Toolbox for AI agent skills: scaffold, lint, pack, install, and serve SKILL.md skills
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.

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
new — scaffold a spec-compliant skill folder in one commandlint — 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 platformsinstall — install from a folder or any git URL into
~/.claude/skills (or your own directory)list / remove — manage your installed skill librarymcp — a zero-dependency MCP server (stdio, JSON-RPC 2.0) that
exposes list_skills, read_skill, and lint_skill tools to any client# 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
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:
| Tool | What it does |
|---|---|
list_skills | Discover installed skills with names + descriptions |
read_skill | Load the full SKILL.md instructions of one skill |
lint_skill | Validate a skill and get its quality score |
| Rule | Severity | Check |
|---|---|---|
| SEC001 | error | Leaked secrets: GitHub/AWS/OpenAI/Slack tokens, private keys, hardcoded credentials |
| SKILL001 | error | Invalid name: charset, length ≤ 64, reserved words (anthropic, claude) |
| SKILL002 | error | name does not match the folder name |
| SKILL003 | error | description longer than 1,024 characters |
| SKILL009 | error | metadata is not a string→string map |
| SKILL004 | warn | Vague description (won't trigger — describe what and when) |
| SKILL005 | warn | Body over ~500 lines (move detail into references/) |
| SKILL007 | warn | Folder typos: script/, reference/, docs/… |
| SKILL006 | · info | Very thin body — add steps and examples |
| SKILL008 | · info | Unknown frontmatter fields |
Every run ends with a 0–100 score and a letter grade, so you know when a skill is ready to publish.
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.
pip install pytest
pytest -v
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/
skillkit search — search community skill registriesskillkit doctor — prompt-injection heuristics (planned, not implemented yet)MIT — see the LICENSE file for details.
Source-derived launch command. Check the maintainer’s required arguments and credentials before running:
uvx skillkit-cliMerge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.
{
"mcpServers": {
"io-github-furkan708-skillkit": {
"command": "uvx",
"args": [
"skillkit-cli"
]
}
}
}Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.
Claude Desktop setup referenceskillkit-clipypiskillkit works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.