Skill Exporter

---

name: skill-exporter description: Export Clawdbot skills as standalone, deployable microservices. Use when you want to dockerize a skill, deploy it to Railway or Fly.io, or create an independent API service. Generates Dockerfile, FastAPI wrapper, requirements.txt, deployment configs, and optional LLM client integration. license: MIT compatibility: Requires python3. Works with any AgentSkills-compatible agent. metadata: author: MacStenk version: "1.0.0" clawdbot: emoji: "📦" requires: bins: - python3

---

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 | ./-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

-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

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 | ./-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

| 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 | ./-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