed and maintain persistent mcp-venv
 if [ ! -d "/home/node/.openclaw/mcp-venv" ]; then
  echo "Seeding persistent mcp-venv..."
  uv venv --python 3.12 /home/node/.openclaw/mcp-venv
  uv pip install --python /home/node/.openclaw/mcp-venv \
    prometheus-mcp-server \
    ha-mcp \
    chuk-mcp-open-meteo \
    gitea-mcp \
    git+https://github.com/Taxuspt/garmin_mcp \
    "mcp>=2.0" \
    filetype \
    google-api-python-client \
    google-auth \
    bring-api \
    requests \
    beautifulsoup4 \
    youtube-transcript-api
 fi
 if [ -d "/home/node/.openclaw/mcp-venv" ]; then
  python3 -c 'import os; p="/home/node/.openclaw/mcp-venv/lib/python3.12/site-packages/mcp/server/fastmcp.py"; open(p, "w").write("import os\nfrom fastmcp import FastMCP as _FastMCP, Context\n\nclass FastMCP(_FastMCP):\n    def __init__(self, name=\"MCP Server\", host=None, port=None, **kwargs):\n        if host is not None: os.environ[\"FASTMCP_HOST\"] = str(host)\n        if port is not None: os.environ[\"FASTMCP_PORT\"] = str(port)\n        super().__init__(name=name, **kwargs)\n")' || true
  python3 "$SCRIPTS_DIR/patch_garmin_mcp.py" || true
 fi
 # 11. Extensions & Plugins
 if [ ! -d "/home/node/.openclaw/extensions/perplexity" ]; then
  echo "Installing perplexity plugin..."
  openclaw plugins install clawhub:@openclaw/perplexity-plugin --accept-capabilities || true
 fi
 echo "Enabling memory-wiki plugin..."
 openclaw plugins enable memory-wiki || true
 echo "Patching perplexity web search runtime for chat completions compatibility..."
 node "$SCRIPTS_DIR/patch_perplexity.mjs" || true
 # 12. Ensure OpenRouter auth profile in state DB
 echo "Ensuring OpenRouter auth profile in state DB..."
 node --input-type=module -e '
  import { DatabaseSync } from "node:sqlite";
  const key = process.env.OPENROUTER_API_KEY;
  if (key) {
    try {
      const dbPath = "/home/node/.openclaw/state/openclaw.sqlite";
      const db = new DatabaseSync(dbPath);
      db.prepare("CREATE TABLE IF NOT EXISTS config_machine_state (state_key TEXT PRIMARY KEY, value_json TEXT NOT NULL, updated_at_ms INTEGER NOT NULL)").run();
      const row = db.prepare("SELECT value_json FROM config_machine_state WHERE state_key = \x27authProfiles.store\x27").get();
      let store = row?.value_json ? JSON.parse(row.value_json) : { version: 1, profiles: {} };
      if (!store.profiles) store.profiles = {};
      store.profiles["openrouter:default"] = {
        type: "api_key",
        provider: "openrouter",
        key: key
      };
      db.prepare("INSERT INTO config_machine_state (state_key, value_json, updated_at_ms) VALUES (\x27authProfiles.store\x27, ?, ?) ON CONFLICT(state_key) DO UPDATE SET value_json = excluded.value_json, updated_at_ms = excluded.updated_at_ms")
        .run(JSON.stringify(store), Date.now());
      console.log("Synchronized openrouter auth profile in state DB.");
    } catch (e) {
      console.error("Could not sync auth profile:", e.message);
    }
  }
 ' || true
 # 13. Pre-warm SQLite page cache
 echo "Pre-warming SQLite database files into OS page cache for instant cold start..."
 cat /home/node/.openclaw/state/openclaw.sqlite /home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite > /dev/null 2>&1 || true
 echo "=== Bootstrap Complete ==="
@@ -0,0 +1,336 @@
 #!/usr/bin/env python3
 """
 Nightly multi-agent session maintenance and compaction script for OpenClaw.
 1. Pre-warms OS page cache for SQLite databases on spinning disks.
 2. Recovers any wedged or locked sessions via recover_sessions.py.
 3. Prunes abandoned isolated cron sessions (>48h old) to prevent token/state bloat.
 4. Tier A Hard-Reset: Resets koch, hebamme, and shopping topics to 0 tokens (clean archive).
 5. Tier B Smart-Compaction: Compacts active sessions exceeding token thresholds (5s pacing).
 6. Checkpoints SQLite WAL journals across all agent databases to disk.
 7. Optimizes SQLite query planner without blocking full VACUUM.
 """
 import glob
 import json
 import os
 import sqlite3
 import subprocess
 import sys
 import time
 THRESHOLD_TOKENS = 15000
 THRESHOLD_TRANSCRIPT_BYTES = 200000
 THRESHOLD_EVENT_COUNT = 30
 CRON_MAX_AGE_HOURS = 48
 RPC_TIMEOUT_MS = 180000
 # Tracking Channels: Deterministic sliding-window (mila_tracker, nutrition_tracker).
 # Strict sliding window of ~5-8 events (2-3 turns max), 0 LLM tokens, instant truncation.
 TRACKING_TARGETS = [
    ("mila_tracker", "agent:mila_tracker:telegram:group:-1004326921510:topic:2796"),
    ("nutrition_tracker", "agent:nutrition_tracker:telegram:group:-1004326921510:topic:2797"),
 ]
 MAX_TRACKING_EVENTS = 8
 MAX_TRACKING_LINES = 8
 # Tier A: High-frequency interaction topics (koch, hebamme, shopping).
 # Deep-compaction keeps a compact summary + latest 2 turns without completely wiping conversational memory.
 TIER_A_TARGETS = [
    ("koch", "agent:koch:telegram:group:-1004326921510:topic:21"),
    ("hebamme", "agent:hebamme:telegram:group:-1004326921510:topic:22"),
    ("shopping", "agent:shopping:telegram:group:-1004326921510:topic:115"),
 ]
 def prewarm_page_cache():
    print("=== Pre-warming SQLite databases and Knowledge Wiki into OS page cache ===")
    t0 = time.time()
    try:
        subprocess.run(
            "cat /home/node/.openclaw/state/openclaw.sqlite /home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite > /dev/null 2>&1 || true; "
            "find /home/node/.openclaw/wiki/main /home/node/.openclaw/workspace* -maxdepth 3 -name '*.md' -exec cat {} + > /dev/null 2>&1 || true",
            shell=True,
            timeout=90.0
        )
        print(f"Page cache pre-warmed in {time.time() - t0:.2f}s")
    except Exception as e:
        print(f"Page cache pre-warming warning: {e}")
 def prune_stale_cron_sessions():
    print(f"=== Pruning isolated cron sessions older than {CRON_MAX_AGE_HOURS}h ===")
    cutoff_ms = int(time.time() * 1000) - (CRON_MAX_AGE_HOURS * 3600 * 1000)
    total_pruned = 0
    total_tokens_reclaimed = 0
    for db in sorted(glob.glob("/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite")):
        agent = db.split("/")[5]
        try:
            conn = sqlite3.connect(db, timeout=30.0)
            conn.execute("PRAGMA foreign_keys = ON;")
            cursor = conn.cursor()
            cursor.execute("SELECT name FROM sqlite_master WHERE type=\"table\"")
            all_tables = set(r[0] for r in cursor.fetchall())
            cursor.execute("SELECT session_key, current_session_id, updated_at, entry_json FROM session_nodes WHERE session_key LIKE \"%:cron:%\"")
            stale = []
            for k, sid, up, ej in cursor.fetchall():
                if up and up < cutoff_ms:
                    tok = 0
                    if ej:
                        try:
                            tok = json.loads(ej).get("totalTokens", 0) or 0
                        except Exception:
                            pass
                    stale.append((k, sid, tok))
            if stale:
                tokens_reclaimed = sum(t[2] for t in stale)
                for k, sid, _ in stale:
                    for t in ["trajectory_runtime_events", "transcript_events", "transcript_event_identities", "session_transcript_active_events", "transcript_rewrite_watermarks", "session_transcript_index_state", "session_transcript_fts", "session_conversations"]:
                        if t in all_tables and sid:
                            cursor.execute(f"DELETE FROM {t} WHERE session_id = ?", (sid,))
                    for t in ["session_participants", "heartbeat_outcomes", "session_progress_cards", "board_widgets", "board_tabs"]:
                        if t in all_tables:
                            cursor.execute(f"DELETE FROM {t} WHERE session_key = ?", (k,))
                    if "memory_entry_origins" in all_tables:
                        cursor.execute("DELETE FROM memory_entry_origins WHERE session_key = ? OR session_id = ?", (k, sid or ""))
                    if "session_windows" in all_tables:
                        cursor.execute("DELETE FROM session_windows WHERE session_key = ? OR session_id = ?", (k, sid or ""))
                    cursor.execute("DELETE FROM session_nodes WHERE session_key = ?", (k,))
                conn.commit()
                total_pruned += len(stale)
                total_tokens_reclaimed += tokens_reclaimed
                print(f"  [{agent}] Pruned {len(stale)} dead cron sessions ({tokens_reclaimed} tokens reclaimed)")
            # Unconditionally resolve any dangling foreign key references across all tables
            while True:
                cursor.execute("PRAGMA foreign_key_check;")
                violations = cursor.fetchall()
                if not violations:
                    break
                for table, rowid, parent, fkid in violations:
                    cursor.execute(f"DELETE FROM {table} WHERE rowid = ?", (rowid,))
            conn.commit()
            conn.close()
        except Exception as e:
            print(f"  [{agent}] Pruning error: {e}")
    # Clear resolved quarantine entries if all databases are healthy
    try:
        q_path = "/home/node/.openclaw/state/openclaw-quarantine.sqlite"
        if os.path.exists(q_path):
            q_conn = sqlite3.connect(q_path)
            q_cur = q_conn.cursor()
            q_cur.execute("DELETE FROM quarantined_databases")
            q_conn.commit()
            q_conn.close()
    except Exception as e:
        print(f"Quarantine cleanup error: {e}")
    print(f"Cron pruning complete: {total_pruned} sessions pruned, {total_tokens_reclaimed} tokens reclaimed.")
 def compact_tracking_sessions():
    print("=== Tracking Channels Sliding-Window Maintenance (mila_tracker, nutrition_tracker) ===")
    for agent, key in TRACKING_TARGETS:
        db_path = f"/home/node/.openclaw/agents/{agent}/agent/openclaw-agent.sqlite"
        if not os.path.exists(db_path):
            continue
        try:
            con = sqlite3.connect(db_path, timeout=5.0)
            row = con.execute("SELECT current_session_id FROM session_nodes WHERE session_key=?", (key,)).fetchone()
            if not row or not row[0]:
                con.close()
                print(f"  [{agent}] No active session node found for {key}.")
                continue
            sid = row[0]
            cnt = con.execute("SELECT count(*) FROM transcript_events WHERE session_id=?", (sid,)).fetchone()[0]
            con.close()
            if cnt > MAX_TRACKING_EVENTS:
                print(f"  [{agent}] Session {key} has {cnt} events (> {MAX_TRACKING_EVENTS}). Truncating to last {MAX_TRACKING_LINES} lines...")
                cmd = [
                    "openclaw", "sessions", "compact", key,
                    "--agent", agent,
                    "--max-lines", str(MAX_TRACKING_LINES),
                    "--timeout", "30000"
                ]
                r = subprocess.run(cmd, capture_output=True, text=True)
                if r.returncode == 0:
                    print(f"    ✓ Truncated successfully: {r.stdout.strip()}")
                else:
                    print(f"    ✗ Truncation failed: {r.stderr.strip()}")
            else:
                print(f"  [{agent}] Session {key} has {cnt} events (<= {MAX_TRACKING_EVENTS}). Clean.")
        except Exception as e:
            print(f"  ✗ [{agent}] Error during tracking compaction: {e}")
 def compact_tier_a_sessions():
    print("=== Tier A: Deep-Compaction (koch, hebamme, shopping) ===")
    for agent, key in TIER_A_TARGETS:
        db_path = f"/home/node/.openclaw/agents/{agent}/agent/openclaw-agent.sqlite"
        if not os.path.exists(db_path):
            continue
        try:
            con = sqlite3.connect(db_path, timeout=10.0)
            row = con.execute("SELECT current_session_id FROM session_nodes WHERE session_key=?", (key,)).fetchone()
            con.close()
            if not row or not row[0]:
                print(f"  [Tier A] {agent} ({key}) already at 0 (no active session).")
                continue
            ev_cnt, ev_bytes = get_session_metrics(agent, key, row[0])
            if ev_cnt <= 2 and ev_bytes < 20000:
                print(f"  [Tier A] {agent} ({key}) has only {ev_cnt} events ({ev_bytes} bytes), skipping.")
                continue
            print(f"  [Tier A] Deep-compacting {agent} ({key}) [{ev_cnt} events, {ev_bytes//1024}KB]...")
            r = subprocess.run(
                ["openclaw", "sessions", "compact", key, "--agent", agent, "--timeout", str(RPC_TIMEOUT_MS)],
                capture_output=True, text=True
            )
            if r.returncode == 0:
                print(f"    ✓ Deep-compacted: {r.stdout.strip()}")
            elif "Already compacted" in r.stderr or "Already compacted" in r.stdout:
                print(f"    ✓ Already compacted.")
            else:
                print(f"    ✗ Standard compact error: {r.stderr.strip()}; retrying with --max-lines 40...")
                fb = subprocess.run(
                    ["openclaw", "sessions", "compact", key, "--agent", agent, "--max-lines", "40", "--timeout", str(RPC_TIMEOUT_MS)],
                    capture_output=True, text=True
                )
                if fb.returncode == 0:
                    print(f"    ✓ Truncation fallback success: {fb.stdout.strip()}")
                else:
                    print(f"    ✗ Truncation fallback failed: {fb.stderr.strip()}")
        except Exception as e:
            print(f"    ✗ Exception deep-compacting {agent}: {e}")
        time.sleep(2)
 def get_session_metrics(agent, key, sid=None):
    db_path = f"/home/node/.openclaw/agents/{agent}/agent/openclaw-agent.sqlite"
    if not os.path.exists(db_path):
        return 0, 0
    try:
        con = sqlite3.connect(db_path, timeout=5.0)
        cur = con.cursor()
        if not sid:
            row = cur.execute("SELECT current_session_id FROM session_nodes WHERE session_key=?", (key,)).fetchone()
            sid = row[0] if row else None
        if not sid:
            con.close()
            return 0, 0
        ev_cnt, ev_bytes = cur.execute(
            "SELECT count(*), coalesce(sum(length(event_json)), 0) FROM transcript_events WHERE session_id=?", 
            (sid,)
        ).fetchone()
        con.close()
        return ev_cnt, ev_bytes
    except Exception:
        return 0, 0
 def compact_active_sessions():
    excluded_keys = set(t[1] for t in TIER_A_TARGETS) | set(t[1] for t in TRACKING_TARGETS)
    print(f"=== Tier B: Running Multi-Agent Compaction (threshold: {THRESHOLD_TOKENS} tokens / {THRESHOLD_TRANSCRIPT_BYTES//1024}KB, LLM summarization) ===")
    res = subprocess.run(["openclaw", "sessions", "--all-agents", "--json"], capture_output=True, text=True)
    if res.returncode != 0:
        print(f"Failed to list sessions: {res.stderr}")
        return
    sessions = json.loads(res.stdout).get("sessions", [])
    compacted = 0
    skipped = 0
    for s in sessions:
        key = s.get("key", "")
        agent = s.get("agentId") or "main"
        tokens = s.get("totalTokens") or 0
        sid = s.get("sessionId")
        # Skip Tier A and Tracking agents as they have dedicated routines
        if key in excluded_keys:
            continue
        # Target main sessions and all telegram sessions (topics and direct)
        is_target = (
            key == "agent:main:main" or 
            ":telegram:" in key or
            (key.startswith("agent:") and key.endswith(":main"))
        )
        if is_target and not key.endswith(":heartbeat"):
            ev_cnt, ev_bytes = get_session_metrics(agent, key, sid)
            needs_compaction = (
                tokens >= THRESHOLD_TOKENS or
                ev_bytes >= THRESHOLD_TRANSCRIPT_BYTES or
                (tokens == 0 and ev_cnt >= THRESHOLD_EVENT_COUNT)
            )
            if needs_compaction:
                stat_str = f"{tokens} tokens" if tokens else f"{ev_bytes//1024}KB / {ev_cnt} events"
                print(f"Compacting {agent} ({stat_str}) -> {key}...")
                c_res = subprocess.run(
                    ["openclaw", "sessions", "compact", key, "--agent", agent, "--timeout", str(RPC_TIMEOUT_MS)],
                    capture_output=True, text=True
                )
                if c_res.returncode == 0:
                    print(f"  ✓ {c_res.stdout.strip()}")
                    compacted += 1
                elif "Already compacted" in c_res.stderr or "Already compacted" in c_res.stdout:
                    print(f"  ✓ Already compacted.")
                    skipped += 1
                else:
                    print(f"  ✗ {c_res.stderr.strip()}; retrying with --max-lines 80 fallback...")
                    fb_res = subprocess.run(
                        ["openclaw", "sessions", "compact", key, "--agent", agent, "--max-lines", "80", "--timeout", str(RPC_TIMEOUT_MS)],
                        capture_output=True, text=True
                    )
                    if fb_res.returncode == 0:
                        print(f"  ✓ (fallback) {fb_res.stdout.strip()}")
                        compacted += 1
                    else:
                        print(f"  ✗ Fallback failed: {fb_res.stderr.strip()}")
                time.sleep(5)  # 5s pause to avoid rotational HDD I/O saturation
            else:
                skipped += 1
    print(f"Compaction complete: {compacted} compacted, {skipped} skipped.")
 def checkpoint_wal_journals():
    print("=== Checkpointing SQLite WAL journals across all agent databases ===")
    dbs = ["/home/node/.openclaw/state/openclaw.sqlite"] + glob.glob("/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite")
    wal_freed = 0
    for db in dbs:
        wal = db + "-wal"
        if os.path.exists(wal):
            sz = os.path.getsize(wal)
            try:
                con = sqlite3.connect(db, timeout=30.0)
                con.execute("PRAGMA wal_checkpoint(TRUNCATE);")
                con.close()
                wal_freed += sz
            except Exception as e:
                print(f"  ✗ Error checkpointing {db}: {e}")
    print(f"WAL Checkpoint complete: {wal_freed / (1024*1024):.2f} MB merged to disk.")
 def vacuum_and_optimize():
    print("=== Running SQLite OPTIMIZE across all databases ===")
    dbs = ["/home/node/.openclaw/state/openclaw.sqlite"] + glob.glob("/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite")
    for db in dbs:
        try:
            con = sqlite3.connect(db, timeout=30.0)
            con.execute("PRAGMA optimize;")
            con.close()
        except Exception as e:
            print(f"  ✗ Error optimizing {db}: {e}")
    print("SQLite optimization complete.")
 def main():
    prewarm_page_cache()
    try:
        subprocess.run(["python3", "/home/node/.openclaw/scripts/recover_sessions.py"], check=False)
    except Exception:
        pass
    prune_stale_cron_sessions()
    compact_tracking_sessions()
    compact_tier_a_sessions()
    compact_active_sessions()
    checkpoint_wal_journals()
    vacuum_and_optimize()
    prewarm_page_cache()
 if __name__ == "__main__":
    main()
@@ -0,0 +1,66 @@
 #!/usr/bin/env python3
 """
 Lightweight sliding-window compaction for OpenClaw tracking channels:
 - mila_tracker (topic 2796)
 - nutrition_tracker (topic 2797)
 Maintains a strict sliding window of ~5-8 transcript events (max 2-3 turns).
 Uses native gateway truncation (--max-lines 8) requiring 0 LLM tokens and 0 external API calls.
 """
 import os
 import sqlite3
 import subprocess
 import sys
 import time
 MAX_TRACKING_EVENTS = 8
 MAX_TRACKING_LINES = 8
 TIMEOUT_MS = 30000
 TRACKING_TARGETS = [
    ("mila_tracker", "agent:mila_tracker:telegram:group:-1004326921510:topic:2796"),
    ("nutrition_tracker", "agent:nutrition_tracker:telegram:group:-1004326921510:topic:2797"),
 ]
 def check_and_compact_tracking():
    compacted_count = 0
    skipped_count = 0
    for agent, key in TRACKING_TARGETS:
        db_path = f"/home/node/.openclaw/agents/{agent}/agent/openclaw-agent.sqlite"
        if not os.path.exists(db_path):
            continue
        try:
            con = sqlite3.connect(db_path, timeout=5.0)
            row = con.execute("SELECT current_session_id FROM session_nodes WHERE session_key=?", (key,)).fetchone()
            if not row or not row[0]:
                con.close()
                continue
            sid = row[0]
            cnt = con.execute("SELECT count(*) FROM transcript_events WHERE session_id=?", (sid,)).fetchone()[0]
            con.close()
            if cnt > MAX_TRACKING_EVENTS:
                print(f"[{agent}] Session {key} has {cnt} events (threshold {MAX_TRACKING_EVENTS}). Truncating to last {MAX_TRACKING_LINES} lines...")
                cmd = [
                    "openclaw", "sessions", "compact", key,
                    "--agent", agent,
                    "--max-lines", str(MAX_TRACKING_LINES),
                    "--timeout", str(TIMEOUT_MS)
                ]
                res = subprocess.run(cmd, capture_output=True, text=True)
                if res.returncode == 0:
                    print(f"  ✓ [{agent}] Truncated successfully: {res.stdout.strip()}")
                    compacted_count += 1
                else:
                    print(f"  ✗ [{agent}] Truncation failed: {res.stderr.strip()}", file=sys.stderr)
            else:
                skipped_count += 1
        except Exception as e:
            print(f"[{agent}] Error checking session: {e}", file=sys.stderr)
    if compacted_count > 0:
        print(f"Tracking maintenance: {compacted_count} sessions truncated, {skipped_count} within window.")
 if __name__ == "__main__":
    check_and_compact_tracking()
@@ -0,0 +1,48 @@
 #!/usr/bin/env python3
 import glob, json, os, sqlite3, sys
 cfg_path = "/home/node/.openclaw/openclaw.json"
 if os.path.exists(cfg_path):
    try:
        with open(cfg_path, "r") as f:
            cfg = json.load(f)
        mem_search = cfg.get("memory", {}).get("search", {})
        if mem_search.get("extraPaths"):
            mem_search["extraPaths"] = []
            with open(cfg_path, "w") as f:
                json.dump(cfg, f, indent=2)
            print("[dedup_subagents] Cleared top-level memory.search.extraPaths from openclaw.json (scoped to main only)")
    except Exception as e:
        print(f"[dedup_subagents] Warning checking openclaw.json: {e}", file=sys.stderr)
 vec_path = "/app/node_modules/sqlite-vec-linux-x64/vec0.so"
 for db in sorted(glob.glob("/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite")):
    agent = os.path.basename(os.path.dirname(os.path.dirname(db)))
    if agent == "main":
        continue
    try:
        conn = sqlite3.connect(db, timeout=10.0)
        if os.path.exists(vec_path):
            conn.enable_load_extension(True)
            conn.load_extension(vec_path)
        cur = conn.cursor()
        chk = cur.execute("SELECT count(*) FROM memory_index_chunks").fetchone()[0]
        if chk > 0:
            print(f"[dedup_subagents] Purging {chk} duplicated vector chunks from agent {agent}...")
            for t in [
                "memory_index_sources",
                "memory_index_chunks",
                "memory_index_chunk_recall_metadata",
                "memory_index_chunk_provenance",
                "memory_entry_origins",
                "memory_embedding_cache",
                "memory_index_chunks_vec"
            ]:
                try: cur.execute(f"DELETE FROM {t}")
                except Exception: pass
            conn.commit()
            cur.execute("VACUUM")
            print(f"[dedup_subagents] Reclaimed disk space for agent {agent}")
        conn.close()
    except Exception as e:
        print(f"[dedup_subagents] Notice for {agent}: {e}", file=sys.stderr)
@@ -0,0 +1,50 @@
 #!/home/node/.openclaw/mcp-venv/bin/python3
 import sys, os, mimetypes, filetype
 def get_file_info(filepath, mime_only=False):
    if not os.path.exists(filepath):
        return "cannot open (No such file or directory)", "cannot open (No such file or directory)"
    if os.path.isdir(filepath):
        return "directory", "inode/directory"
    kind = filetype.guess(filepath)
    if kind is not None:
        return f"{kind.extension.upper()} image/media data ({kind.mime})", kind.mime
    guessed_mime, _ = mimetypes.guess_type(filepath)
    try:
        with open(filepath, "rb") as f:
            sample = f.read(4096)
        if len(sample) == 0:
            return "empty", "application/x-empty"
        try:
            sample.decode("utf-8")
            if guessed_mime:
                return f"{guessed_mime} text", guessed_mime
            return "ASCII text", "text/plain"
        except UnicodeDecodeError:
            return "data", "application/octet-stream"
    except Exception as e:
        return f"cannot read ({e})", "application/octet-stream"
 def main():
    args = sys.argv[1:]
    brief, mime_only, files = False, False, []
    for arg in args:
        if arg in ("-b", "--brief"):
            brief = True
        elif arg in ("-i", "--mime", "--mime-type"):
            mime_only = True
        elif arg.startswith("-") and len(arg) > 1 and not arg.startswith("--"):
            if "b" in arg: brief = True
            if "i" in arg: mime_only = True
        else:
            files.append(arg)
    if not files:
        sys.stderr.write("Usage: file [-b] [-i|--mime-type] <file>...\n")
        sys.exit(1)
    for f in files:
        desc, mime = get_file_info(f, mime_only)
        res = mime if mime_only else desc
        print(res if brief else f"{f}: {res}")
 if __name__ == "__main__":
    main()
@@ -0,0 +1,78 @@
 import fs from "node:fs";
 import path from "node:path";
 import { execSync, spawn } from "node:child_process";
 if (!process.env.__OPENCLAW_PREFLIGHT_DONE) {
  process.env.__OPENCLAW_PREFLIGHT_DONE = "1";
  const isGateway = process.argv.some(arg => arg.endsWith("openclaw.mjs") || arg.endsWith("openclaw")) && process.argv.includes("gateway");
  if (isGateway) {
    const t0 = Date.now();
    console.log("[gateway-preflight] Initializing container self-healing preflight...");
    // 1. Clean up stale gateway lock files from ungraceful kills
    for (const dir of ["/tmp/openclaw-1000", "/tmp"]) {
      if (fs.existsSync(dir)) {
        try {
          const files = fs.readdirSync(dir);
          for (const file of files) {
            if (file.startsWith("gateway") && file.endsWith(".lock")) {
              const fullPath = path.join(dir, file);
              fs.unlinkSync(fullPath);
              console.log(`[gateway-preflight] Removed stale lock: ${fullPath}`);
            }
          }
        } catch (e) {
          console.warn(`[gateway-preflight] Lock cleanup warning in ${dir}:`, e.message);
        }
      }
    }
    // 2. Clear false database quarantines
    const qPath = "/home/node/.openclaw/state/openclaw-quarantine.sqlite";
    if (fs.existsSync(qPath)) {
      try {
        execSync(`/home/node/.openclaw/.local/bin/python3 -c "import sqlite3; c=sqlite3.connect(\x27${qPath}\x27); c.execute(\x27DELETE FROM quarantined_databases\x27); c.commit(); c.close()"`, { stdio: "ignore" });
        console.log("[gateway-preflight] Cleared database quarantine.");
      } catch (_) {}
    }
    // 3. Deduplicate subagent vector databases (keeps non-main agent DBs < 15MB)
    try {
      execSync("/home/node/.openclaw/.local/bin/python3 /home/node/.openclaw/scripts/dedup_subagent_vectors.py", { stdio: "inherit" });
    } catch (e) {
      console.warn("[gateway-preflight] Vector deduplication warning:", e.message);
    }
    // 4. Pre-warm page cache sequentially (transforms random 70 IOPS disk reads into sequential streaming)
    try {
      const pw0 = Date.now();
      execSync("cat /home/node/.openclaw/state/openclaw.sqlite /home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite > /dev/null 2>&1 || true; find /home/node/.openclaw/wiki/main /home/node/.openclaw/workspace* -maxdepth 3 -name '*.md' -exec cat {} + > /dev/null 2>&1 || true");
      console.log(`[gateway-preflight] Pre-warmed SQLite databases and Wiki markdown in ${Date.now() - pw0}ms`);
    } catch (_) {}
    // 5. Recover any wedged running sessions left over from ungraceful container restart
    try {
      execSync("/home/node/.openclaw/.local/bin/python3 /home/node/.openclaw/scripts/recover_sessions.py", { stdio: "inherit" });
    } catch (e) {
      console.warn("[gateway-preflight] Session recovery warning:", e.message);
    }
    // 6. Spawn background turn replay daemon if interrupted turns were detected
    try {
      if (fs.existsSync("/tmp/openclaw-interrupted-turns.json")) {
        console.log("[gateway-preflight] Spawning background turn replay daemon...");
        const child = spawn("/home/node/.openclaw/.local/bin/python3", ["/home/node/.openclaw/scripts/replay_interrupted_turns.py"], {
          detached: true,
          stdio: "ignore"
        });
        child.unref();
      }
    } catch (e) {
      console.warn("[gateway-preflight] Could not spawn turn replay daemon:", e.message);
    }
    console.log(`[gateway-preflight] Self-healing completed in ${Date.now() - t0}ms.`);
  }
 }
@@ -22,6 +22,8 @@ TOPIC_TO_AGENT = {
    "118": "doktor",
    "119": "itguy",
    "164": "grabengasse_media",
    "2796": "mila_tracker",
    "2797": "nutrition_tracker",
 }
 def parse_args():
@@ -49,12 +51,12 @@ def triage_agent_session(agent, topic_id=None, limit=10, db_root="/home/node/.op
    if topic_id:
        target_pattern = f"%topic:{topic_id}%"
        cur.execute(
-            "SELECT session_key, current_session_id, status, updated_at, entry_json FROM session_nodes WHERE session_key LIKE ? ORDER BY updated_at DESC LIMIT 1",
+            "SELECT session_key, current_session_id, status, updated_at, entry_json FROM session_nodes WHERE session_key LIKE ? AND session_key NOT LIKE '%:heartbeat' ORDER BY updated_at DESC LIMIT 1",
            (target_pattern,)
        )
    else:
        cur.execute(
-            "SELECT session_key, current_session_id, status, updated_at, entry_json FROM session_nodes ORDER BY updated_at DESC LIMIT 1"
+            "SELECT session_key, current_session_id, status, updated_at, entry_json FROM session_nodes WHERE session_key NOT LIKE '%:heartbeat' ORDER BY updated_at DESC LIMIT 1"
        )
    row = cur.fetchone()
@@ -90,6 +92,22 @@ def triage_agent_session(agent, topic_id=None, limit=10, db_root="/home/node/.op
    elif status == "processing":
        badges.append("⚡ [ACTIVE_PROCESSING]")
    # Check ingress queue status
    state_db = "/home/node/.openclaw/state/openclaw.sqlite"
    if topic_id and os.path.exists(state_db):
        try:
            s_con = sqlite3.connect(state_db, timeout=2.0)
            lane_pat = f"%topic:{topic_id}%"
            pending_cnt = s_con.execute(
                "SELECT count(*) FROM channel_ingress_events WHERE lane_key LIKE ? AND status IN ('pending', 'claimed')",
                (lane_pat,)
            ).fetchone()[0]
            s_con.close()
            if pending_cnt > 0:
                badges.append(f"📬 [INGRESS_STALLED: {pending_cnt} message(s) pending]")
        except Exception:
            pass
    print("=" * 72)
    print(f"🎯 AGENT: {agent.upper():<12} | TOPIC: {topic_id or 'N/A':<6} | STATUS: {status.upper()}")
    print(f"   SESSION KEY: {skey}")
@@ -0,0 +1,64 @@
 import os
 p = "/home/node/.openclaw/mcp-venv/lib/python3.12/site-packages/garmin_mcp/workouts.py"
 if os.path.exists(p):
    with open(p, "r") as f:
        c = f.read()
    if "_normalize_sport_type" not in c:
        patch = '''
 SPORT_TYPE_MAPPINGS = {
    "running": {"sportTypeId": 1, "sportTypeKey": "running", "displayOrder": 1},
    "cycling": {"sportTypeId": 2, "sportTypeKey": "cycling", "displayOrder": 2},
    "other": {"sportTypeId": 3, "sportTypeKey": "other", "displayOrder": 3},
    "lap_swimming": {"sportTypeId": 4, "sportTypeKey": "lap_swimming", "displayOrder": 4},
    "swimming": {"sportTypeId": 4, "sportTypeKey": "lap_swimming", "displayOrder": 4},
    "strength_training": {"sportTypeId": 5, "sportTypeKey": "strength_training", "displayOrder": 5},
    "cardio_training": {"sportTypeId": 6, "sportTypeKey": "cardio_training", "displayOrder": 6},
    "cardio": {"sportTypeId": 6, "sportTypeKey": "cardio_training", "displayOrder": 6},
    "yoga": {"sportTypeId": 7, "sportTypeKey": "yoga", "displayOrder": 8},
    "pilates": {"sportTypeId": 8, "sportTypeKey": "pilates", "displayOrder": 9},
    "hiit": {"sportTypeId": 9, "sportTypeKey": "hiit", "displayOrder": 7},
    "mobility": {"sportTypeId": 11, "sportTypeKey": "mobility", "displayOrder": 11},
    "walking": {"sportTypeId": 12, "sportTypeKey": "walking", "displayOrder": 10},
    "rucking": {"sportTypeId": 13, "sportTypeKey": "rucking", "displayOrder": 12},
 }
 SPORT_ID_MAPPINGS = {v["sportTypeId"]: v for v in SPORT_TYPE_MAPPINGS.values()}
 def _resolve_sport_block(st):
    if isinstance(st, str):
        k = st.strip().lower()
        if k in SPORT_TYPE_MAPPINGS:
            return dict(SPORT_TYPE_MAPPINGS[k])
    elif isinstance(st, dict):
        key = st.get("sportTypeKey")
        sid = st.get("sportTypeId")
        if key and str(key).strip().lower() in SPORT_TYPE_MAPPINGS:
            base = dict(SPORT_TYPE_MAPPINGS[str(key).strip().lower()])
            if sid is not None and sid != 0 and sid != base["sportTypeId"]:
                raise ValueError(f"sportType mismatch: {key} vs {sid}")
            return base
        if sid is not None and sid in SPORT_ID_MAPPINGS:
            return dict(SPORT_ID_MAPPINGS[sid])
    return None
 def _normalize_sport_type(workout_data: dict) -> None:
    resolved = _resolve_sport_block(workout_data.get("sportType"))
    segments = workout_data.get("workoutSegments") or []
    if not resolved and segments:
        for seg in segments:
            resolved = _resolve_sport_block(seg.get("sportType"))
            if resolved:
                break
    if not resolved:
        raise ValueError("Missing or invalid sportType. Both sportTypeId and sportTypeKey are required.")
    workout_data["sportType"] = resolved
    for seg in segments:
        st = _resolve_sport_block(seg.get("sportType"))
        seg["sportType"] = st if st else dict(resolved)
 '''
        t = "def _normalize_workout_steps(workout_data: dict) -> None:"
        if t in c:
            with open(p, "w") as f:
                f.write(c.replace(t, patch + t + "\n    _normalize_sport_type(workout_data)", 1))
            print("Successfully patched garmin_mcp workouts.py!")
@@ -0,0 +1,61 @@
 import fs from "node:fs";
 import path from "node:path";
 import { globSync } from "node:fs";
 const baseDir = "/home/node/.openclaw/extensions/perplexity/dist";
 if (fs.existsSync(baseDir)) {
  const files = fs.readdirSync(baseDir).filter(f => f.startsWith("perplexity-web-search-provider.runtime-") && f.endsWith(".js"));
  for (const filename of files) {
    const file = path.join(baseDir, filename);
    let code = fs.readFileSync(file, "utf8");
    if (!code.includes("/* PATCHED_CHAT_COMPLETIONS */")) {
      const target = "const structured = runtime.transport === \"search_api\";";
      const fastPath = `const structured = runtime.transport === "search_api"; /* PATCHED_CHAT_COMPLETIONS */
        if (!structured) {
          const cacheKey = buildSearchCacheKey([
            "perplexity",
            runtime.transport,
            runtime.baseUrl,
            runtime.model,
            query,
            freshness
          ]);
          const cacheTtlMs = resolveSearchCacheTtlMs(searchConfig);
          const cached = readCachedSearchPayload(cacheKey, cacheTtlMs);
          if (cached) return cached;
          const start = Date.now();
          const timeoutSeconds = resolveSearchTimeoutSeconds(searchConfig);
          const result = await runPerplexitySearch({
            query,
            apiKey: runtime.apiKey,
            baseUrl: runtime.baseUrl,
            model: runtime.model,
            timeoutSeconds,
            signal,
            freshness
          });
          const payload = {
            query,
            provider: "perplexity",
            model: runtime.model,
            tookMs: Date.now() - start,
            externalContent: {
              untrusted: true,
              source: "web_search",
              provider: "perplexity",
              wrapped: true
            },
            content: wrapWebContent(result.content, "web_search"),
            citations: result.citations
          };
          writeCachedSearchPayload(cacheKey, payload);
          return payload;
        }`;
      if (code.includes(target)) {
        code = code.replace(target, fastPath);
        fs.writeFileSync(file, code, "utf8");
        console.log("Patched perplexity runtime for chat completions:", file);
      }
    }
  }
 }
@@ -0,0 +1,96 @@
 #!/usr/bin/env python3
 import glob, sqlite3, json, os, sys, time
 t0 = time.time()
 recovered = 0
 interrupted_turns = []
 def extract_prompt(msg):
    if not msg: return ""
    content = msg.get("content")
    if isinstance(content, str): return content
    if isinstance(content, list):
        parts = []
        for c in content:
            if isinstance(c, dict): parts.append(c.get("text") or c.get("content") or "")
            elif isinstance(c, str): parts.append(c)
        return "\n".join(filter(None, parts))
    return str(content or "")
 for db in sorted(glob.glob("/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite")):
    try:
        conn = sqlite3.connect(db, timeout=10.0)
        cursor = conn.cursor()
        while True:
            cursor.execute("PRAGMA foreign_key_check;")
            violations = cursor.fetchall()
            if not violations: break
            for table, rowid, parent, fkid in violations:
                cursor.execute(f"DELETE FROM {table} WHERE rowid = ?", (rowid,))
        cursor.execute("SELECT session_key, entry_json, current_session_id, status FROM session_nodes WHERE status IN (\"running\", \"failed\", \"error\")")
        rows = cursor.fetchall()
        agent_id = os.path.basename(os.path.dirname(os.path.dirname(db)))
        for sk, ej, csid, st in rows:
            try:
                p = json.loads(ej) if ej else {}
                sid = csid or p.get("sessionId")
                if sid:
                    ev = cursor.execute("SELECT seq, event_json FROM transcript_events WHERE session_id = ? ORDER BY seq DESC LIMIT 1", (sid,)).fetchone()
                    if ev:
                        ev_seq, ev_raw = ev
                        try:
                            ev_data = json.loads(ev_raw)
                            msg = ev_data.get("message") or ev_data
                            if st == "running" and msg.get("role") == "user":
                                prompt_text = extract_prompt(msg)
                                ctx = p.get("restartRecoveryDeliveryContext") or p.get("delivery", {}).get("context") or p.get("delivery", {}).get("route", {}).get("context") or {}
                                interrupted_turns.append({
                                    "agent": agent_id,
                                    "session_key": sk,
                                    "session_id": sid,
                                    "context": ctx,
                                    "prompt": prompt_text
                                })
                                cursor.execute("PRAGMA foreign_keys = ON")
                                cursor.execute("DELETE FROM transcript_events WHERE session_id = ? AND seq = ?", (sid, ev_seq))
                            elif msg.get("role") == "assistant" and msg.get("stopReason") == "error":
                                cursor.execute("PRAGMA foreign_keys = ON")
                                cursor.execute("DELETE FROM transcript_events WHERE session_id = ? AND seq = ?", (sid, ev_seq))
                        except Exception as ex:
                            print(f"[recover_sessions] Error parsing event: {ex}", file=sys.stderr)
                p["status"] = "done"
                p["activeWriterRunId"] = None
                p["activeClaimRunId"] = None
                p["restartRecoveryDeliveryRunId"] = None
                cursor.execute("UPDATE session_nodes SET status = \"done\", entry_json = ? WHERE session_key = ?", (json.dumps(p), sk))
                cursor.execute("UPDATE session_nodes SET entry_valid = 1 WHERE session_key = ?", (sk,))
                recovered += 1
            except Exception: pass
        cursor.execute("UPDATE session_nodes SET entry_valid = 1 WHERE entry_valid != 1")
        cursor.execute("UPDATE session_windows SET status = \"done\" WHERE status IN (\"running\", \"failed\", \"error\")")
        conn.commit()
        conn.close()
    except Exception as e:
        print(f"[recover_sessions] Warning for {db}: {e}", file=sys.stderr)
 state_db = "/home/node/.openclaw/state/openclaw.sqlite"
 if os.path.exists(state_db):
    try:
        sconn = sqlite3.connect(state_db, timeout=10.0)
        scur = sconn.cursor()
        scur.execute("UPDATE channel_ingress_events SET attempts = 0, last_attempt_at = NULL, last_error = NULL WHERE status = 'pending' AND attempts > 0")
        sconn.commit()
        sconn.close()
    except Exception as e:
        print(f"[recover_sessions] Warning resetting ingress backoff: {e}", file=sys.stderr)
 if interrupted_turns:
    try:
        with open("/tmp/openclaw-interrupted-turns.json", "w") as f:
            json.dump(interrupted_turns, f, indent=2)
        print(f"[recover_sessions] Detected {len(interrupted_turns)} interrupted user turn(s) saved to /tmp/openclaw-interrupted-turns.json")
    except Exception as e:
        print(f"[recover_sessions] Error writing interrupted turns: {e}", file=sys.stderr)
 print(f"[recover_sessions] Completed in {time.time() - t0:.2f}s ({recovered} wedged sessions recovered)")
@@ -0,0 +1,97 @@
 #!/usr/bin/env python3
 import json, os, subprocess, sys, time, urllib.request
 INTERRUPTED_FILE = "/tmp/openclaw-interrupted-turns.json"
 if not os.path.exists(INTERRUPTED_FILE):
    sys.exit(0)
 try:
    with open(INTERRUPTED_FILE, "r") as f:
        turns = json.load(f)
 except Exception as e:
    print(f"[replay_interrupted_turns] Failed to read {INTERRUPTED_FILE}: {e}", file=sys.stderr)
    sys.exit(0)
 if not turns:
    sys.exit(0)
 print(f"[replay_interrupted_turns] Found {len(turns)} interrupted turn(s). Waiting for gateway /healthz...")
 gateway_ready = False
 for _ in range(60):
    try:
        with urllib.request.urlopen("http://127.0.0.1:18790/healthz", timeout=3) as resp:
            if resp.status == 200:
                gateway_ready = True
                break
    except Exception:
        pass
    time.sleep(2)
 if not gateway_ready:
    print("[replay_interrupted_turns] Gateway did not become healthy in 120s. Aborting.", file=sys.stderr)
    sys.exit(1)
 # Allow 5s for Telegram ingress to bind
 time.sleep(5)
 for turn in turns:
    sk = turn.get("session_key")
    sid = turn.get("session_id")
    agent_id = turn.get("agent")
    ctx = turn.get("context") or {}
    prompt = turn.get("prompt") or ""
    channel = ctx.get("channel") or "telegram"
    to_target = ctx.get("to") or ""
    thread_id = ctx.get("threadId")
    target = to_target
    if target.startswith("telegram:"):
        parts = target.split(":")
        target = parts[1] if len(parts) > 1 else target
    print(f"[replay_interrupted_turns] Processing agent '{agent_id}' on session '{sk}' target='{target}' thread='{thread_id}'")
    # 1. Send status notification to Telegram if target exists
    if target:
        notice = "⚠️ OpenClaw wurde während der Bearbeitung neu gestartet – deine Anfrage wird jetzt nachgeholt..."
        notify_cmd = [
            "openclaw", "message", "send",
            "--channel", channel,
            "--target", str(target),
            "-m", notice
        ]
        if thread_id is not None:
            notify_cmd.extend(["--thread-id", str(thread_id)])
        try:
            subprocess.run(notify_cmd, check=False, timeout=30)
            print(f"[replay_interrupted_turns] Sent recovery notice to {target}")
        except Exception as e:
            print(f"[replay_interrupted_turns] Notice failed: {e}", file=sys.stderr)
    # 2. Replay agent turn
    if sk and prompt:
        p_short = (prompt[:60] + "...") if len(prompt) > 60 else prompt
        print(f"[replay_interrupted_turns] Replaying agent turn: {p_short}")
        agent_cmd = [
            "openclaw", "agent",
            "--session-key", sk,
            "-m", prompt,
            "--deliver"
        ]
        try:
            res = subprocess.run(agent_cmd, capture_output=True, text=True, timeout=300)
            if res.returncode == 0:
                print(f"[replay_interrupted_turns] Turn replay succeeded for {sk}")
            else:
                print(f"[replay_interrupted_turns] Turn replay exited with code {res.returncode}: {res.stderr[:200]}", file=sys.stderr)
        except Exception as e:
            print(f"[replay_interrupted_turns] Replay execution error: {e}", file=sys.stderr)
 try:
    os.remove(INTERRUPTED_FILE)
    print(f"[replay_interrupted_turns] Cleaned up {INTERRUPTED_FILE}")
 except Exception:
    pass
@@ -0,0 +1,144 @@
 #!/usr/bin/env python3
 """
 sync_crons.py
 Idempotently reconciles declarative OpenClaw automations defined in crons.yaml
 with the running OpenClaw gateway state.
 Can run directly inside the container or remotely via kubectl exec.
 """
 import json
 import os
 import subprocess
 import sys
 try:
    import yaml
 except ImportError:
    venv_py = "/home/node/.openclaw/mcp-venv/bin/python3"
    if os.path.exists(venv_py) and sys.executable != venv_py:
        os.execv(venv_py, [venv_py] + sys.argv)
    raise
 def find_crons_file():
    candidates = [
        os.environ.get("CRONS_FILE"),
        "crons.yaml",
        "k8s/openclaw/crons.yaml",
        "/home/node/.openclaw/scripts/crons.yaml",
        os.path.join(os.path.dirname(__file__), "../crons.yaml"),
        os.path.join(os.path.dirname(__file__), "crons.yaml"),
    ]
    for c in candidates:
        if c and os.path.exists(c):
            return os.path.abspath(c)
    raise FileNotFoundError("Could not find crons.yaml. Pass via CRONS_FILE environment variable.")
 def is_inside_container():
    return os.path.exists("/home/node/.openclaw") or os.environ.get("OPENCLAW_HOME") is not None
 def run_openclaw_cmd(args):
    if is_inside_container():
        cmd = ["openclaw"] + args
    else:
        namespace = os.environ.get("NAMESPACE", "openclaw")
        pod = os.environ.get("POD_NAME", "openclaw-0")
        container = os.environ.get("CONTAINER_NAME", "openclaw")
        cmd = ["kubectl", "exec", "-n", namespace, pod, "-c", container, "--", "openclaw"] + args
    res = subprocess.run(cmd, capture_output=True, text=True)
    if res.returncode != 0:
        raise RuntimeError(f"OpenClaw CLI command failed ({' '.join(cmd)}):\n{res.stderr}\n{res.stdout}")
    return res.stdout
 def list_existing_jobs():
    raw = run_openclaw_cmd(["cron", "list", "--json"])
    try:
        data = json.loads(raw)
        return data.get("jobs", [])
    except Exception as e:
        print(f"Warning: could not parse cron list json: {e}\nRaw output: {raw[:300]}", file=sys.stderr)
        return []
 def reconcile_jobs():
    file_path = find_crons_file()
    print(f"=== Syncing OpenClaw Crons-as-Code from {file_path} ===")
    with open(file_path, "r", encoding="utf-8") as f:
        spec = yaml.safe_load(f)
    declarations = spec.get("jobs", [])
    existing_jobs = list_existing_jobs()
    print(f"Found {len(declarations)} declared jobs in YAML, {len(existing_jobs)} active jobs on gateway.")
    for job in declarations:
        name = job.get("name")
        decl_key = job.get("declarationKey") or name
        desc = job.get("description", "")
        sched = job.get("schedule", {})
        # Match existing job by declarationKey or exact name
        match = next((j for j in existing_jobs if j.get("declarationKey") == decl_key or j.get("name") == name), None)
        if match:
            existing_id = match.get("id")
            print(f"Removing existing job '{name}' (ID {existing_id}) for idempotent recreation...")
            try:
                run_openclaw_cmd(["cron", "rm", existing_id])
            except Exception as e:
                print(f"Warning removing {existing_id}: {e}")
        # Build add command
        cmd = [
            "cron", "add",
            "--name", name,
            "--declaration-key", decl_key,
            "--description", desc,
        ]
        if sched.get("kind") == "every":
            cmd.extend(["--every", sched.get("every", "15m")])
        elif sched.get("kind") == "cron":
            cmd.extend(["--cron", sched.get("expr", "* * * * *")])
            if sched.get("tz"):
                cmd.extend(["--tz", sched.get("tz")])
        if job.get("session"):
            cmd.extend(["--session", job.get("session")])
        if job.get("delivery") == "none":
            cmd.append("--no-deliver")
        if job.get("command"):
            cmd.extend(["--command", job.get("command")])
        if job.get("agent"):
            cmd.extend(["--agent", job.get("agent")])
        if job.get("model"):
            cmd.extend(["--model", job.get("model")])
        if job.get("channel"):
            cmd.extend(["--channel", job.get("channel")])
        if job.get("to"):
            cmd.extend(["--to", job.get("to")])
        if job.get("threadId"):
            cmd.extend(["--thread-id", str(job.get("threadId"))])
        if job.get("announce"):
            cmd.append("--announce")
        if job.get("message"):
            cmd.extend(["--message", job.get("message")])
        print(f"Registering job '{name}'...")
        run_openclaw_cmd(cmd)
        print(f"Successfully registered '{name}'.")
    print("=== OpenClaw Crons-as-Code reconciliation complete! ===")
 if __name__ == "__main__":
    reconcile_jobs()
@@ -1,14 +1,16 @@
 #!/usr/bin/env bash
 # ==============================================================================
 # setup-compaction-cron.sh
-# Declaratively registers the Multi-Agent Nightly Session Compaction in OpenClaw.
+# Declaratively registers OpenClaw session maintenance automations:
-# Schedule: Every night at 04:45 Europe/Berlin (02:45 UTC) (cron: 45 4 * * *)
+# 1. Tracking Sliding Window (every 15m): Truncates mila_tracker & nutrition_tracker
-#
+#    to <= 8 events (~5 messages / 2 turns) via instant native gateway truncation.
-# Architecture:
+# 2. Nightly Deep Compaction (every night at 04:45 Europe/Berlin):
-# - Tier A: Daily Hard-Reset to 0 for koch (Topic 21), hebamme (Topic 22), shopping (Topic 115)
+#    - Pre-warms SQLite page cache on rotational storage
-#   (100% externalized state in DuckDB/JSONL; resets prevent cross-day hallucination)
+#    - Recovers wedged/quarantined sessions
-# - Tier B: Smart Compaction for long-running project agents (itguy, recherche, regensburg, fitness, doktor)
+#    - Prunes abandoned isolated cron sessions (>48h)
-# - WAL checkpoints and SQLite optimization without blocking full VACUUM
+#    - Deep-compacts conversational topics (koch, hebamme, shopping)
 #    - Smart-compacts active long-running sessions (itguy, recherche, etc.)
 #    - Flushes SQLite WAL journals and executes PRAGMA optimize
 # ==============================================================================
 set -euo pipefail
@@ -16,310 +18,62 @@ set -euo pipefail
 NAMESPACE="${NAMESPACE:-openclaw}"
 POD_NAME="${POD_NAME:-openclaw-0}"
 CONTAINER_NAME="${CONTAINER_NAME:-openclaw}"
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-JOB_NAME="nightly-session-compaction"
+echo "=== Registering Multi-Agent Session Maintenance in OpenClaw ($POD_NAME) ==="
 # 1. Install maintenance scripts from repo onto PVC
 echo "Syncing compact_tracking_sessions.py to pod..."
 kubectl exec -i -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- /bin/sh -c \
  'cat > /home/node/.openclaw/scripts/compact_tracking_sessions.py && chmod +x /home/node/.openclaw/scripts/compact_tracking_sessions.py' \
  < "$SCRIPT_DIR/scripts/compact_tracking_sessions.py"
 echo "Syncing compact_sessions.py to pod..."
 kubectl exec -i -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- /bin/sh -c \
  'cat > /home/node/.openclaw/scripts/compact_sessions.py && chmod +x /home/node/.openclaw/scripts/compact_sessions.py' \
  < "$SCRIPT_DIR/scripts/compact_sessions.py"
 # 2. Register / Update 15-Minute Tracking Sliding Window Automation
 TRACKING_JOB="tracking-session-sliding-window"
 echo "Checking existing OpenClaw Cron automation '$TRACKING_JOB'..."
 EXISTING_TRACKING_ID=$(kubectl exec -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- openclaw cron list --json 2>/dev/null | python3 -c 'import sys, json; data=json.load(sys.stdin); print(next((j["id"] for j in data.get("jobs", []) if j.get("declarationKey") == "'"$TRACKING_JOB"'"), ""))' 2>/dev/null || true)
 if [ -n "$EXISTING_TRACKING_ID" ]; then
  echo "Updating existing tracking sliding window automation '$EXISTING_TRACKING_ID' (every 15m)..."
  kubectl exec -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- openclaw cron edit "$EXISTING_TRACKING_ID" \
    --every "15m" \
    --command "python3 /home/node/.openclaw/scripts/compact_tracking_sessions.py"
 else
  echo "Registering new tracking sliding window automation '$TRACKING_JOB' (every 15m)..."
  kubectl exec -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- openclaw cron add \
    --name "Tracking Session Sliding Window" \
    --declaration-key "$TRACKING_JOB" \
    --description "Lightweight sliding-window truncation (max 8 events) for mila_tracker and nutrition_tracker" \
    --every "15m" \
    --session "isolated" \
    --no-deliver \
    --command "python3 /home/node/.openclaw/scripts/compact_tracking_sessions.py"
 fi
 # 3. Register / Update Nightly Deep Compaction Automation
 NIGHTLY_JOB="nightly-session-compaction"
 CRON_SCHEDULE="45 4 * * *"
 TIMEZONE="Europe/Berlin"
-echo "=== Registering Multi-Agent Nightly Session Maintenance in OpenClaw ($POD_NAME) ==="
+echo "Checking existing OpenClaw Cron automation '$NIGHTLY_JOB'..."
 EXISTING_NIGHTLY_ID=$(kubectl exec -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- openclaw cron list --json 2>/dev/null | python3 -c 'import sys, json; data=json.load(sys.stdin); print(next((j["id"] for j in data.get("jobs", []) if j.get("declarationKey") == "'"$NIGHTLY_JOB"'"), ""))' 2>/dev/null || true)
-# 1. Install or ensure python maintenance script is present on PVC
+if [ -n "$EXISTING_NIGHTLY_ID" ]; then
-echo "Ensuring /home/node/.openclaw/scripts/compact_sessions.py exists..."
+  echo "Updating existing nightly compaction automation '$EXISTING_NIGHTLY_ID' ($CRON_SCHEDULE @ $TIMEZONE)..."
-kubectl exec -i -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- /bin/sh -c 'cat << "EOF" > /home/node/.openclaw/scripts/compact_sessions.py
+  kubectl exec -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- openclaw cron edit "$EXISTING_NIGHTLY_ID" \
 #!/usr/bin/env python3
 """
 Nightly multi-agent session maintenance and compaction script for OpenClaw.
 1. Pre-warms OS page cache for SQLite databases on spinning disks.
 2. Recovers any wedged or locked sessions via recover_sessions.py.
 3. Prunes abandoned isolated cron sessions (>48h old) to prevent token/state bloat.
 4. Tier A Hard-Reset: Resets koch, hebamme, and shopping topics to 0 tokens (clean archive).
 5. Tier B Smart-Compaction: Compacts active sessions exceeding token thresholds (5s pacing).
 6. Checkpoints SQLite WAL journals across all agent databases to disk.
 7. Optimizes SQLite query planner without blocking full VACUUM.
 """
 import glob
 import json
 import os
 import sqlite3
 import subprocess
 import sys
 import time
 THRESHOLD_TOKENS = 20000
 THRESHOLD_TRANSCRIPT_BYTES = 300000
 THRESHOLD_EVENT_COUNT = 40
 CRON_MAX_AGE_HOURS = 48
 RPC_TIMEOUT_MS = 180000
 # Tier A: Event-logging agents whose state is 100% externalized (DuckDB / JSONL / Groceries DB).
 # Nightly reset to 0 prevents cross-day hallucination and eliminates LLM compaction token costs.
 TIER_A_RESET_TARGETS = [
    ("koch", "agent:koch:telegram:group:-1004326921510:topic:21"),
    ("hebamme", "agent:hebamme:telegram:group:-1004326921510:topic:22"),
    ("shopping", "agent:shopping:telegram:group:-1004326921510:topic:115"),
 ]
 def prewarm_page_cache():
    print("=== Pre-warming SQLite databases into OS page cache ===")
    t0 = time.time()
    try:
        subprocess.run(
            "cat /home/node/.openclaw/state/openclaw.sqlite /home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite > /dev/null 2>&1 || true",
            shell=True,
            timeout=90.0
        )
        print(f"Page cache pre-warmed in {time.time() - t0:.2f}s")
    except Exception as e:
        print(f"Page cache pre-warming warning: {e}")
 def prune_stale_cron_sessions():
    print(f"=== Pruning isolated cron sessions older than {CRON_MAX_AGE_HOURS}h ===")
    cutoff_ms = int(time.time() * 1000) - (CRON_MAX_AGE_HOURS * 3600 * 1000)
    total_pruned = 0
    total_tokens_reclaimed = 0
    for db in sorted(glob.glob("/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite")):
        agent = db.split("/")[5]
        try:
            conn = sqlite3.connect(db, timeout=30.0)
            conn.execute("PRAGMA foreign_keys = ON;")
            cursor = conn.cursor()
            cursor.execute("SELECT name FROM sqlite_master WHERE type=\"table\"")
            all_tables = set(r[0] for r in cursor.fetchall())
            cursor.execute("SELECT session_key, current_session_id, updated_at, entry_json FROM session_nodes WHERE session_key LIKE \"%:cron:%\"")
            stale = []
            for k, sid, up, ej in cursor.fetchall():
                if up and up < cutoff_ms:
                    tok = 0
                    if ej:
                        try:
                            tok = json.loads(ej).get("totalTokens", 0) or 0
                        except Exception:
                            pass
                    stale.append((k, sid, tok))
            if stale:
                tokens_reclaimed = sum(t[2] for t in stale)
                for k, sid, _ in stale:
                    for t in ["trajectory_runtime_events", "transcript_events", "transcript_event_identities", "session_transcript_active_events", "transcript_rewrite_watermarks", "session_transcript_index_state", "session_transcript_fts", "session_conversations"]:
                        if t in all_tables and sid:
                            cursor.execute(f"DELETE FROM {t} WHERE session_id = ?", (sid,))
                    for t in ["session_participants", "heartbeat_outcomes", "session_progress_cards", "board_widgets", "board_tabs"]:
                        if t in all_tables:
                            cursor.execute(f"DELETE FROM {t} WHERE session_key = ?", (k,))
                    if "memory_entry_origins" in all_tables:
                        cursor.execute("DELETE FROM memory_entry_origins WHERE session_key = ? OR session_id = ?", (k, sid or ""))
                    if "session_windows" in all_tables:
                        cursor.execute("DELETE FROM session_windows WHERE session_key = ? OR session_id = ?", (k, sid or ""))
                    cursor.execute("DELETE FROM session_nodes WHERE session_key = ?", (k,))
                conn.commit()
                total_pruned += len(stale)
                total_tokens_reclaimed += tokens_reclaimed
                print(f"  [{agent}] Pruned {len(stale)} dead cron sessions ({tokens_reclaimed} tokens reclaimed)")
            # Unconditionally resolve any dangling foreign key references across all tables
            while True:
                cursor.execute("PRAGMA foreign_key_check;")
                violations = cursor.fetchall()
                if not violations:
                    break
                for table, rowid, parent, fkid in violations:
                    cursor.execute(f"DELETE FROM {table} WHERE rowid = ?", (rowid,))
            conn.commit()
            conn.close()
        except Exception as e:
            print(f"  [{agent}] Pruning error: {e}")
    # Clear resolved quarantine entries if all databases are healthy
    try:
        q_path = "/home/node/.openclaw/state/openclaw-quarantine.sqlite"
        if os.path.exists(q_path):
            q_conn = sqlite3.connect(q_path)
            q_cur = q_conn.cursor()
            q_cur.execute("DELETE FROM quarantined_databases")
            q_conn.commit()
            q_conn.close()
    except Exception as e:
        print(f"Quarantine cleanup error: {e}")
    print(f"Cron pruning complete: {total_pruned} sessions pruned, {total_tokens_reclaimed} tokens reclaimed.")
 def reset_tier_a_sessions():
    print("=== Tier A: Daily Hard-Reset to 0 (koch, hebamme, shopping) ===")
    for agent, key in TIER_A_RESET_TARGETS:
        db_path = f"/home/node/.openclaw/agents/{agent}/agent/openclaw-agent.sqlite"
        if not os.path.exists(db_path):
            continue
        try:
            con = sqlite3.connect(db_path, timeout=10.0)
            row = con.execute("SELECT current_session_id FROM session_nodes WHERE session_key=?", (key,)).fetchone()
            con.close()
            if not row or not row[0]:
                print(f"  [Tier A] {agent} ({key}) already at 0 (no active session).")
                continue
            print(f"  [Tier A] Resetting {agent} ({key})...")
            r = subprocess.run(
                ["openclaw", "sessions", "delete", key, "--agent", agent, "--yes"],
                capture_output=True, text=True, timeout=60.0
            )
            if r.returncode == 0:
                print(f"    ✓ Reset success: {r.stdout.strip()}")
            else:
                print(f"    ✗ Reset error: {r.stderr.strip()}")
        except Exception as e:
            print(f"    ✗ Exception resetting {agent}: {e}")
        time.sleep(1)
 def get_session_metrics(agent, key, sid=None):
    db_path = f"/home/node/.openclaw/agents/{agent}/agent/openclaw-agent.sqlite"
    if not os.path.exists(db_path):
        return 0, 0
    try:
        con = sqlite3.connect(db_path, timeout=5.0)
        cur = con.cursor()
        if not sid:
            row = cur.execute("SELECT current_session_id FROM session_nodes WHERE session_key=?", (key,)).fetchone()
            sid = row[0] if row else None
        if not sid:
            con.close()
            return 0, 0
        ev_cnt, ev_bytes = cur.execute(
            "SELECT count(*), coalesce(sum(length(event_json)), 0) FROM transcript_events WHERE session_id=?", 
            (sid,)
        ).fetchone()
        con.close()
        return ev_cnt, ev_bytes
    except Exception:
        return 0, 0
 def compact_active_sessions():
    tier_a_keys = set(t[1] for t in TIER_A_RESET_TARGETS)
    print(f"=== Tier B: Running Multi-Agent Compaction (threshold: {THRESHOLD_TOKENS} tokens / {THRESHOLD_TRANSCRIPT_BYTES//1024}KB, LLM summarization) ===")
    res = subprocess.run(["openclaw", "sessions", "--all-agents", "--json"], capture_output=True, text=True)
    if res.returncode != 0:
        print(f"Failed to list sessions: {res.stderr}")
        return
    sessions = json.loads(res.stdout).get("sessions", [])
    compacted = 0
    skipped = 0
    for s in sessions:
        key = s.get("key", "")
        agent = s.get("agentId") or "main"
        tokens = s.get("totalTokens") or 0
        sid = s.get("sessionId")
        # Skip Tier A agents as they are handled via hard-reset
        if key in tier_a_keys:
            continue
        # Target main sessions and all telegram sessions (topics and direct)
        is_target = (
            key == "agent:main:main" or 
            ":telegram:" in key or
            (key.startswith("agent:") and key.endswith(":main"))
        )
        if is_target and not key.endswith(":heartbeat"):
            ev_cnt, ev_bytes = get_session_metrics(agent, key, sid)
            needs_compaction = (
                tokens >= THRESHOLD_TOKENS or
                ev_bytes >= THRESHOLD_TRANSCRIPT_BYTES or
                (tokens == 0 and ev_cnt >= THRESHOLD_EVENT_COUNT)
            )
            if needs_compaction:
                stat_str = f"{tokens} tokens" if tokens else f"{ev_bytes//1024}KB / {ev_cnt} events"
                print(f"Compacting {agent} ({stat_str}) -> {key}...")
                c_res = subprocess.run(
                    ["openclaw", "sessions", "compact", key, "--agent", agent, "--timeout", str(RPC_TIMEOUT_MS)],
                    capture_output=True, text=True
                )
                if c_res.returncode == 0:
                    print(f"  ✓ {c_res.stdout.strip()}")
                    compacted += 1
                elif "Already compacted" in c_res.stderr or "Already compacted" in c_res.stdout:
                    print(f"  ✓ Already compacted.")
                    skipped += 1
                else:
                    print(f"  ✗ {c_res.stderr.strip()}; retrying with --max-lines 80 fallback...")
                    fb_res = subprocess.run(
                        ["openclaw", "sessions", "compact", key, "--agent", agent, "--max-lines", "80", "--timeout", str(RPC_TIMEOUT_MS)],
                        capture_output=True, text=True
                    )
                    if fb_res.returncode == 0:
                        print(f"  ✓ (fallback) {fb_res.stdout.strip()}")
                        compacted += 1
                    else:
                        print(f"  ✗ Fallback failed: {fb_res.stderr.strip()}")
                time.sleep(5)  # 5s pause to avoid rotational HDD I/O saturation
            else:
                skipped += 1
    print(f"Compaction complete: {compacted} compacted, {skipped} skipped.")
 def checkpoint_wal_journals():
    print("=== Checkpointing SQLite WAL journals across all agent databases ===")
    dbs = ["/home/node/.openclaw/state/openclaw.sqlite"] + glob.glob("/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite")
    wal_freed = 0
    for db in dbs:
        wal = db + "-wal"
        if os.path.exists(wal):
            sz = os.path.getsize(wal)
            try:
                con = sqlite3.connect(db, timeout=30.0)
                con.execute("PRAGMA wal_checkpoint(TRUNCATE);")
                con.close()
                wal_freed += sz
            except Exception as e:
                print(f"  ✗ Error checkpointing {db}: {e}")
    print(f"WAL Checkpoint complete: {wal_freed / (1024*1024):.2f} MB merged to disk.")
 def vacuum_and_optimize():
    print("=== Running SQLite OPTIMIZE across all databases ===")
    dbs = ["/home/node/.openclaw/state/openclaw.sqlite"] + glob.glob("/home/node/.openclaw/agents/*/agent/openclaw-agent.sqlite")
    for db in dbs:
        try:
            con = sqlite3.connect(db, timeout=30.0)
            con.execute("PRAGMA optimize;")
            con.close()
        except Exception as e:
            print(f"  ✗ Error optimizing {db}: {e}")
    print("SQLite optimization complete.")
 def main():
    prewarm_page_cache()
    try:
        subprocess.run(["python3", "/home/node/.openclaw/scripts/recover_sessions.py"], check=False)
    except Exception:
        pass
    prune_stale_cron_sessions()
    reset_tier_a_sessions()
    compact_active_sessions()
    checkpoint_wal_journals()
    vacuum_and_optimize()
 if __name__ == "__main__":
    main()
 EOF
 chmod +x /home/node/.openclaw/scripts/compact_sessions.py
 '
 # 2. Register / Update the OpenClaw cron job
 echo "Checking existing OpenClaw Cron automation '$JOB_NAME'..."
 EXISTING_ID=$(kubectl exec -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- openclaw cron list --json 2>/dev/null | python3 -c 'import sys, json; data=json.load(sys.stdin); print(next((j["id"] for j in data.get("jobs", []) if j.get("declarationKey") == "'"$JOB_NAME"'"), ""))' 2>/dev/null || true)
 if [ -n "$EXISTING_ID" ]; then
  echo "Updating existing OpenClaw Cron automation '$EXISTING_ID' ($CRON_SCHEDULE @ $TIMEZONE)..."
  kubectl exec -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- openclaw cron edit "$EXISTING_ID" \
    --cron "$CRON_SCHEDULE" \
    --tz "$TIMEZONE" \
    --command "python3 /home/node/.openclaw/scripts/compact_sessions.py"
 else
-  echo "Registering new OpenClaw Cron automation '$JOB_NAME' ($CRON_SCHEDULE @ $TIMEZONE)..."
+  echo "Registering new nightly compaction automation '$NIGHTLY_JOB' ($CRON_SCHEDULE @ $TIMEZONE)..."
  kubectl exec -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- openclaw cron add \
    --name "Nightly Session Compaction" \
-    --declaration-key "$JOB_NAME" \
+    --declaration-key "$NIGHTLY_JOB" \
    --description "Nightly multi-agent session compaction and SQLite WAL checkpointing" \
    --cron "$CRON_SCHEDULE" \
    --tz "$TIMEZONE" \
@@ -328,7 +82,4 @@ else
    --command "python3 /home/node/.openclaw/scripts/compact_sessions.py"
 fi
-echo "=== Compaction Cron automation successfully registered/updated! ==="
+echo "=== All session maintenance automations successfully registered/updated! ==="
 if [ -n "$EXISTING_ID" ]; then
  kubectl exec -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- openclaw cron get "$EXISTING_ID" 2>/dev/null || true
 fi
@@ -35,13 +35,7 @@ Führe den nächtlichen Garmin Connect Sync durch.
 Vorgehen:
 1. Führe den Garmin-Sync-Befehl aus:
   uv run /home/node/mop-skills/mop-skills/skills/datastore/scripts/garmin_sync.py --days 2 --data-dir /home/node/.openclaw/wiki/main/data
-2. Aktualisiere die gerenderten Markdown-Ansichten:
+2. Finale Antwort:
   PYTHONPATH=/home/node/mop-skills/mop-skills/skills/datastore/scripts uv run /home/node/mop-skills/mop-skills/skills/datastore/scripts/render_views.py --data-dir /home/node/.openclaw/wiki/main/data --wiki-dir /home/node/.openclaw/wiki/main
 3. Aktualisiere das persönliche Health & Nutrition Dashboard (moritz.html):
   uv run /home/node/mop-skills/mop-skills/skills/datastore/scripts/update_moritz_website.py --data-dir /home/node/.openclaw/wiki/main/data
 4. Git Commit & Push im Knowledge Wiki:
   cd /home/node/.openclaw/wiki/main && git add data/garmin/ entities/nutrition-log/ public/ && git diff --staged --quiet || (git commit -m "chore(garmin): automated nightly mirror [skip ci]" && git push origin main)
 5. Finale Antwort:
   - Bei Erfolg: Gib exakt 'NO_REPLY' aus (intentional silence, kein Telegram-Spam in der Nacht).
   - Nur bei Authentifizierungsfehlern: Informiere kurz via Telegram (Thema #Sport), dass ein Garmin-Re-Auth nötig ist, oder starte den Re-Auth-Flow.
 EOF
@@ -54,7 +48,7 @@ kubectl exec -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- openclaw cron a
  --cron "$CRON_SCHEDULE" \
  --tz "$TIMEZONE" \
  --agent "fitness" \
-  --model "openrouter/deepseek/deepseek-v4.1-flash" \
+  --model "openrouter/deepseek/deepseek-v4.1-flash-1017" \
  --session "isolated" \
  --channel "telegram" \
  --to "$TELEGRAM_GROUP" \
@@ -48,7 +48,7 @@ kubectl exec -n "$NAMESPACE" "$POD_NAME" -c "$CONTAINER_NAME" -- openclaw cron a
  --cron "$CRON_SCHEDULE" \
  --tz "$TIMEZONE" \
  --agent "itguy" \
-  --model "openrouter/deepseek/deepseek-v4.1-flash" \
+  --model "openrouter/deepseek/deepseek-v4.1-flash-1017" \
  --session "isolated" \
  --channel "telegram" \
  --to "$TELEGRAM_GROUP" \
@@ -0,0 +1,13 @@
 # AGENTS.md — DuckDB Backend
 ## Purpose
 FastAPI HTTP backend executing in-memory DuckDB queries against Git-backed JSONL data in the Knowledge Wiki.
 ## Development & Testing
 ```bash
 # Run tests
 uv run --project projects/duckdb-backend pytest -v projects/duckdb-backend/tests
 # Run locally
 uv run --project projects/duckdb-backend uvicorn app.main:app --port 8000
 ```
@@ -0,0 +1,26 @@
 FROM python:3.12-slim
 # Install system dependencies (git for wiki sync)
 RUN apt-get update && apt-get install -y --no-install-recommends \
    git \
    ca-certificates \
    && rm -rf /var/lib/apt/lists/*
 # Install uv for fast dependency resolution
 COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
 WORKDIR /app
 # Install dependencies
 COPY pyproject.toml .
 RUN uv pip install --system --no-cache -r pyproject.toml
 # Copy application source
 COPY app/ ./app/
 ENV PYTHONUNBUFFERED=1
 ENV PORT=8000
 ENV HOST=0.0.0.0
 EXPOSE 8000
 CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
@@ -0,0 +1,26 @@
 # DuckDB Backend
 HTTP-based analytical and transactional backend for personal logging data stored in the Knowledge Wiki.
 Powered by Python 3.12, FastAPI, and in-memory DuckDB querying JSONL files directly.
 ## Architecture
 - **Single Source of Truth**: Knowledge Wiki (`/wiki` git repository with data in `/wiki/data/**/*.jsonl`).
 - **Engine**: In-memory DuckDB reading `sleep`, `nutrition`, `mila`, `entities`, and `garmin` partitions.
 - **Git Synchronization**:
  - Background periodic `git pull --rebase origin main` (every 60s).
  - Mutating operations (`POST /duckdb-api/v1/events`) append to typed JSONL partition files, sort them, commit, rebase, and push to origin main.
  - Conflicts trigger automatic rebase abort and flag `git_conflict: true` on `/status` and `/healthz`.
 ## Endpoints
 - `GET /duckdb-api/v1/mila/dashboard`: Curated aggregated dashboard for Mila (sleep, wake timer, feedings, diapers, WHO percentiles).
 - `GET /duckdb-api/v1/moritz/dashboard`: Curated aggregated dashboard for Moritz (today's intake, yesterday's 24h deficit/surplus, Garmin recovery & sleep, 7d/30d trends).
 - `POST /duckdb-api/v1/query`: Generic read-only SQL queries against DuckDB tables and views.
 - `POST /duckdb-api/v1/events`: Record new events (sleep, nutrition, diaper, feeding, growth).
 - `POST /duckdb-api/v1/events/stop`: Close active open sleep session or interval.
 - `DELETE /duckdb-api/v1/events/{id}`: Soft-delete event.
 - `POST /duckdb-api/v1/entities`: Upsert entities (`foods`, `recipes`, `places`, `people`).
 - `GET /duckdb-api/v1/healthz`: Liveness and readiness probe.
 - `GET /duckdb-api/v1/status`: Git synchronization status and table row counts.
 - `POST /duckdb-api/v1/git/sync`: Manual pull or webhook sync trigger.
@@ -0,0 +1 @@
 # app package
@@ -0,0 +1,46 @@
 from __future__ import annotations
 import os
 from pathlib import Path
 def find_default_wiki_dir() -> Path:
    env_wiki = os.environ.get("WIKI_DIR") or os.environ.get("GIT_REPO_DIR")
    if env_wiki:
        return Path(env_wiki).resolve()
    candidates = [
        Path("/wiki"),
        Path.cwd() / "knowledge-wiki",
        Path.cwd().parent.parent / "knowledge-wiki",
        Path("/Users/moritz/src/infrapuzzle/knowledge-wiki"),
        Path.home() / "src" / "infrapuzzle" / "knowledge-wiki",
        Path("/home/node/.openclaw/wiki/main"),
    ]
    for c in candidates:
        if c.is_dir() and (c / "data").is_dir():
            return c.resolve()
    return (Path.cwd() / "knowledge-wiki").resolve()
 WIKI_DIR = find_default_wiki_dir()
 DATA_DIR = Path(
    os.environ.get("DATA_DIR")
    or os.environ.get("DUCKDB_DATA_DIR")
    or (WIKI_DIR / "data")
 ).resolve()
 GIT_REPO_URL = os.environ.get(
    "GIT_REPO_URL",
    os.environ.get("GIT_REMOTE_URL", "https://git.moritzgraf.de/moritz/knowledge-wiki.git"),
 )
 GIT_USERNAME = os.environ.get("GIT_SYNC_USERNAME", "")
 GIT_PASSWORD = os.environ.get("GIT_SYNC_PASSWORD", os.environ.get("WIKI_SYNC_TOKEN", ""))
 GIT_BRANCH = os.environ.get("GIT_BRANCH", "main")
 GIT_SYNC_INTERVAL_SECONDS = int(os.environ.get("GIT_SYNC_INTERVAL_SECONDS", "60"))
 AUTO_GIT_SYNC = os.environ.get("AUTO_GIT_SYNC", "true").lower() in ("1", "true", "yes")
 GIT_AUTHOR_NAME = os.environ.get("GIT_AUTHOR_NAME", "DuckDB Backend")
 GIT_AUTHOR_EMAIL = os.environ.get("GIT_AUTHOR_EMAIL", "duckdb-backend@haumdaucher.de")
 PORT = int(os.environ.get("PORT", "8000"))
 HOST = os.environ.get("HOST", "0.0.0.0")
@@ -0,0 +1,326 @@
 from __future__ import annotations
 import asyncio
 import datetime
 import logging
 import os
 import subprocess
 import threading
 import urllib.parse
 from pathlib import Path
 from typing import Callable, Optional
 from app.config import (
    AUTO_GIT_SYNC,
    GIT_AUTHOR_EMAIL,
    GIT_AUTHOR_NAME,
    GIT_BRANCH,
    GIT_PASSWORD,
    GIT_REPO_URL,
    GIT_SYNC_INTERVAL_SECONDS,
    GIT_USERNAME,
    WIKI_DIR,
 )
 logger = logging.getLogger("duckdb_backend.git_sync")
 class GitSyncManager:
    def __init__(self, wiki_dir: Optional[Path] = None, on_data_pulled: Optional[Callable[[], None]] = None):
        self.wiki_dir = wiki_dir or WIKI_DIR
        self.on_data_pulled = on_data_pulled
        self._lock = threading.Lock()
        self.status = "ok"
        self.is_conflict = False
        self.last_sync_time: Optional[str] = None
        self.last_commit_hash: Optional[str] = None
        self.last_error: Optional[str] = None
        self._bg_task: Optional[asyncio.Task] = None
        self._stop_event = asyncio.Event()
    def _configure_git_client(self):
        """Configures git client with safe.directory and author identity."""
        try:
            subprocess.run(["git", "config", "--global", "http.sslVerify", "false"], check=False)
            subprocess.run(["git", "config", "--global", "--add", "safe.directory", "*"], check=False)
            if (self.wiki_dir / ".git").exists():
                subprocess.run(["git", "-C", str(self.wiki_dir), "config", "user.name", GIT_AUTHOR_NAME], check=False)
                subprocess.run(["git", "-C", str(self.wiki_dir), "config", "user.email", GIT_AUTHOR_EMAIL], check=False)
        except Exception as e:
            logger.warning(f"Failed to configure git client options: {e}")
    def get_auth_repo_url(self) -> str:
        if GIT_USERNAME and GIT_PASSWORD and "://" in GIT_REPO_URL:
            proto, rest = GIT_REPO_URL.split("://", 1)
            # Remove existing credentials in URL if any
            if "@" in rest:
                rest = rest.split("@", 1)[1]
            user_enc = urllib.parse.quote(GIT_USERNAME, safe="")
            pass_enc = urllib.parse.quote(GIT_PASSWORD, safe="")
            return f"{proto}://{user_enc}:{pass_enc}@{rest}"
        return GIT_REPO_URL
    def ensure_repo(self) -> bool:
        """Ensures repository exists and is initialized."""
        with self._lock:
            self._configure_git_client()
            if (self.wiki_dir / ".git").exists():
                try:
                    res = subprocess.run(
                        ["git", "-C", str(self.wiki_dir), "rev-parse", "--short", "HEAD"],
                        capture_output=True,
                        text=True,
                        check=False,
                    )
                    if res.returncode == 0:
                        self.last_commit_hash = res.stdout.strip()
                    return True
                except Exception as e:
                    logger.warning(f"Failed to check git rev: {e}")
                    return True
            if not GIT_REPO_URL:
                logger.info(f"Wiki directory {self.wiki_dir} is not a git repo, but no GIT_REPO_URL configured.")
                return False
            logger.info(f"Initializing repository {GIT_REPO_URL} in {self.wiki_dir}...")
            self.wiki_dir.mkdir(parents=True, exist_ok=True)
            auth_url = self.get_auth_repo_url()
            try:
                # Use git init + remote + fetch + checkout to safely support non-empty directories (e.g. lost+found on PVC)
                subprocess.run(["git", "-C", str(self.wiki_dir), "init"], capture_output=True, check=False)
                self._configure_git_client()
                subprocess.run(
                    ["git", "-C", str(self.wiki_dir), "remote", "add", "origin", auth_url],
                    capture_output=True,
                    check=False,
                )
                subprocess.run(
                    ["git", "-C", str(self.wiki_dir), "remote", "set-url", "origin", auth_url],
                    capture_output=True,
                    check=False,
                )
                res = subprocess.run(
                    ["git", "-C", str(self.wiki_dir), "fetch", "origin", GIT_BRANCH],
                    capture_output=True,
                    text=True,
                    check=False,
                    timeout=60,
                )
                if res.returncode == 0:
                    if (self.wiki_dir / ".git" / "shallow").exists():
                        subprocess.run(
                            ["git", "-C", str(self.wiki_dir), "fetch", "--unshallow", "origin", GIT_BRANCH],
                            capture_output=True,
                            check=False,
                        )
                    checkout_res = subprocess.run(
                        ["git", "-C", str(self.wiki_dir), "checkout", "-f", "-B", GIT_BRANCH, f"origin/{GIT_BRANCH}"],
                        capture_output=True,
                        text=True,
                        check=False,
                    )
                    if checkout_res.returncode == 0:
                        logger.info("Successfully initialized and checked out wiki repository.")
                        self.status = "ok"
                        self.is_conflict = False
                        self.last_sync_time = datetime.datetime.now(datetime.timezone.utc).isoformat()
                        return True
                    else:
                        self.status = "error"
                        self.last_error = f"Checkout failed: {checkout_res.stderr.strip()}"
                        logger.error(self.last_error)
                        return False
                else:
                    self.status = "error"
                    self.last_error = f"Fetch failed: {res.stderr.strip()}"
                    logger.error(self.last_error)
                    return False
            except Exception as e:
                self.status = "error"
                self.last_error = f"Clone exception: {e}"
                logger.error(self.last_error)
                return False
    def pull_rebase(self) -> bool:
        """Pulls latest changes via rebase. Handles conflicts cleanly."""
        if not (self.wiki_dir / ".git").exists():
            return False
        with self._lock:
            try:
                # Update remote url with credentials if provided
                auth_url = self.get_auth_repo_url()
                subprocess.run(
                    ["git", "-C", str(self.wiki_dir), "remote", "set-url", "origin", auth_url],
                    capture_output=True,
                    check=False,
                )
                # Fetch and rebase with autostash
                res = subprocess.run(
                    ["git", "-C", str(self.wiki_dir), "pull", "--rebase", "--autostash", "origin", GIT_BRANCH],
                    capture_output=True,
                    text=True,
                    check=False,
                    timeout=30,
                )
                if res.returncode == 0:
                    self.status = "ok"
                    self.is_conflict = False
                    self.last_error = None
                    self.last_sync_time = datetime.datetime.now(datetime.timezone.utc).isoformat()
                    # Update commit hash
                    rev = subprocess.run(
                        ["git", "-C", str(self.wiki_dir), "rev-parse", "--short", "HEAD"],
                        capture_output=True,
                        text=True,
                        check=False,
                    )
                    if rev.returncode == 0:
                        self.last_commit_hash = rev.stdout.strip()
                    if self.on_data_pulled:
                        try:
                            self.on_data_pulled()
                        except Exception as ex:
                            logger.error(f"Error in on_data_pulled callback: {ex}")
                    return True
                else:
                    # Check if conflict occurred
                    stderr = res.stderr or res.stdout
                    logger.warning(f"Git pull --rebase failed: {stderr}")
                    # Abort any in-progress rebase to keep working tree stable
                    subprocess.run(
                        ["git", "-C", str(self.wiki_dir), "rebase", "--abort"],
                        capture_output=True,
                        check=False,
                    )
                    self.is_conflict = True
                    self.status = "conflict"
                    self.last_error = f"Rebase conflict: {stderr.strip()}"
                    return False
            except Exception as e:
                self.status = "error"
                self.last_error = f"Pull error: {e}"
                logger.error(self.last_error)
                return False
    def commit_and_push(self, commit_msg: str) -> bool:
        """Stages data/, commits with descriptive message, rebases and pushes."""
        if not (self.wiki_dir / ".git").exists():
            return False
        with self._lock:
            try:
                self._configure_git_client()
                data_rel = "data"
                subprocess.run(
                    ["git", "-C", str(self.wiki_dir), "add", data_rel],
                    capture_output=True,
                    check=False,
                )
                commit_res = subprocess.run(
                    ["git", "-C", str(self.wiki_dir), "commit", "-m", f"{commit_msg} [skip ci]"],
                    capture_output=True,
                    text=True,
                    check=False,
                )
                if commit_res.returncode != 0:
                    # Nothing to commit or already committed
                    logger.debug(f"Commit returncode {commit_res.returncode}: {commit_res.stdout.strip()}")
                    return True
                # Pull rebase with autostash before push
                auth_url = self.get_auth_repo_url()
                subprocess.run(
                    ["git", "-C", str(self.wiki_dir), "remote", "set-url", "origin", auth_url],
                    capture_output=True,
                    check=False,
                )
                rebase_res = subprocess.run(
                    ["git", "-C", str(self.wiki_dir), "pull", "--rebase", "--autostash", "origin", GIT_BRANCH],
                    capture_output=True,
                    text=True,
                    check=False,
                    timeout=30,
                )
                if rebase_res.returncode != 0:
                    stderr = rebase_res.stderr or rebase_res.stdout
                    logger.warning(f"Rebase failed during commit_and_push: {stderr}")
                    subprocess.run(
                        ["git", "-C", str(self.wiki_dir), "rebase", "--abort"],
                        capture_output=True,
                        check=False,
                    )
                    self.is_conflict = True
                    self.status = "conflict"
                    self.last_error = f"Rebase conflict on push: {stderr.strip()}"
                    return False
                # Push to remote
                push_res = subprocess.run(
                    ["git", "-C", str(self.wiki_dir), "push", "origin", GIT_BRANCH],
                    capture_output=True,
                    text=True,
                    check=False,
                    timeout=30,
                )
                if push_res.returncode == 0:
                    self.status = "ok"
                    self.is_conflict = False
                    self.last_error = None
                    self.last_sync_time = datetime.datetime.now(datetime.timezone.utc).isoformat()
                    rev = subprocess.run(
                        ["git", "-C", str(self.wiki_dir), "rev-parse", "--short", "HEAD"],
                        capture_output=True,
                        text=True,
                        check=False,
                    )
                    if rev.returncode == 0:
                        self.last_commit_hash = rev.stdout.strip()
                    return True
                else:
                    self.status = "error"
                    self.last_error = f"Push error: {push_res.stderr.strip()}"
                    logger.error(self.last_error)
                    return False
            except Exception as e:
                self.status = "error"
                self.last_error = f"Commit/push error: {e}"
                logger.error(self.last_error)
                return False
    async def start_periodic_sync(self):
        """Starts background periodic git pull loop."""
        if not AUTO_GIT_SYNC:
            logger.info("Automatic git sync is disabled by configuration.")
            return
        self._stop_event.clear()
        async def _loop():
            logger.info(f"Starting periodic git sync every {GIT_SYNC_INTERVAL_SECONDS}s")
            while not self._stop_event.is_set():
                try:
                    await asyncio.to_thread(self.pull_rebase)
                except Exception as ex:
                    logger.error(f"Error during periodic git pull: {ex}")
                try:
                    await asyncio.wait_for(self._stop_event.wait(), timeout=GIT_SYNC_INTERVAL_SECONDS)
                except asyncio.TimeoutError:
                    pass
        self._bg_task = asyncio.create_task(_loop())
    async def stop_periodic_sync(self):
        """Stops background sync loop."""
        self._stop_event.set()
        if self._bg_task:
            self._bg_task.cancel()
            try:
                await self._bg_task
            except asyncio.CancelledError:
                pass
            self._bg_task = None
@@ -0,0 +1,70 @@
 from __future__ import annotations
 import logging
 from contextlib import asynccontextmanager
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from app.config import DATA_DIR, WIKI_DIR
 from app.engine import DuckDBEngine
 from app.git_sync import GitSyncManager
 from app.routes.dashboard import router as dashboard_router
 from app.routes.entities import router as entities_router
 from app.routes.events import router as events_router
 from app.routes.query import router as query_router
 from app.routes.system import router as system_router
 logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(name)s: %(message)s")
 logger = logging.getLogger("duckdb_backend")
@asynccontextmanager
 async def lifespan(app: FastAPI):
    logger.info("Initializing DuckDB Backend...")
    if getattr(app.state, "git_sync", None) is None or getattr(app.state, "engine", None) is None:
        git_sync = GitSyncManager(
            wiki_dir=WIKI_DIR,
            on_data_pulled=lambda: app.state.engine.reload_all() if hasattr(app.state, "engine") else None,
        )
        git_sync.ensure_repo()
        app.state.git_sync = git_sync
        engine = DuckDBEngine(data_dir=DATA_DIR, git_sync_manager=git_sync)
        app.state.engine = engine
        await git_sync.start_periodic_sync()
        logger.info("DuckDB Backend is ready to serve queries.")
        try:
            yield
        finally:
            logger.info("Shutting down DuckDB Backend...")
            await git_sync.stop_periodic_sync()
    else:
        yield
 app = FastAPI(
    title="DuckDB Backend for Knowledge Wiki",
    version="1.0.0",
    description="HTTP-based analytical and transactional backend for personal logging data powered by DuckDB",
    lifespan=lifespan,
 )
 app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
 )
 # API v1 prefix
 v1_router = FastAPI()
 app.include_router(dashboard_router, prefix="/duckdb-api/v1")
 app.include_router(query_router, prefix="/duckdb-api/v1")
 app.include_router(events_router, prefix="/duckdb-api/v1")
 app.include_router(entities_router, prefix="/duckdb-api/v1")
 app.include_router(system_router, prefix="/duckdb-api/v1")
 # Direct root health probes for Kubernetes
 app.include_router(system_router)
@@ -0,0 +1,69 @@
 from __future__ import annotations
 from typing import Any, Dict, List, Optional
 from pydantic import BaseModel, Field, model_validator
 class QueryRequest(BaseModel):
    query: str = Field(..., description="Read-only SQL query to execute in DuckDB")
    params: Optional[List[Any]] = Field(default=None, description="Positional query parameters")
 class QueryResponse(BaseModel):
    columns: List[str]
    rows: List[Dict[str, Any]]
    count: int
    execution_time_ms: float
 class EventCreateRequest(BaseModel):
    kind: str = Field(..., description="Event kind, e.g. sleep.session, nutrition.intake, diaper.change, feeding.bottle, growth.measurement")
    subject: str = Field(..., description="Event subject, e.g. mila or moritz")
    payload: Dict[str, Any] = Field(default_factory=dict, description="Event-specific payload")
    actor: Optional[str] = Field(default="web-app", description="Actor who logged the event")
    date: Optional[str] = Field(default=None, description="Explicit log date override YYYY-MM-DD")
    start: Optional[str] = Field(default=None, description="ISO-8601 start timestamp")
    end: Optional[str] = Field(default=None, description="ISO-8601 end timestamp (optional)")
    since: Optional[str] = Field(default=None, description="Relative start duration like '15m', '1h'")
    estimated: bool = Field(default=False, description="Whether intake is estimated")
    meal: Optional[str] = Field(default=None, description="Meal category, e.g. fruehstueck, mittagessen, abendessen, snack")
    note: Optional[str] = Field(default=None, description="Free-text note")
    source_ref: Optional[str] = Field(default=None, description="Source reference")
    allow_duplicate: bool = Field(default=False, description="Allow event within 15min of duplicate")
 class EventStopRequest(BaseModel):
    kind: str = Field(default="sleep.session", description="Event kind to stop")
    subject: str = Field(..., description="Event subject, e.g. mila")
    end_time: Optional[str] = Field(default=None, description="ISO-8601 end timestamp")
    since: Optional[str] = Field(default=None, description="Relative end duration like '5m'")
    event_id: Optional[str] = Field(default=None, description="Specific event ID to close")
    actor: Optional[str] = Field(default="web-app", description="Actor who stopped the event")
 class EntityPutRequest(BaseModel):
    collection: str = Field(..., description="Target collection: foods, recipes, places, people")
    record: Dict[str, Any] = Field(..., description="Entity record with 'id'")
 class GarminSyncRequest(BaseModel):
    daily: List[Dict[str, Any]] = Field(default_factory=list, description="Garmin daily summary records")
    sleep: List[Dict[str, Any]] = Field(default_factory=list, description="Garmin sleep records")
    activities: List[Dict[str, Any]] = Field(default_factory=list, description="Garmin activity records")
    daily_summary: Optional[Dict[str, Any]] = None
    sleep_data: Optional[Dict[str, Any]] = None
    @model_validator(mode="before")
    @classmethod
    def normalize_aliases(cls, data: Any) -> Any:
        if isinstance(data, dict):
            # Normalize daily_summary dict to daily list if daily is missing/empty
            if "daily_summary" in data and data["daily_summary"] and not data.get("daily"):
                data["daily"] = [data["daily_summary"]]
            # Normalize sleep_data dict to sleep list if sleep is missing/empty
            if "sleep_data" in data and data["sleep_data"] and not data.get("sleep"):
                data["sleep"] = [data["sleep_data"]]
        return data
 class StatusResponse(BaseModel):
    status: str
    git_conflict: bool
    last_sync_time: Optional[str]
    last_commit_hash: Optional[str]
    last_error: Optional[str]
    data_dir: str
    table_counts: Dict[str, int]
@@ -0,0 +1 @@
 # routes package
@@ -0,0 +1,68 @@
 from __future__ import annotations
 from typing import Any, Dict, Optional
 from fastapi import APIRouter, Depends, HTTPException, Query, Request
 from app.engine import DuckDBEngine
 router = APIRouter(tags=["Dashboards"])
 def get_engine(request: Request) -> DuckDBEngine:
    return request.app.state.engine
@router.get("/mila/dashboard")
 async def get_mila_dashboard(
    as_of: Optional[str] = Query(default=None, description="Optional target date YYYY-MM-DD"),
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    try:
        return engine.get_mila_dashboard(as_of_date=as_of)
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@router.get("/moritz/dashboard")
 async def get_moritz_dashboard(
    as_of: Optional[str] = Query(default=None, description="Optional target date YYYY-MM-DD"),
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    try:
        return engine.get_moritz_dashboard(as_of_date=as_of)
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@router.get("/mila/day/{date}")
 async def get_mila_day_detail(
    date: str,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    try:
        return engine.get_mila_day_detail(target_date=date)
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@router.get("/moritz/day/{date}")
 async def get_moritz_day_detail(
    date: str,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    try:
        return engine.get_moritz_day_detail(target_date=date)
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@router.get("/summary/{subject}")
 async def get_summary(
    subject: str,
    date: Optional[str] = Query(default=None, description="Target date YYYY-MM-DD"),
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    try:
        return engine.get_summary(subject=subject, date_str=date)
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@@ -0,0 +1,51 @@
 from typing import Any, Dict, List, Optional
 from fastapi import APIRouter, Depends, HTTPException, Query, Request
 from app.engine import DuckDBEngine
 from app.models import EntityPutRequest
 router = APIRouter(tags=["Entities"])
 def get_engine(request: Request) -> DuckDBEngine:
    return request.app.state.engine
@router.post("/entities")
 async def put_entity(
    req: EntityPutRequest,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    try:
        return engine.put_entity(req)
    except ValueError as ve:
        raise HTTPException(status_code=400, detail=str(ve))
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@router.get("/entities/{collection}")
 async def list_entities(
    collection: str,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> List[Dict[str, Any]]:
    try:
        return engine.list_entities(collection=collection)
    except ValueError as ve:
        raise HTTPException(status_code=400, detail=str(ve))
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@router.get("/places/near")
 async def find_places_near(
    lat: float = Query(..., description="Latitude"),
    lon: float = Query(..., description="Longitude"),
    radius_m: float = Query(default=1000.0, description="Radius in meters"),
    category: Optional[str] = Query(default=None, description="Category filter"),
    engine: DuckDBEngine = Depends(get_engine),
 ) -> List[Dict[str, Any]]:
    try:
        return engine.find_places_near(lat=lat, lon=lon, radius_m=radius_m, category=category)
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@@ -0,0 +1,65 @@
 from __future__ import annotations
 from typing import Any, Dict
 from fastapi import APIRouter, Depends, HTTPException, Request
 from app.engine import DuckDBEngine
 from app.models import EventCreateRequest, EventStopRequest, GarminSyncRequest
 router = APIRouter(tags=["Events"])
 def get_engine(request: Request) -> DuckDBEngine:
    return request.app.state.engine
@router.post("/events")
 async def add_event(
    req: EventCreateRequest,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    try:
        return engine.add_event(req)
    except ValueError as ve:
        raise HTTPException(status_code=400, detail=str(ve))
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@router.post("/events/stop")
 async def stop_event(
    req: EventStopRequest,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    try:
        return engine.stop_event(req)
    except ValueError as ve:
        raise HTTPException(status_code=400, detail=str(ve))
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@router.delete("/events/{event_id}")
 async def delete_event(
    event_id: str,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    try:
        return engine.delete_event(event_id)
    except ValueError as ve:
        raise HTTPException(status_code=404, detail=str(ve))
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@router.post("/garmin/sync")
 async def sync_garmin(
    req: GarminSyncRequest,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    try:
        return engine.sync_garmin(req)
    except ValueError as ve:
        raise HTTPException(status_code=400, detail=str(ve))
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@@ -0,0 +1,35 @@
 from __future__ import annotations
 import time
 from fastapi import APIRouter, Depends, HTTPException, Request
 from app.engine import DuckDBEngine
 from app.models import QueryRequest, QueryResponse
 router = APIRouter(tags=["Generic Queries"])
 def get_engine(request: Request) -> DuckDBEngine:
    return request.app.state.engine
@router.post("/query", response_model=QueryResponse)
 async def execute_query(
    req: QueryRequest,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> QueryResponse:
    t0 = time.perf_counter()
    try:
        rows = engine.query(req.query, req.params)
        duration_ms = round((time.perf_counter() - t0) * 1000, 2)
        cols = list(rows[0].keys()) if rows else []
        return QueryResponse(
            columns=cols,
            rows=rows,
            count=len(rows),
            execution_time_ms=duration_ms,
        )
    except ValueError as ve:
        raise HTTPException(status_code=400, detail=str(ve))
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@@ -0,0 +1,77 @@
 from __future__ import annotations
 from typing import Any, Dict
 from fastapi import APIRouter, Depends, HTTPException, Request
 from app.config import DATA_DIR
 from app.engine import DuckDBEngine
 from app.git_sync import GitSyncManager
 from app.models import StatusResponse
 router = APIRouter(tags=["System"])
 def get_engine(request: Request) -> DuckDBEngine:
    return request.app.state.engine
 def get_git_sync(request: Request) -> Optional[GitSyncManager]:
    return getattr(request.app.state, "git_sync", None)
@router.get("/healthz")
 async def healthz(
    request: Request,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    git_sync: Optional[GitSyncManager] = get_git_sync(request)
    conflict = git_sync.is_conflict if git_sync else False
    status_str = "conflict" if conflict else "ok"
    return {
        "status": status_str,
        "conflict": conflict,
        "engine_ready": True,
    }
@router.get("/status", response_model=StatusResponse)
 async def status(
    request: Request,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> StatusResponse:
    git_sync: Optional[GitSyncManager] = get_git_sync(request)
    counts = engine.get_table_counts()
    return StatusResponse(
        status=git_sync.status if git_sync else "ok",
        git_conflict=git_sync.is_conflict if git_sync else False,
        last_sync_time=git_sync.last_sync_time if git_sync else None,
        last_commit_hash=git_sync.last_commit_hash if git_sync else None,
        last_error=git_sync.last_error if git_sync else None,
        data_dir=str(engine.data_dir),
        table_counts=counts,
    )
@router.post("/git/sync")
 async def trigger_sync(
    request: Request,
    engine: DuckDBEngine = Depends(get_engine),
 ) -> Dict[str, Any]:
    git_sync: Optional[GitSyncManager] = get_git_sync(request)
    if not git_sync:
        raise HTTPException(status_code=400, detail="Git sync is not configured")
    success = git_sync.pull_rebase()
    if success:
        engine.reload_all()
        return {
            "status": "ok",
            "message": "Git pull --rebase completed and DuckDB reloaded.",
            "commit": git_sync.last_commit_hash,
        }
    else:
        return {
            "status": git_sync.status,
            "conflict": git_sync.is_conflict,
            "error": git_sync.last_error,
        }
@@ -0,0 +1,128 @@
 from __future__ import annotations
 import math
 from typing import Any, Dict, List, Optional, Tuple
 WHO_GIRLS_WEIGHT = [
    {"month": 0, "L": 0.3809, "M": 3.2322, "S": 0.14171, "p3": 2.4, "p50": 3.2, "p97": 4.2},
    {"month": 1, "L": 0.1714, "M": 4.1873, "S": 0.13724, "p3": 3.2, "p50": 4.2, "p97": 5.4},
    {"month": 2, "L": 0.0962, "M": 5.1282, "S": 0.13000, "p3": 4.0, "p50": 5.1, "p97": 6.5},
    {"month": 3, "L": 0.0402, "M": 5.8458, "S": 0.12619, "p3": 4.6, "p50": 5.8, "p97": 7.4},
    {"month": 4, "L": -0.0050, "M": 6.4237, "S": 0.12402, "p3": 5.1, "p50": 6.4, "p97": 8.1},
    {"month": 5, "L": -0.0430, "M": 6.8985, "S": 0.12274, "p3": 5.5, "p50": 6.9, "p97": 8.7},
    {"month": 6, "L": -0.0756, "M": 7.2970, "S": 0.12204, "p3": 5.8, "p50": 7.3, "p97": 9.2},
    {"month": 7, "L": -0.1039, "M": 7.6422, "S": 0.12178, "p3": 6.1, "p50": 7.6, "p97": 9.6},
    {"month": 8, "L": -0.1288, "M": 7.9487, "S": 0.12181, "p3": 6.3, "p50": 7.9, "p97": 10.0},
    {"month": 9, "L": -0.1507, "M": 8.2254, "S": 0.12199, "p3": 6.6, "p50": 8.2, "p97": 10.4},
    {"month": 10, "L": -0.1700, "M": 8.4800, "S": 0.12223, "p3": 6.8, "p50": 8.5, "p97": 10.7},
    {"month": 11, "L": -0.1872, "M": 8.7192, "S": 0.12247, "p3": 7.0, "p50": 8.7, "p97": 11.0},
    {"month": 12, "L": -0.2024, "M": 8.9481, "S": 0.12268, "p3": 7.1, "p50": 8.9, "p97": 11.3},
    {"month": 13, "L": -0.2158, "M": 9.1699, "S": 0.12283, "p3": 7.3, "p50": 9.2, "p97": 11.6},
    {"month": 14, "L": -0.2278, "M": 9.3870, "S": 0.12294, "p3": 7.5, "p50": 9.4, "p97": 11.9},
    {"month": 15, "L": -0.2384, "M": 9.6008, "S": 0.12299, "p3": 7.7, "p50": 9.6, "p97": 12.2},
    {"month": 16, "L": -0.2478, "M": 9.8124, "S": 0.12303, "p3": 7.8, "p50": 9.8, "p97": 12.5},
    {"month": 17, "L": -0.2562, "M": 10.0226, "S": 0.12306, "p3": 8.0, "p50": 10.0, "p97": 12.7},
    {"month": 18, "L": -0.2637, "M": 10.2315, "S": 0.12309, "p3": 8.2, "p50": 10.2, "p97": 13.0},
    {"month": 19, "L": -0.2703, "M": 10.4393, "S": 0.12315, "p3": 8.3, "p50": 10.4, "p97": 13.3},
    {"month": 20, "L": -0.2762, "M": 10.6464, "S": 0.12323, "p3": 8.5, "p50": 10.6, "p97": 13.5},
    {"month": 21, "L": -0.2815, "M": 10.8534, "S": 0.12335, "p3": 8.7, "p50": 10.9, "p97": 13.8},
    {"month": 22, "L": -0.2862, "M": 11.0608, "S": 0.12350, "p3": 8.8, "p50": 11.1, "p97": 14.1},
    {"month": 23, "L": -0.2903, "M": 11.2688, "S": 0.12369, "p3": 9.0, "p50": 11.3, "p97": 14.3},
    {"month": 24, "L": -0.2941, "M": 11.4775, "S": 0.12390, "p3": 9.2, "p50": 11.5, "p97": 14.6},
 ]
 WHO_GIRLS_HEIGHT = [
    {"month": 0, "L": 1.0, "M": 49.1477, "S": 0.03790, "p3": 45.6, "p50": 49.1, "p97": 52.7},
    {"month": 1, "L": 1.0, "M": 53.6872, "S": 0.03640, "p3": 50.0, "p50": 53.7, "p97": 57.4},
    {"month": 2, "L": 1.0, "M": 57.0673, "S": 0.03568, "p3": 53.2, "p50": 57.1, "p97": 60.9},
    {"month": 3, "L": 1.0, "M": 59.8029, "S": 0.03520, "p3": 55.8, "p50": 59.8, "p97": 63.8},
    {"month": 4, "L": 1.0, "M": 62.0899, "S": 0.03486, "p3": 58.0, "p50": 62.1, "p97": 66.2},
    {"month": 5, "L": 1.0, "M": 64.0301, "S": 0.03463, "p3": 59.9, "p50": 64.0, "p97": 68.2},
    {"month": 6, "L": 1.0, "M": 65.7311, "S": 0.03448, "p3": 61.5, "p50": 65.7, "p97": 70.0},
    {"month": 7, "L": 1.0, "M": 67.2873, "S": 0.03441, "p3": 62.9, "p50": 67.3, "p97": 71.6},
    {"month": 8, "L": 1.0, "M": 68.7498, "S": 0.03440, "p3": 64.3, "p50": 68.7, "p97": 73.2},
    {"month": 9, "L": 1.0, "M": 70.1435, "S": 0.03444, "p3": 65.6, "p50": 70.1, "p97": 74.7},
    {"month": 10, "L": 1.0, "M": 71.4818, "S": 0.03452, "p3": 66.8, "p50": 71.5, "p97": 76.1},
    {"month": 11, "L": 1.0, "M": 72.7710, "S": 0.03464, "p3": 68.0, "p50": 72.8, "p97": 77.5},
    {"month": 12, "L": 1.0, "M": 74.0150, "S": 0.03479, "p3": 69.2, "p50": 74.0, "p97": 78.9},
    {"month": 13, "L": 1.0, "M": 75.2176, "S": 0.03496, "p3": 70.3, "p50": 75.2, "p97": 80.2},
    {"month": 14, "L": 1.0, "M": 76.3817, "S": 0.03514, "p3": 71.3, "p50": 76.4, "p97": 81.4},
    {"month": 15, "L": 1.0, "M": 77.5099, "S": 0.03534, "p3": 72.4, "p50": 77.5, "p97": 82.7},
    {"month": 16, "L": 1.0, "M": 78.6055, "S": 0.03555, "p3": 73.3, "p50": 78.6, "p97": 83.9},
    {"month": 17, "L": 1.0, "M": 79.6710, "S": 0.03576, "p3": 74.3, "p50": 79.7, "p97": 85.0},
    {"month": 18, "L": 1.0, "M": 80.7079, "S": 0.03598, "p3": 75.2, "p50": 80.7, "p97": 86.2},
    {"month": 19, "L": 1.0, "M": 81.7182, "S": 0.03620, "p3": 76.2, "p50": 81.7, "p97": 87.3},
    {"month": 20, "L": 1.0, "M": 82.7036, "S": 0.03643, "p3": 77.0, "p50": 82.7, "p97": 88.4},
    {"month": 21, "L": 1.0, "M": 83.6654, "S": 0.03666, "p3": 77.9, "p50": 83.7, "p97": 89.4},
    {"month": 22, "L": 1.0, "M": 84.6040, "S": 0.03688, "p3": 78.7, "p50": 84.6, "p97": 90.5},
    {"month": 23, "L": 1.0, "M": 85.5202, "S": 0.03711, "p3": 79.6, "p50": 85.5, "p97": 91.5},
    {"month": 24, "L": 1.0, "M": 86.4153, "S": 0.03734, "p3": 80.3, "p50": 86.4, "p97": 92.5},
 ]
 def _interpolate_lms(table: List[Dict[str, float]], age_months: float) -> Tuple[float, float, float, float, float, float]:
    m_clamped = max(0.0, min(float(table[-1]["month"]), float(age_months)))
    m_low = int(math.floor(m_clamped))
    m_high = int(math.ceil(m_clamped))
    r_low = table[m_low]
    if m_low == m_high:
        return r_low["L"], r_low["M"], r_low["S"], r_low["p3"], r_low["p50"], r_low["p97"]
    r_high = table[m_high]
    frac = m_clamped - m_low
    L = r_low["L"] + frac * (r_high["L"] - r_low["L"])
    M = r_low["M"] + frac * (r_high["M"] - r_low["M"])
    S = r_low["S"] + frac * (r_high["S"] - r_low["S"])
    p3 = r_low["p3"] + frac * (r_high["p3"] - r_low["p3"])
    p50 = r_low["p50"] + frac * (r_high["p50"] - r_low["p50"])
    p97 = r_low["p97"] + frac * (r_high["p97"] - r_low["p97"])
    return L, M, S, p3, p50, p97
 def calculate_percentile(metric: str, value: float, age_months: float) -> Dict[str, Any]:
    table = WHO_GIRLS_WEIGHT if metric == "weight" else WHO_GIRLS_HEIGHT
    L, M, S, p3, p50, p97 = _interpolate_lms(table, age_months)
    if value <= 0 or M <= 0 or S <= 0:
        return {
            "value": value,
            "age_months": round(age_months, 2),
            "z_score": 0.0,
            "percentile": 50.0,
            "percentile_str": "P50",
            "p3": round(p3, 2),
            "p50": round(p50, 2),
            "p97": round(p97, 2),
            "in_normal_range": True,
            "status": "normal",
        }
    if abs(L) > 1e-6:
        z = ((value / M) ** L - 1.0) / (L * S)
    else:
        z = math.log(value / M) / S
    p = 0.5 * (1.0 + math.erf(z / math.sqrt(2.0))) * 100.0
    p_clamped = max(0.1, min(99.9, p))
    in_normal = 3.0 <= p_clamped <= 97.0
    if p_clamped < 3.0:
        status = "unter P3"
    elif p_clamped > 97.0:
        status = "über P97"
    else:
        status = "im WHO-Normbereich"
    return {
        "value": value,
        "age_months": round(age_months, 2),
        "z_score": round(z, 2),
        "percentile": round(p_clamped, 1),
        "percentile_str": f"P{int(round(p_clamped))}",
        "p3": round(p3, 2),
        "p50": round(p50, 2),
        "p97": round(p97, 2),
        "in_normal_range": in_normal,
        "status": status,
    }
@@ -0,0 +1,28 @@
 [project]
 name = "duckdb-backend"
 version = "1.0.0"
 description = "FastAPI HTTP DuckDB Backend for Knowledge Wiki Personal Data"
 readme = "README.md"
 requires-python = ">=3.12"
 dependencies = [
    "fastapi>=0.115.0",
    "uvicorn[standard]>=0.30.0",
    "duckdb>=1.1.0",
    "python-ulid>=3.0.0",
    "pytz>=2024.1",
    "pydantic>=2.8.0",
    "httpx>=0.27.0",
 ]
 [project.optional-dependencies]
 dev = [
    "pytest>=8.0.0",
    "pytest-asyncio>=0.24.0",
 ]
 [build-system]
 requires = ["hatchling"]
 build-backend = "hatchling.build"
 [tool.hatch.build.targets.wheel]
 packages = ["app"]
@@ -0,0 +1,36 @@
 import os
 import shutil
 import tempfile
 from pathlib import Path
 import pytest
 from fastapi.testclient import TestClient
 from app.config import DATA_DIR
 from app.engine import DuckDBEngine
 from app.git_sync import GitSyncManager
 from app.main import app
@pytest.fixture(scope="session")
 def test_data_dir():
    temp_root = Path(tempfile.mkdtemp())
    temp_data = temp_root / "data"
    if DATA_DIR.is_dir():
        shutil.copytree(DATA_DIR, temp_data)
    else:
        temp_data.mkdir(parents=True, exist_ok=True)
    yield temp_data
    shutil.rmtree(temp_root, ignore_errors=True)
@pytest.fixture
 def engine(test_data_dir):
    return DuckDBEngine(data_dir=test_data_dir)
@pytest.fixture
 def client(engine):
    app.state.engine = engine
    app.state.git_sync = GitSyncManager(wiki_dir=engine.data_dir.parent)
    with TestClient(app) as c:
        yield c
@@ -0,0 +1,205 @@
 import pytest
 from fastapi.testclient import TestClient
 def test_mila_dashboard_endpoint(client: TestClient):
    resp = client.get("/duckdb-api/v1/mila/dashboard")
    assert resp.status_code == 200
    data = resp.json()
    assert data["status"] == "ok"
    assert data["metadata"]["subject"] == "mila"
    assert "live_status" in data
    assert "today" in data
    assert "growth" in data
 def test_moritz_dashboard_endpoint(client: TestClient):
    resp = client.get("/duckdb-api/v1/moritz/dashboard")
    assert resp.status_code == 200
    data = resp.json()
    assert data["status"] == "ok"
    assert data["metadata"]["subject"] == "moritz"
    assert "today" in data
    assert "yesterday" in data
    assert "seven_days" in data
    assert "thirty_days" in data
 def test_healthz_and_status_endpoints(client: TestClient):
    resp_h = client.get("/healthz")
    assert resp_h.status_code == 200
    assert resp_h.json()["engine_ready"] is True
    resp_s = client.get("/duckdb-api/v1/status")
    assert resp_s.status_code == 200
    data_s = resp_s.json()
    assert "status" in data_s
    assert "table_counts" in data_s
    assert data_s["table_counts"]["sleep"] > 0
 def test_mila_history_includes_diaper_only_days(client: TestClient):
    # Log a diaper change for a specific day without sleep
    client.post("/duckdb-api/v1/events", json={
        "kind": "diaper.change",
        "subject": "mila",
        "start": "2026-10-12T12:00:00+02:00",
        "payload": {"pee": True, "poo": True},
    })
    resp = client.get("/duckdb-api/v1/mila/dashboard")
    assert resp.status_code == 200
    data = resp.json()
    history = data["history"]
    dates = [h["date"] for h in history]
    assert "2026-10-12" in dates
 def test_moritz_seven_days_includes_garmin_days(client: TestClient):
    resp = client.get("/duckdb-api/v1/moritz/dashboard")
    assert resp.status_code == 200
    data = resp.json()
    days = data["seven_days"]["days"]
    assert len(days) > 0
    # Every returned day has a valid date and steps or expenditure
    for d in days:
        assert d["date"] is not None
        assert "expenditure_kcal" in d
 def test_mila_dashboard_parent_cockpit_and_norms(client: TestClient):
    resp = client.get("/duckdb-api/v1/mila/dashboard")
    assert resp.status_code == 200
    data = resp.json()
    # Parent cockpit live fields
    live = data["live_status"]
    assert "is_sleeping" in live
    assert "active_sleep_duration_str" in live
    assert "wake_window_minutes" in live
    assert "last_feed_since_str" in live
    assert "last_diaper_since_str" in live
    assert "last_stool_str" in live
    # Science age norms
    assert "age_norms" in data
    norms = data["age_norms"]
    assert norms["age_months"] >= 6.0
    assert norms["wake_window_min_minutes"] == 135
    assert norms["wake_window_max_minutes"] == 180
    assert norms["feed_interval_min_minutes"] == 180
    # Ensure IDs on items
    today = data["today"]
    for f in today["feedings"]:
        assert "id" in f
    for d in today["diapers"]:
        assert "id" in d
 def test_day_detail_and_summary_endpoints(client: TestClient):
    # Test mila day detail
    resp_mila = client.get("/duckdb-api/v1/mila/day/2026-10-12")
    assert resp_mila.status_code == 200
    assert resp_mila.json()["metadata"]["today_date"] == "2026-10-12"
    # Test moritz day detail
    resp_moritz = client.get("/duckdb-api/v1/moritz/day/2026-10-12")
    assert resp_moritz.status_code == 200
    assert "today" in resp_moritz.json()
    # Test summary
    resp_sum = client.get("/duckdb-api/v1/summary/mila?date=2026-10-12")
    assert resp_sum.status_code == 200
    sum_data = resp_sum.json()
    assert sum_data["subject"] == "mila"
    assert sum_data["date"] == "2026-10-12"
    assert "nutrition" in sum_data
 def test_entities_and_places_endpoints(client: TestClient):
    # Put and list entity
    client.post("/duckdb-api/v1/entities", json={
        "collection": "places",
        "record": {
            "id": "test-biergarten",
            "name": "Test Biergarten",
            "category": "biergarten",
            "lat": 49.02,
            "lon": 12.09,
        }
    })
    resp_places = client.get("/duckdb-api/v1/entities/places")
    assert resp_places.status_code == 200
    places = resp_places.json()
    assert any(p["id"] == "test-biergarten" for p in places)
    # Places near search
    resp_near = client.get("/duckdb-api/v1/places/near?lat=49.02&lon=12.09&radius_m=500")
    assert resp_near.status_code == 200
    near = resp_near.json()
    assert len(near) > 0
    assert near[0]["id"] == "test-biergarten"
 def test_garmin_sync_and_duplicate_guard(client: TestClient):
    # Duplicate guard test
    post_data = {
        "kind": "feeding.bottle",
        "subject": "mila",
        "start": "2026-10-12T10:00:00+02:00",
        "payload": {"consumed_ml": 180, "milk_type": "pre"},
    }
    r1 = client.post("/duckdb-api/v1/events", json=post_data)
    assert r1.status_code == 200
    assert r1.json()["status"] == "success"
    assert "feedback" in r1.json()
    # Second post within 15min should be duplicate_skipped
    r2 = client.post("/duckdb-api/v1/events", json=post_data)
    assert r2.status_code == 200
    assert r2.json()["status"] == "duplicate_skipped"
    # Garmin sync test
    garmin_payload = {
        "daily": [{
            "calendarDate": "2026-10-15",
            "totalKilocalories": 2400,
            "activeKilocalories": 600,
            "bmrKilocalories": 1800,
            "totalSteps": 11000,
            "restingHeartRate": 52,
        }],
        "sleep": [],
        "activities": [],
    }
    r_sync = client.post("/duckdb-api/v1/garmin/sync", json=garmin_payload)
    assert r_sync.status_code == 200
    assert r_sync.json()["status"] == "success"
    assert r_sync.json()["synced_daily"] == 1
    # Test alias support (daily_summary and sleep_data dicts)
    garmin_alias_payload = {
        "date": "2026-10-16",
        "daily_summary": {
            "calendarDate": "2026-10-16",
            "totalKilocalories": 2550,
            "activeKilocalories": 650,
            "bmrKilocalories": 1900,
            "totalSteps": 12000,
            "restingHeartRate": 50,
        },
        "sleep_data": {
            "dailySleepDTO": {
                "calendarDate": "2026-10-16",
                "sleepTimeSeconds": 28800,
            }
        },
        "activities": [],
    }
    r_alias = client.post("/duckdb-api/v1/garmin/sync", json=garmin_alias_payload)
    assert r_alias.status_code == 200
    assert r_alias.json()["status"] == "success"
    assert r_alias.json()["synced_daily"] == 1
    assert r_alias.json()["synced_sleep"] == 1
@@ -0,0 +1,176 @@
 import tempfile
 import pytest
 from pathlib import Path
 from fastapi.testclient import TestClient
 from app.engine import DuckDBEngine
 from app.models import EventCreateRequest, EventStopRequest
 def test_add_and_stop_sleep_event(tmp_path: Path):
    # Use isolated temp directory for write tests so we do not pollute wiki git repo
    engine = DuckDBEngine(data_dir=tmp_path)
    # 1. Add active sleep event (end=None)
    add_req = EventCreateRequest(
        kind="sleep.session",
        subject="mila",
        payload={"type": "nap", "location": "kinderwagen"},
        actor="test-runner",
        note="Mittagsschlaf Test",
    )
    res_add = engine.add_event(add_req)
    assert res_add["status"] == "success"
    event_id = res_add["id"]
    assert event_id is not None
    # Check that it appears in open sleep
    open_rows = engine.query(f"SELECT * FROM sleep WHERE id = '{event_id}' AND (isOpen = true OR endIso IS NULL)")
    assert len(open_rows) == 1
    # 2. Stop the active sleep event
    stop_req = EventStopRequest(
        kind="sleep.session",
        subject="mila",
        event_id=event_id,
        actor="test-runner",
    )
    res_stop = engine.stop_event(stop_req)
    assert res_stop["status"] == "success"
    assert res_stop["id"] == event_id
    # Check that it is now closed
    closed_rows = engine.query(f"SELECT isOpen, endIso FROM sleep WHERE id = '{event_id}'")
    assert len(closed_rows) == 1
    assert closed_rows[0]["isOpen"] is False
    assert closed_rows[0]["endIso"] is not None
 def test_add_nutrition_and_diaper_event(tmp_path: Path):
    engine = DuckDBEngine(data_dir=tmp_path)
    # Add nutrition event
    nut_req = EventCreateRequest(
        kind="nutrition.intake",
        subject="moritz",
        payload={"item": "Apfel", "qty": 150.0, "kcal": 78.0, "protein_g": 0.5},
        meal="snack",
        actor="test-runner",
    )
    res_nut = engine.add_event(nut_req)
    assert res_nut["status"] == "success"
    nut_id = res_nut["id"]
    nut_rows = engine.query(f"SELECT * FROM nutrition WHERE id = '{nut_id}'")
    assert len(nut_rows) == 1
    # Add diaper event
    diaper_req = EventCreateRequest(
        kind="diaper.change",
        subject="mila",
        payload={"pee": True, "poo": False},
        actor="test-runner",
    )
    res_diaper = engine.add_event(diaper_req)
    assert res_diaper["status"] == "success"
    diaper_id = res_diaper["id"]
    diaper_rows = engine.query(f"SELECT * FROM mila WHERE id = '{diaper_id}'")
    assert len(diaper_rows) == 1
 def test_duplicate_open_sleep_rejected(tmp_path: Path):
    engine = DuckDBEngine(data_dir=tmp_path)
    # 1. Start first open sleep session
    req1 = EventCreateRequest(
        kind="sleep.session",
        subject="mila",
        payload={"type": "nap", "location": "bett"},
        actor="parent",
    )
    res1 = engine.add_event(req1)
    assert res1["status"] == "success"
    # 2. Attempt to start second open sleep session without stopping the first
    req2 = EventCreateRequest(
        kind="sleep.session",
        subject="mila",
        payload={"type": "nap", "location": "kinderwagen"},
        actor="parent",
    )
    with pytest.raises(ValueError, match="already active for subject 'mila'"):
        engine.add_event(req2)
 def test_duplicate_open_sleep_api_endpoint(client: TestClient):
    # 1. Start first session via API
    res1 = client.post("/duckdb-api/v1/events", json={
        "kind": "sleep.session",
        "subject": "test_baby",
        "payload": {"type": "nap"},
    })
    assert res1.status_code == 200
    # 2. Start second session via API -> must return 400 Bad Request
    res2 = client.post("/duckdb-api/v1/events", json={
        "kind": "sleep.session",
        "subject": "test_baby",
        "payload": {"type": "nap"},
    })
    assert res2.status_code == 400
    assert "already active for subject 'test_baby'" in res2.json()["detail"]
    # 3. Clean up by stopping
    stop_res = client.post("/duckdb-api/v1/events/stop", json={
        "kind": "sleep.session",
        "subject": "test_baby",
    })
    assert stop_res.status_code == 200
 def test_agent_utc_wallclock_guard_and_mila_recipe_defaults(tmp_path: Path):
    engine = DuckDBEngine(data_dir=tmp_path)
    # 1. Agent passes +00:00 on local wall-clock times (e.g. 08:30 to 10:20)
    nap_req = EventCreateRequest(
        kind="sleep.session",
        subject="mila",
        actor="agent:mila_tracker",
        start="2026-10-17T08:30:00+00:00",
        end="2026-10-17T10:20:00+00:00",
        payload={"type": "nap", "location": "bett"},
    )
    res_nap = engine.add_event(nap_req)
    assert res_nap["status"] == "success"
    assert res_nap["record"]["startIso"] == "2026-10-17T08:30:00+02:00"
    assert res_nap["record"]["endIso"] == "2026-10-17T10:20:00+02:00"
    assert res_nap["record"]["sleepTimeSeconds"] == 6600
    # 2. Solid food without amount_g gets standard recipe defaults
    brei_req = EventCreateRequest(
        kind="feeding.solid",
        subject="mila",
        actor="agent:mila_tracker",
        start="2026-10-17T12:20:00+00:00",
        meal="lunch",
        payload={"item": "mittagsbrei"},
    )
    res_brei = engine.add_event(brei_req)
    assert res_brei["record"]["start"] == "2026-10-17T12:20:00+02:00"
    assert res_brei["record"]["payload"]["amount_g"] == 190
    assert res_brei["record"]["payload"]["kcal"] == 135
    abend_req = EventCreateRequest(
        kind="feeding.solid",
        subject="mila",
        actor="agent:mila_tracker",
        start="2026-10-17T16:40:00+00:00",
        meal="dinner",
        payload={"item": "abendbrei"},
    )
    res_abend = engine.add_event(abend_req)
    assert res_abend["record"]["start"] == "2026-10-17T16:40:00+02:00"
    assert res_abend["record"]["payload"]["amount_g"] == 200
    assert res_abend["record"]["payload"]["kcal"] == 110
@@ -0,0 +1,28 @@
 import pytest
 from fastapi.testclient import TestClient
 def test_generic_query_select(client: TestClient):
    payload = {
        "query": "SELECT count(*) AS cnt FROM v_sleep WHERE subject = 'mila'"
    }
    resp = client.post("/duckdb-api/v1/query", json=payload)
    assert resp.status_code == 200
    data = resp.json()
    assert "rows" in data
    assert len(data["rows"]) == 1
    assert data["rows"][0]["cnt"] > 0
    assert data["execution_time_ms"] < 50.0  # verifies sub-50ms execution
 def test_generic_query_disallowed_drop(client: TestClient):
    payload = {"query": "DROP TABLE sleep;"}
    resp = client.post("/duckdb-api/v1/query", json=payload)
    assert resp.status_code == 400
    assert "not permitted" in resp.json()["detail"]
 def test_generic_query_disallowed_insert(client: TestClient):
    payload = {"query": "INSERT INTO sleep VALUES ('x', 'y')"}
    resp = client.post("/duckdb-api/v1/query", json=payload)
    assert resp.status_code == 400
@@ -0,0 +1,36 @@
 import pytest
 from app.engine import DuckDBEngine
 def test_engine_init_and_counts(engine: DuckDBEngine):
    counts = engine.get_table_counts()
    assert "sleep" in counts
    assert "nutrition" in counts
    assert "mila" in counts
    assert "garmin_daily" in counts
    assert counts["sleep"] > 0
    assert counts["nutrition"] > 0
 def test_mila_dashboard_payload(engine: DuckDBEngine):
    data = engine.get_mila_dashboard()
    assert data["status"] == "ok"
    assert data["metadata"]["subject"] == "mila"
    assert "live_status" in data
    assert "today" in data
    assert "averages" in data
    assert "history" in data
    assert "growth" in data
    assert len(data["history"]) > 0
 def test_moritz_dashboard_payload(engine: DuckDBEngine):
    data = engine.get_moritz_dashboard()
    assert data["status"] == "ok"
    assert data["metadata"]["subject"] == "moritz"
    assert "today" in data
    assert "yesterday" in data
    assert "garmin_recovery" in data
    assert "seven_days" in data
    assert "thirty_days" in data
    assert len(data["thirty_days"]["days"]) > 0
@@ -0,0 +1,68 @@
 import subprocess
 from pathlib import Path
 from app.git_sync import GitSyncManager
 def test_git_sync_conflict_handling(tmp_path: Path):
    repo_dir = tmp_path / "fake_repo"
    repo_dir.mkdir()
    subprocess.run(["git", "init", "-b", "main", str(repo_dir)], check=True)
    subprocess.run(["git", "-C", str(repo_dir), "config", "user.email", "test@test.local"], check=True)
    subprocess.run(["git", "-C", str(repo_dir), "config", "user.name", "Test User"], check=True)
    test_file = repo_dir / "test.txt"
    test_file.write_text("initial")
    subprocess.run(["git", "-C", str(repo_dir), "add", "."], check=True)
    subprocess.run(["git", "-C", str(repo_dir), "commit", "-m", "initial commit"], check=True)
    mgr = GitSyncManager(wiki_dir=repo_dir)
    assert mgr.ensure_repo() is True
    assert mgr.status == "ok"
    assert mgr.is_conflict is False
 def test_git_url_encoding(monkeypatch):
    monkeypatch.setattr("app.git_sync.GIT_USERNAME", "moritz@graf")
    monkeypatch.setattr("app.git_sync.GIT_PASSWORD", "p@ss:w/ord%123")
    monkeypatch.setattr("app.git_sync.GIT_REPO_URL", "https://git.moritzgraf.de/moritz/knowledge-wiki.git")
    mgr = GitSyncManager()
    auth_url = mgr.get_auth_repo_url()
    assert auth_url == "https://moritz%40graf:p%40ss%3Aw%2Ford%25123@git.moritzgraf.de/moritz/knowledge-wiki.git"
 def test_ensure_repo_handles_non_empty_dir(tmp_path: Path):
    # Simulate a PVC containing lost+found before repo initialization
    wiki_pvc = tmp_path / "wiki_pvc"
    wiki_pvc.mkdir()
    (wiki_pvc / "lost+found").mkdir()
    # Create upstream origin to fetch from
    origin = tmp_path / "origin.git"
    subprocess.run(["git", "init", "--bare", str(origin)], check=True)
    # Push initial commit to bare origin
    work = tmp_path / "work"
    work.mkdir()
    subprocess.run(["git", "init", "-b", "main", str(work)], check=True)
    subprocess.run(["git", "-C", str(work), "config", "user.name", "Admin"], check=True)
    subprocess.run(["git", "-C", str(work), "config", "user.email", "admin@test.local"], check=True)
    (work / "README.md").write_text("# Knowledge Wiki")
    subprocess.run(["git", "-C", str(work), "add", "."], check=True)
    subprocess.run(["git", "-C", str(work), "commit", "-m", "init"], check=True)
    subprocess.run(["git", "-C", str(work), "remote", "add", "origin", str(origin)], check=True)
    subprocess.run(["git", "-C", str(work), "push", "origin", "main"], check=True)
    # Now verify GitSyncManager initializes cleanly into non-empty directory
    mgr = GitSyncManager(wiki_dir=wiki_pvc)
    # Point URL to file repo
    import app.git_sync
    app.git_sync.GIT_REPO_URL = str(origin)
    app.git_sync.GIT_USERNAME = ""
    app.git_sync.GIT_PASSWORD = ""
    success = mgr.ensure_repo()
    assert success is True
    assert (wiki_pvc / ".git").is_dir()
    assert (wiki_pvc / "README.md").is_file()
    assert (wiki_pvc / "lost+found").is_dir()
@@ -0,0 +1,813 @@
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@@ -0,0 +1,38 @@
 # AGENTS.md — Kitchen e-Paper Display (`esphome_display_kitchen`)
 > [!NOTE]
 > **Domain**: ESP32 microcontroller driving the e-Paper display in the kitchen.  
 > **Source Location**: `projects/esphome_display_kitchen/`  
 > **Integrations**: Home Assistant Native API (`https://hass.moritzgraf.de`), Prometheus metrics client.  
 > **Hardware**: Waveshare e-Paper display on ESP32 (`nodemcu-32s`).
 ---
 ## 🛠️ Build, Flash & Messaging Tooling
 - **Interactive Flashing Wizard**:
  ```bash
  cd projects/esphome_display_kitchen
  uv run flash.py
  ```
  Provides an interactive CLI to Validate, Compile, Upload, and view Logs for `esdisplay_kitchen.yaml`.
 - **Direct Terminal Messaging**:
  ```bash
  cd projects/esphome_display_kitchen
  ./send_message.sh "Your custom display message"
  ```
  Uses the Home Assistant long-lived token from `k8s/home-assistant/` to set the `input_text.epaper_message` helper in Home Assistant, which instantly pushes updates to the screen.
 ---
 ## 🚨 Rules & Standards
 ### 1. Secret Management
 * **NEVER** write plaintext Wi-Fi passwords, tokens, or API keys directly into YAML configurations.
 * **DO NOT** modify `.gitignore` to allow committing `.env` files.
 * Use ESPHome's `!env_var VAR_NAME` to inject environment variables at compile-time. Any new secrets must be declared in `.env.template` and configured locally in `.env`.
 ### 2. Configuration Standards
 * Board architecture: ESP32 (`nodemcu-32s` with `arduino` framework).
 * SNTP time synchronization configured via `time` component for clock rendering.
 * Sensor values (outdoor temperature, indoor climate) are dynamically pulled from Home Assistant entities.
@@ -5,7 +5,7 @@ set -e
 CDIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
 # Read the token from the home-assistant secrets folder
-TOKEN_FILE="${CDIR}/../k8s/home-assistant/tmp_long_lived_token.secret.yml"
+TOKEN_FILE="${CDIR}/../../k8s/home-assistant/tmp_long_lived_token.secret.yml"
 if [ ! -f "$TOKEN_FILE" ]; then
  echo "Error: Home Assistant token file not found at $TOKEN_FILE."
@@ -0,0 +1,6 @@
 node_modules/
 dist/
 __pycache__/
 *.pyc
 .env
 .DS_Store
@@ -0,0 +1,76 @@
 # AGENTS.md — Grabengasse 7 Home Portal (`grabengasse`)
 > [!NOTE]
 > **Domain**: Local climate, environment, and smart home portal for Grabengasse 7.  
 > **Live Production URL**: `https://grabengasse7.de`  
 > **Kubernetes Manifests**: `k8s/grabengasse/` (Namespace: `grabengasse`)  
 > **Images**:  
 > - Frontend: `registry.haumdaucher.de/website/grabengasse_frontend:latest`  
 > - Backend: `registry.haumdaucher.de/website/grabengasse_backend:latest`  
 > **Source Location**: `projects/grabengasse/`
 ---
 ## 🏛️ Architecture & Tech Stack
 1. **Frontend (`frontend/`)**:
   - **Framework**: Vue 3 (Composition API) + Vite + TypeScript.
   - **Styling**: Retro-chic aesthetic with pixel art accents, glassmorphic cards, and an optional CRT scanline toggle.
   - **Data Visualization**: Chart.js / Vue-Chartjs / Apexcharts for 24h temperature, humidity, wind, solar, and rain telemetry.
   - **Serving Runtime**: Nginx (`nginx:alpine`) in Docker.
 2. **Backend (`backend/`)**:
   - **Framework**: FastAPI (Python 3.11).
   - **Telemetry Source**: Direct HTTP queries to cluster Prometheus (`http://prometheus-operator-kube-p-prometheus.monitoring.svc.cluster.local:9090`) aggregating metrics from the Shelly WS90 weather station.
   - **Endpoints**:
     - `GET /healthz`: Liveness and readiness probe.
     - `GET /api/v1/weather/current`: Live weather telemetry (temperature, humidity, wind speed, solar radiation, rain).
     - `GET /api/v1/weather/history`: Historical timeseries for 24h graphing.
 3. **Kubernetes Ingress & Routing (`k8s/grabengasse/`)**:
   - Ingress Host: `grabengasse7.de` with Traefik ingress controller and `cert-manager` TLS.
   - `/` &rarr; `grabengasse-frontend` (Port 80)
   - `/api` &rarr; `grabengasse-backend` (Port 8000)
 ---
 ## 🛠️ Build & Deployment Commands
 ```bash
 cd projects/grabengasse
 make compile          # Build frontend static assets (npm run build)
 make build            # Build both frontend and backend Docker images (linux/amd64)
 make push             # Push images to registry.haumdaucher.de
 make deploy           # Apply k8s manifests and rollout restart pods
 ```
 ---
 ## 📁 Repository Structure
 ```
 projects/grabengasse/
 ├── Makefile                    # Coordinated multi-service build and deploy
 ├── AGENTS.md                   # This handbook
 ├── README.md                   # Project overview
 ├── frontend/                   # Vue 3 SPA
 │   ├── Dockerfile
 │   ├── Makefile
 │   ├── nginx.conf
 │   ├── package.json
 │   ├── src/
 │   │   ├── App.vue             # Weather dashboard layout & state
 │   │   ├── components/         # Weather gauges, telemetry cards & retro CRT overlay
 │   │   └── scripts/            # generate_icons.py (Pixel art icon generator)
 │   └── public/                 # Static icons, manifest, and service worker
 └── backend/                    # FastAPI microservice
    ├── Dockerfile
    ├── Makefile
    ├── requirements.txt
    ├── main.py                 # FastAPI application entrypoint
    ├── config.py               # CORS & environment configuration
    ├── routers/
    │   └── weather.py          # /api/v1/weather routes
    └── services/
        └── prometheus.py       # Prometheus query client
 ```
@@ -0,0 +1,43 @@
 REGISTRY ?= registry.haumdaucher.de
 FRONTEND_IMAGE ?= $(REGISTRY)/website/grabengasse_frontend:latest
 BACKEND_IMAGE ?= $(REGISTRY)/website/grabengasse_backend:latest
 NAMESPACE ?= grabengasse
 .PHONY: all compile dev build push deploy rollout build-frontend build-backend push-frontend push-backend
 all: compile build push deploy
 compile:
 	cd frontend && npm run build
 dev-frontend:
 	cd frontend && npm run dev
 dev-backend:
 	cd backend && uvicorn main:app --reload
 build: build-frontend build-backend
 build-frontend:
 	cd frontend && docker build --platform linux/amd64 -t $(FRONTEND_IMAGE) .
 build-backend:
 	cd backend && docker build --platform linux/amd64 -t $(BACKEND_IMAGE) .
 push: push-frontend push-backend
 push-frontend:
 	docker push $(FRONTEND_IMAGE)
 push-backend:
 	docker push $(BACKEND_IMAGE)
 deploy:
 	kubectl apply -f ../../k8s/grabengasse/backend.yaml -f ../../k8s/grabengasse/frontend.yaml -f ../../k8s/grabengasse/ingress.yaml
 	$(MAKE) rollout
 rollout:
 	kubectl rollout restart deployment/grabengasse-frontend -n $(NAMESPACE)
 	kubectl rollout restart deployment/grabengasse-backend -n $(NAMESPACE)
 	kubectl rollout status deployment/grabengasse-frontend -n $(NAMESPACE)
 	kubectl rollout status deployment/grabengasse-backend -n $(NAMESPACE)
@@ -0,0 +1,12 @@
 # Grabengasse 7 Home Portal 🌦️
 Climate and environmental monitoring web dashboard for Grabengasse 7 (`https://grabengasse7.de`).
 ## Architecture
 - **`frontend/`**: Vue 3 + TypeScript SPA displaying real-time telemetry from the Shelly WS90 outdoor weather station.
 - **`backend/`**: FastAPI backend fetching Prometheus metric aggregations for temperature, humidity, rain, wind, and solar irradiance.
 ## Development & Deployment
 See [AGENTS.md](AGENTS.md) for architecture details and the [Makefile](Makefile) for standard build commands (`make compile`, `make build`, `make deploy`).
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Moritz Graf	a34fa7ee08	fix(cron): resolve Garmin sync payload mismatch, harden cronjobs, and update wiki submodule	2026-10-18 20:33:26 +02:00
Moritz Graf	c33b6e94fb	fix(openclaw): configure 64k completion headroom for deepseek-v4.1-flash, promote cloudflare, and onboard fireworks	2026-10-18 11:06:50 +02:00
Moritz Graf	dd60a095c6	feat(openclaw): upgrade fleet to DeepSeek V4.1 Flash 1017 and harden operations - Upgrade OpenClaw primary model from deepseek-v4.1-flash to deepseek-v4.1-flash-1017 across all interactive agents, heartbeats, compaction, and cron jobs. - Configure hardened OpenRouter provider routing for 1017 (deepinfra, inference-net, parasail, cloudflare) with strict fp8/bf16 quantization and tool_choice verification. - Retain deepseek-v4.1-flash (0910), z-ai/glm-5.3-flash, and qwen3.8-flash in the automated fallback chain. - Update ADR 0002 with 1017 economics (30% price reduction on prompt/cache, +60% intelligence benchmark increase) and a 7-point provider qualification playbook. - Add operational scripts and tooling for session compaction, subagent vector deduplication, gateway preflight, and triage diagnostics in k8s/openclaw. - Update DuckDB backend engine, git-sync logic, and test suites. - Enhance Mila tracking UI components and add container build configuration. - Sync Terraform infrastructure state for Authentik.	2026-10-18 10:54:59 +02:00
Moritz Graf	7ce1da18ab	fix(mila): fix last feed display, hide diaper tile when empty today, and add resilient git-init	2026-10-17 08:01:39 +02:00
Moritz Graf	5b8432caf4	feat(family): deploy Single-Writer DuckDB backend, Mila parent cockpit & feeding analytics, and Moritz macro tracker	2026-10-17 07:21:49 +02:00
Moritz Graf	ef50d87bd7	fix(openclaw): add automatic mcp-venv fallback to sync_crons.py	2026-10-16 21:28:15 +02:00
Moritz Graf	ed3529a9d7	feat(openclaw): modularize scripts, implement crons-as-code and EaC governance	2026-10-16 21:25:33 +02:00
Moritz Graf	f4d8210cc4	fix(openclaw): fix tracking tool allowlist, resolve research fastpath and cap bootstrap bloat	2026-10-14 15:34:45 +02:00
Moritz Graf	02fcbd3174	feat(openclaw): strip tracking agent prompt bloat and add 15m deterministic sliding-window compaction - Disable bootstrap context injection (contextInjection: never) and skill catalog injection (skills: []) on mila_tracker and nutrition_tracker, dropping baseline prompt by 95% (<350 tokens) - Disable reasoning loops on tracking agents (thinkingDefault: off) for instantaneous sub-second execution - Add compact_tracking_sessions.py with deterministic 8-line sliding window (--max-lines 8) requiring 0 LLM tokens - Register automated 15-minute cron job (tracking-session-sliding-window) in OpenClaw gateway - Streamline setup-compaction-cron.sh to sync python scripts directly and manage both 15m and nightly maintenance	2026-10-14 14:14:35 +02:00
Moritz Graf	a0c8c3828c	fix(openclaw): resolve tracking compaction hang, restrict tracking tools and enforce lifecycle management	2026-10-14 13:39:38 +02:00
Moritz Graf	cab8dd290f	feat(openclaw): switch mila_tracker primary model to DeepSeek V4.1 Flash and add koch recipe delegation	2026-10-13 09:49:04 +02:00
Moritz Graf	c85a60d920	feat(openclaw): update agent instance configuration and sync knowledge-wiki submodule	2026-10-13 09:41:25 +02:00
Moritz Graf	a2cf3bfe39	fix(openclaw): decouple Gemini 3.8 Flash vision perception while preserving GLM-5.3-flash as primary chat model	2026-10-12 22:21:06 +02:00
Moritz Graf	d84d7b0bec	fix(openclaw): upgrade fitness agent model to gemini-3.8-flash and document issue 28	2026-10-12 22:04:22 +02:00
Moritz Graf	6acceec701	docs(openclaw): document lasagna logging recovery and compaction in issue 27	2026-10-12 21:05:22 +02:00
Moritz Graf	972d629df8	chore(wiki): update knowledge-wiki submodule pointer	2026-10-12 21:04:06 +02:00
Moritz Graf	a12b596053	fix(openclaw): allocate Gemini 3.8 Flash to koch agent, harden vision and tool protocols	2026-10-12 19:52:11 +02:00
Moritz Graf	393d928b19	feat(openclaw): tune compaction to keepRecentTokens 3k and convert Tier A to deep-compaction	2026-10-12 17:10:00 +02:00
Moritz Graf	8f01b75bd6	refactor(structure): reorganize monorepo with projects, terraform hierarchy, and strict k8s namespace rules	2026-10-12 13:49:41 +02:00
Moritz Graf	4831147087	docs(openclaw): document issue 25 duplicate porridge logging & update triage filter	2026-10-12 12:09:57 +02:00
Moritz Graf	3b190988be	feat(projects): migrate haumdaucherde website into monorepo and document in AGENTS.md	2026-10-12 10:42:30 +02:00