mcpField
S
skillkit

skillkit

Local
github.com/furkan708AI & Agents0Updated 9w ago

About skillkit

skillkit is a command-line toolbox for developers who create, maintain, and distribute Agent Skills in SKILL.md format. It scaffolds, validates, packages, and installs skills, and can serve a skill library through its built-in MCP server.

Key features

  1. 01Scaffold spec-compliant skills
  2. 02Check specification issues and security smells
  3. 03Package skills as ZIP files
  4. 04Install skills from folders or Git URLs
  5. 05List and remove installed skills
  6. 06Browse, read, and lint skills over MCP

Use cases

  1. 01Create and validate SKILL.md files for publication
  2. 02Find leaked secrets before shipping a skill
  3. 03Install skills from a Git repository
  4. 04Let MCP clients access a skill library on demand

MCP support

Its zero-dependency MCP server uses stdio to expose `list_skills`, `read_skill`, and `lint_skill`, letting MCP clients discover, read, and validate installed skills.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"furkan708-skillkit": {
"command": "uvx",
"args": [
"skillkit-cli"
]
}
}
}
Run commanduvx skillkit-cli

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypiskillkit-cli1.0.2

Tools

3

Saved tool list · updated 3w ago

This tool takes no parameters.

Details

From the project README

skillkit

Python License Tests CI Code style: ruff Types: mypy Dependencies

The toolbox for AI agent skills. Scaffold, lint, pack, and install SKILL.md skills — and serve your whole skill library to Claude Code, Cursor, and any MCP client with a built-in Model Context Protocol server.

skillkit terminal demo

Community audits found that the overwhelming majority of published SKILL.md files carry at least one "skill smell" — and a large share leak secrets. skillkit catches those before you ship.

Deep docs: Usage guide — lint rules reference, MCP patterns, CI usage · Architecture · Contributing · Changelog · Security

Features

  • new — scaffold a spec-compliant skill folder in one command
  • lint — validate against the Agent Skills spec plus security smells: leaked API keys, vague descriptions, oversized bodies, folder typos, and more (scored 0–100 with a grade)
  • pack — zip a skill for upload to skill-capable platforms
  • install — install from a folder or any git URL into ~/.claude/skills (or your own directory)
  • list / remove — manage your installed skill library
  • mcp — a zero-dependency MCP server (stdio, JSON-RPC 2.0) that exposes list_skills, read_skill, and lint_skill tools to any client
  • Zero dependencies — pure Python standard library
  • 76 tests, CI on Python 3.10 → 3.12

Quick start

# run without installing (uvx — pulls from PyPI on demand)
uvx --from skillkit-cli skillkit lint ./skills

# or install (installs the `skillkit` command)
pipx install skillkit-cli

# ...or from source
git clone https://github.com/furkan708/skillkit.git
cd skillkit && pip install .

# 1. create a skill
skillkit new commit-writer -d "Writes conventional commit messages from staged diffs. Use when the user asks to commit changes."

# 2. lint it (spec + security + quality)
skillkit lint commit-writer
# ✓ no issues found
# score: 100/100 (grade A) · 0 errors · 0 warnings · 0 notes

# 3. pack it for upload
skillkit pack commit-writer        # → commit-writer.zip

# 4. install it for Claude Code
skillkit install ./commit-writer   # → ~/.claude/skills/commit-writer

Serve your skills over MCP

Add skillkit to any MCP client config — Claude Code, Cursor, Windsurf, and every other MCP-compatible agent:

{
  "mcpServers": {
    "skillkit": { "command": "skillkit", "args": ["mcp"] }
  }
}

Your agent can now discover and read every installed skill on demand:

ToolWhat it does
list_skillsDiscover installed skills with names + descriptions
read_skillLoad the full SKILL.md instructions of one skill
lint_skillValidate a skill and get its quality score

What lint catches

RuleSeverityCheck
SEC001errorLeaked secrets: GitHub/AWS/OpenAI/Slack tokens, private keys, hardcoded credentials
SKILL001errorInvalid name: charset, length ≤ 64, reserved words (anthropic, claude)
SKILL002errorname does not match the folder name
SKILL003errordescription longer than 1,024 characters
SKILL009errormetadata is not a string→string map
SKILL004warnVague description (won't trigger — describe what and when)
SKILL005warnBody over ~500 lines (move detail into references/)
SKILL007warnFolder typos: script/, reference/, docs/…
SKILL006· infoVery thin body — add steps and examples
SKILL008· infoUnknown frontmatter fields

Every run ends with a 0–100 score and a letter grade, so you know when a skill is ready to publish.

CLI reference

skillkit new <name> -d <description> [--dir DIR]   scaffold a skill
skillkit lint <path> [--json] [--strict]           validate a skill
skillkit pack <path> [-o FILE.zip]                 zip for upload
skillkit install <path|git-url> [--agent claude|project] [--dir DIR]
skillkit list [--agent ...] [--dir DIR] [--json]   show installed skills
skillkit remove <name> [--dir DIR]                 uninstall a skill
skillkit mcp [--dir DIR]                           serve skills over MCP

Built on the open Agent Skills specification — the same format supported by 40+ platforms including Claude, OpenAI Codex, and GitHub Copilot.

Tests

pip install pytest
pytest -v

Project Structure

skillkit/
├── skillkit/
│   ├── frontmatter.py   # minimal YAML frontmatter parser
│   ├── model.py         # skill loading (Agent Skills spec)
│   ├── linter.py        # rules, security smells, 0-100 score
│   ├── scaffold.py      # new + pack
│   ├── installer.py     # install / list / remove (folder or git)
│   ├── mcp_server.py    # zero-dependency MCP stdio server
│   └── cli.py           # command-line interface
└── tests/

Roadmap

  • skillkit search — search community skill registries
  • More install targets (Codex, Copilot CLI paths as they standardize)
  • skillkit doctor — prompt-injection heuristics (planned, not implemented yet)

License

MIT — see the LICENSE file for details.

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.