setasoma/mycodo-hermes-skill
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Autonomous mushroom cultivation skill for Hermes agents. Phase-aware decision engine using Mycodo sensors + InfluxDB on Raspberry Pi. 6 species, safety guards, HTML reporting.
概要
Autonomous mushroom cultivation management for AI agents. This is a Hermes agent skill that monitors environmental sensors and controls actuators on a Raspberry Pi running Mycodo and InfluxDB. It operates on a 30-minute decision cycle: read sensors, evaluate against species-specific thresholds, fire relays, and verify results. Built and tested over two complete Lion's Mane grow cycles (colonization through harvest). - -- sensor fetch, threshold evaluation, actuator control, verification, and HTML reporting in a single pass - -- six gourmet species included (Lion's Mane, Oyster, Shiitake, Reishi, Turkey Tail, Maitake) with per-phase YAML configs; add new species with zero code changes - -- colonization, primordia, fruiting, late-stage-fruiting, rest, inactive - with confidence scoring based on sensor trend analysis - -- oversaturation guard, 10-minute follow-up verification, operator override, dry-run mode - with embedded camera snapshots, delivered via Telegram screenshots -...
README
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Mycodo Hermes Skill
Autonomous mushroom cultivation management for AI agents. This is a Hermes agent skill that monitors environmental sensors and controls actuators on a Raspberry Pi running Mycodo and InfluxDB. It operates on a 30-minute decision cycle: read sensors, evaluate against species-specific thresholds, fire relays, and verify results.
Built and tested over two complete Lion’s Mane grow cycles (colonization through harvest).
Features
- 30-minute autonomous decision cycle – sensor fetch, threshold evaluation, actuator control, verification, and HTML reporting in a single pass
- Species-agnostic – six gourmet species included (Lion’s Mane, Oyster, Shiitake, Reishi, Turkey Tail, Maitake) with per-phase YAML configs; add new species with zero code changes
- Six cultivation phases per species – colonization, primordia, fruiting, late-stage-fruiting, rest, inactive
- Auto-phase transitions with confidence scoring based on sensor trend analysis
- Safety systems – oversaturation guard, 10-minute follow-up verification, operator override, dry-run mode
- HTML reports with embedded camera snapshots, delivered via Telegram screenshots
- Contamination intelligence (optional) – Reddit-sourced pattern database with 180+ cataloged entries
Hardware Requirements
| Component | Details |
|---|---|
| Raspberry Pi 4 | 8 GB recommended, running Mycodo + InfluxDB 2.x |
| SHT45 sensor | Temperature + humidity (±0.1°C, ±1% RH) |
| SCD41 sensor | CO2 monitoring |
| Exhaust fan | Relay-controlled via GPIO17 |
| Humidifier | Relay-controlled via GPIO5 (DLI IoT Power Relay v2) |
| USB webcam | Optional, for visual monitoring (e.g., Logitech C920x) |
| Network | Tailscale mesh or any IP connectivity between agent host and Pi |
Software Requirements
- Hermes agent framework
- Python 3.9+
- PyYAML
curl,jq(optional, for manual sensor queries)- Firefox (optional, for HTML report screenshots)
Repository Structure
mycodo-hermes-skill/
├── SKILL.md # Hermes skill definition
├── LICENSE # MIT
├── CONTRIBUTING.md
├── requirements.txt
├── mycodo_skill/ # Python modules
│ ├── decision_engine.py # Core decision engine
│ ├── species_loader.py # YAML species config loader
│ ├── transition_detector.py # Auto-phase transitions
│ ├── phase_detector.py # Phase classification from sensors
│ ├── phase_config.py # Legacy Lion's Mane fallback
│ ├── followup_checker.py # 10-min follow-up verifier
│ └── verify_actuator.py # Testing utility
├── scripts/ # Shell scripts
│ ├── sensor-query.sh # Mycodo/InfluxDB/camera gateway
│ ├── mycodo-followup-wrapper.sh
│ └── archive-grow-cycle.sh
├── species/ # Species threshold configs (YAML)推奨ツール
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インストール
npx skillfish add setasoma/mycodo-hermes-skill