Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
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.
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.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Transform Clawdbot skills into standalone, deployable microservices.
Clawdbot Skill (tested & working) โ skill-exporter โ Standalone Microservice โ Railway / Fly.io / Docker
python3 {baseDir}/scripts/export.py \ --skill ~/.clawdbot/skills/instagram \ --target railway \ --llm anthropic \ --output ~/projects/instagram-service
FlagDescriptionDefault--skillPath to skill directoryrequired--targetDeployment target: railway, fly, dockerdocker--llmLLM provider: anthropic, openai, nonenone--outputOutput directory./<skill-name>-service--portAPI port8000
railway โ Generates railway.json, optimized Dockerfile, health checks fly โ Generates fly.toml, multi-region ready docker โ Generic Dockerfile, docker-compose.yml
When --llm is set, generates llm_client.py with: Caption/prompt generation Decision making helpers Rate limiting and error handling
<skill>-service/ โโโ Dockerfile โโโ docker-compose.yml โโโ api.py # FastAPI wrapper โโโ llm_client.py # If --llm specified โโโ requirements.txt โโโ .env.example โโโ railway.json # If --target railway โโโ fly.toml # If --target fly โโโ scripts/ # Copied from original skill โโโ *.py
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)
Copy .env.example to .env and fill in secrets Test locally: docker-compose up Deploy: railway up or fly deploy
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Largest current source with strong distribution and engagement signals.