Skill Exporter

Transform Clawdbot skills into standalone, deployable microservices.

Workflow

Clawdbot Skill (tested & working)
         ↓
    skill-exporter
         ↓
Standalone Microservice
         ↓
Railway / Fly.io / Docker

Usage

Export a skill

python3 {baseDir}/scripts/export.py \
  --skill ~/.clawdbot/skills/instagram \
  --target railway \
  --llm anthropic \
  --output ~/projects/instagram-service

Options

Flag	Description	Default
--skill	Path to skill directory	required
--target	Deployment target: railway, fly, docker	docker
--llm	LLM provider: anthropic, openai, none	none
--output	Output directory	./<skill-name>-service
--port	API port	8000

Targets

railway — Generates railway.json, optimized Dockerfile, health checks fly — Generates fly.toml, multi-region ready docker — Generic Dockerfile, docker-compose.yml

LLM Integration

When --llm is set, generates llm_client.py with:

• Caption/prompt generation
• Decision making helpers
• Rate limiting and error handling

What Gets Generated

<skill>-service/
├── Dockerfile
├── docker-compose.yml
├── api.py              # FastAPI wrapper
├── llm_client.py       # If --llm specified
├── requirements.txt
├── .env.example
├── railway.json        # If --target railway
├── fly.toml            # If --target fly
└── scripts/            # Copied from original skill
    └── *.py

Requirements

The source skill must have:

• SKILL.md with valid frontmatter
• At least one script in scripts/
• Scripts should be callable (functions, not just inline code)

Post-Export

1. Copy .env.example to .env and fill in secrets
2. Test locally: docker-compose up
3. Deploy: railway up or fly deploy