docs: generate llms.txt and llms-full.txt via mkdocs-llmstxt plugin

.github/workflows/docs.yml

@@ -33,7 +33,7 @@ jobs:
           python-version: '3.12'
 
       - name: Install documentation dependencies
-        run: pip install "mkdocs-material>=9.5,<10"
+        run: pip install "mkdocs-material>=9.5,<10" "mkdocs-llmstxt>=0.5.0,<1.0"
 
       - name: Build documentation
         run: mkdocs build --strict

docs/index.md

@@ -93,3 +93,8 @@ config/
 📝 **Documentation Status**: This documentation lives in the [`docs/` folder of the batcontrol repository](https://github.com/MaStr/batcontrol/tree/main/docs). If you find outdated information or need additional details, please open an issue or pull request.
 
 🔗 **Project Repository**: [GitHub - Batcontrol](https://github.com/MaStr/batcontrol)
+
+---
+
+**LLM-friendly versions of this documentation:**
+[llms.txt](https://mastr.github.io/batcontrol/llms.txt) — [llms-full.txt](https://mastr.github.io/batcontrol/llms-full.txt)

mkdocs.yml

@@ -47,6 +47,38 @@ markdown_extensions:
 
 plugins:
   - search
+  - llmstxt:
+      markdown_description: |
+        Batcontrol controls a PV battery inverter based on dynamic electricity prices,
+        solar production forecasts, and consumption patterns. It charges from the grid
+        when prices are low and preserves stored energy when prices are high. It supports
+        Fronius Gen24 inverters (HTTP API and Modbus TCP) and any inverter via MQTT bridge.
+        Tariff providers include Tibber, aWATTar, evcc, EnergyForecast.de, and static zone
+        tariffs. Solar forecast sources include Forecast.Solar, Solar-Prognose.de, evcc,
+        and Home Assistant Solar Forecast ML. Peak shaving distributes PV battery charging
+        across the day using forecasts, and works with both dynamic and static tariffs.
+      full_output: llms-full.txt
+      sections:
+        Getting Started:
+          - getting-started/installation.md: Installation guide with pre-flight checklist, Docker setup, and next steps
+          - getting-started/how-batcontrol-works.md: Architecture, control loop, forecasting system, and decision logic
+        Configuration:
+          - configuration/batcontrol-configuration.md: Main configuration file reference
+          - configuration/inverter-configuration.md: Fronius Gen24, Fronius Modbus, and MQTT inverter configuration
+          - configuration/dynamic-tariff-provider.md: Tibber, aWATTar, evcc, EnergyForecast, and static tariff zones
+          - configuration/solar-forecast.md: Forecast.Solar, Solar-Prognose.de, evcc, and Home Assistant ML
+          - configuration/consumption-forecast.md: CSV load profile and Home Assistant API forecast
+        Features:
+          - features/peak-shaving.md: Dynamic PV charge rate limiting to maximize solar absorption
+          - features/battery-control-expert.md: Advanced tuning parameters
+          - features/price-difference-calculation.md: How price thresholds are calculated
+        Integrations:
+          - integrations/mqtt-api.md: MQTT state publishing, runtime overrides, and Home Assistant auto-discovery
+          - integrations/mqtt-inverter.md: Integrating any battery system via MQTT bridge
+          - integrations/evcc-connection.md: Coordinating with EV charging via evcc
+          - integrations/forecast-metrics.md: Forecast data exposed via MQTT
+        Optional:
+          - development/15-min-transform.md: Internal 15-minute interval resolution
 
 nav:
   - Home: index.md

pyproject.toml

@@ -55,6 +55,7 @@ test = [
 ]
 docs = [
     "mkdocs-material>=9.5,<10",
+    "mkdocs-llmstxt>=0.5.0,<1.0; python_version >= '3.10'",
 ]
 
 # Bump Version