Skip to main content

The Agent Skills engine, as an MCP server.

Project description

FastSkills Banner

The Agent Skills engine — extracted, standalone, and universal.

PyPI Version Downloads Python Version License Agent Skills Standard


The Problem

Claude Code, GitHub Copilot, OpenAI Codex, and Cursor all have a skill engine built in — the agent discovers SKILL.md playbooks, reads them on demand, and follows structured instructions to produce consistent, high-quality output. That's why they can generate professional documents, presentations, and code without being told how every time.

But the skill engine is locked inside each product.

If you're building with LangChain, CrewAI, AutoGen, Smolagents, or any custom agent — you get nothing. No skill discovery, no progressive disclosure, no structured playbooks. You'd have to build the entire engine from scratch.

The Solution

FastSkills extracts the skill engine into a standalone MCP server. One command gives any agent the same capability:

uvx fastskills --skills-dir ./skills

That's it. Your agent can now discover, read, and execute any SKILL.md — the same open standard used by Claude Code, Copilot, Codex, OpenClaw, and nanobot.

No framework adoption. No code changes. No SDK integration. Just MCP.


Before & After

WITHOUT FastSkills:

  Claude Code ──── has skill engine ──── can use 40,000+ skills
  Copilot     ──── has skill engine ──── can use 40,000+ skills
  Codex CLI   ──── has skill engine ──── can use 40,000+ skills
  OpenClaw    ──── has skill engine ──── can use 40,000+ skills
  nanobot     ──── has skill engine ──── can use 40,000+ skills
  ─────────────────────────────────────────────────────────────
  LangChain   ──── nothing           ──── ✗
  CrewAI      ──── nothing           ──── ✗
  AutoGen     ──── nothing           ──── ✗
  Your agent  ──── nothing           ──── ✗


WITH FastSkills:

  Any agent   ──── FastSkills (MCP) ──── can use 40,000+ skills ✓

What's New

  • 2025-06-xx — v0.x.x: Initial release with 17 bundled skills and TUI chat interface.

Feature Showcase

Document Generation
Create professional PPTX, DOCX, PDF, and XLSX

Document generation demo
Design & Frontend
Generate themes, brand guidelines, and frontend designs

Design demo
Authoring & Content
Co-author docs, write internal comms, build web artifacts

Authoring demo
Developer Tools
Build MCP servers, create new skills, test web apps

Developer tools demo

Why Not Just Use OpenClaw or nanobot?

You can — and they're great. But they solve a different problem:

OpenClaw nanobot FastSkills
What it is Full AI assistant platform Lightweight AI assistant Standalone skill engine
To use skills Adopt the entire platform (Gateway, config, workspace) Install the framework, use its agent loop One command or one JSON block
Lock-in High — skills require OpenClaw runtime Medium — skills require nanobot agent None — standard MCP protocol
Works with your agent? No — you use OpenClaw's agent No — you use nanobot's agent Yes — any MCP client
Lines of code 430,000+ ~4,000 ~800
Install npm install -g openclaw && openclaw onboard --install-daemon pip install nanobot && nanobot onboard uvx fastskills --skills-dir ./skills

OpenClaw and nanobot are platforms — you adopt their agent, their runtime, their ecosystem. FastSkills is a building block — it gives your existing agent skill capabilities without replacing anything.


Quick Start

Connect any agent in 30 seconds

Add one block to your MCP client config (Claude Desktop, Cursor, VS Code, Windsurf, Goose, or any custom agent):

{
  "mcpServers": {
    "fastskills": {
      "command": "uvx",
      "args": ["fastskills", "--skills-dir", "~/.fastskills/skills"]
    }
  }
}

Your agent now has skill discovery, skill reading, and a full execution toolkit (bash, file creation, string replacement) — matching the tool surface that Claude Code provides natively.

What's uvx? It's a tool from uv that runs Python packages in isolated environments — no install step needed. Install it with curl -LsSf https://astral.sh/uv/install.sh | sh or brew install uv.

Or use the built-in TUI

# One-liner install
curl -sSL https://raw.githubusercontent.com/nj19257/FastSkills/main/install.sh | bash

# Start chatting
fastskills_cli

FastSkills TUI

On first launch you'll be prompted for your OpenRouter API key and model. The bundled 17 skills are automatically discovered.

Command What it does
/help Show all commands
/model Change AI model
/skills List available skills
/status Show connection info
Ctrl+H Toggle sidebar

How the Skill Engine Works

The same progressive disclosure pattern used by Claude Code, Copilot, and Codex:

 ┌──────┐    ┌──────┐    ┌──────┐    ┌────────┐    ┌─────────┐
 │ Scan │───►│Match │───►│ Read │───►│ Follow │───►│ Deliver │
 └──────┘    └──────┘    └──────┘    └────────┘    └─────────┘
  metadata    best fit    SKILL.md    run scripts    output
   ~100 tok   agent       full body   bash/create    consistent
   per skill  decides     on demand   on demand      quality
  1. Scanlist_skills returns names + descriptions (~100 tokens per skill)
  2. Match — The agent decides which skill fits the task
  3. Readview(path=...) reads the full SKILL.md into context
  4. Followbash_tool runs scripts, file_create writes output
  5. Deliver — Consistent, high-quality results every time

The agent only loads what it needs, when it needs it. No context window bloat.

System Prompt

FastSkills includes a gold-standard system prompt at prompt/gold_standard_prompt.yaml that teaches any agent the discover → read → execute workflow. Use it directly or reference it to build your own.


Architecture

FastSkills Architecture

┌─────────────────┐        MCP        ┌──────────────┐      filesystem     ┌──────────────┐
│   Your Agent    │◄────────────────►│  FastSkills   │◄──────────────────►│   skills/    │
│  (any MCP       │     protocol      │  MCP Server   │   read SKILL.md    │  ├── pptx/   │
│   client)       │                   │  (FastMCP)    │   run scripts      │  ├── docx/   │
└─────────────────┘                   └──────────────┘                     │  ├── pdf/    │
                                                                           │  └── ...     │
                                                                           └──────────────┘
Tool Purpose
list_skills Discover available skills with name, description, and SKILL.md path
view Read files (including SKILL.md), list directories, inspect images
bash_tool Execute shell commands and skill scripts (120s timeout)
file_create Create output files with content
str_replace Make targeted string replacements in existing files

Bundled Skills (17)

Category Skills
Documents pptx · docx · pdf · xlsx
Design theme-factory · brand-guidelines · canvas-design · frontend-design · algorithmic-art
Authoring doc-coauthoring · internal-comms · web-artifacts-builder · slack-gif-creator
Developer mcp-builder · skill-creator · webapp-testing · duckduckgo-websearch

Add Your Own

Drop a folder with a SKILL.md into your skills directory. FastSkills picks it up automatically:

~/.fastskills/skills/
├── pptx/
│   └── SKILL.md
├── my-custom-skill/
│   ├── SKILL.md
│   ├── scripts/
│   │   └── generate.py
│   └── references/
│       └── style-guide.md
└── ...
Example SKILL.md
---
name: api-documentation
description: Generate consistent API documentation following team standards.
  Use when writing docs for REST endpoints, SDKs, or internal APIs.
---

# API Documentation Skill

## When to Use
Use this skill when the user asks to document an API, generate endpoint
references, or create SDK documentation.

## Instructions
1. Read the source code or endpoint definitions
2. Extract parameters, return types, and error codes
3. Generate documentation following the template in ./references/template.md
4. Include code examples for each endpoint

Skill Sources

The MCP server loads skills from a single directory specified by --skills-dir. The TUI (fastskills_cli) auto-resolves from two locations:

Location Used by Description
--skills-dir path MCP server The single source of skills for the MCP server (required flag)
Repo-bundled skills/ TUI 17 bundled skills shipped with FastSkills
~/.fastskills/skills/ TUI User-global skills auto-discovered by the TUI

You can also use skills from Anthropic's skills repo, ClawHub (3,000+ community skills), or any community source.


The Agent Skills Ecosystem

FastSkills uses the same open standard adopted across the industry:

Platform Skills Support How
Claude Code ✅ Native .claude/skills/ directory
GitHub Copilot ✅ Native .github/skills/ directory
OpenAI Codex CLI ✅ Native Same SKILL.md format
Cursor ✅ Native Built-in skill engine
OpenClaw ✅ Native AgentSkills-compatible folders
nanobot ✅ Native Bundled + custom skills
LangChain / CrewAI / AutoGen ❌ → ✅ Via FastSkills
Any MCP-compatible agent ❌ → ✅ Via FastSkills

Skills are portable. Write once, use everywhere.


Configuration

Flag Description Default
--skills-dir Root directory containing skill folders (required)
--workdir Working directory for command execution and file output Current directory
# Start the MCP server
uvx fastskills --skills-dir /path/to/skills

# With a working directory for file output and command execution
uvx fastskills --skills-dir /path/to/skills --workdir /path/to/output

Tip: Pair FastSkills with a web search MCP server (like mcp-server-fetch) so your agent can research topics alongside executing skills. Skills handle the "how," web search handles the "what."


What's Next

  • ClawHub Integration — Browse, search, and install from ClawHub (3,000+ community skills) without leaving your agent

Contributing

Contributions welcome — new skills, core improvements, or docs:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-skill)
  3. Commit your changes
  4. Open a Pull Request

License

MIT License — see LICENSE for details.


Acknowledgments


The skill engine is locked inside coding agents. FastSkills sets it free.
⭐ Star this repo if FastSkills is useful to you

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fastskills-0.1.3.tar.gz (4.2 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fastskills-0.1.3-py3-none-any.whl (34.0 kB view details)

Uploaded Python 3

File details

Details for the file fastskills-0.1.3.tar.gz.

File metadata

  • Download URL: fastskills-0.1.3.tar.gz
  • Upload date:
  • Size: 4.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.17

File hashes

Hashes for fastskills-0.1.3.tar.gz
Algorithm Hash digest
SHA256 15b0e704e40ee319e96428917461353a2abf509ebe832f153539b1ce90bba76e
MD5 d690b0f802b42f0e2d451df0ed22636e
BLAKE2b-256 3ffde0b9af8b081c234a9ec92e6c799a771fd96b6a9012aba313917262136aee

See more details on using hashes here.

File details

Details for the file fastskills-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: fastskills-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 34.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.17

File hashes

Hashes for fastskills-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 07712400a3726ed75aedd64fcca39097326b14ca4713858bbd620d189ef6b9d0
MD5 2e53386f8aa4213e2f4512f7685edc91
BLAKE2b-256 3c26e2e082e279a367b383b76ccfd7cf147b143289938e80bf75d4bd1fabdbe4

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page