skills-registry 0.5.17

GitHub-backed skill registry: `skills-registry init` bootstraps a personal registry repo, `skill-registry-mcp` serves it over MCP, and the `skill-registry` Go CLI manages it.

skills-registry

One GitHub repo, every AI agent. Skills fetched on demand — not auto-loaded into every startup context.

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What it does

Your AI tools — Claude Code, Cursor, Codex, Goose, Windsurf, all of them — auto-load every skill you've installed into the agent's startup context. That's tokens you pay for whether the agent uses the skill or not.

skills-registry flips the model: skills live in one GitHub repo you own, and agents fetch them on demand through an MCP server. The only thing each agent auto-loads is a tiny pointer file that teaches it how to fetch the rest.

You get:

• 🪶 Lighter agent startup. A directory of SKILL.md files no longer balloons every conversation's context window. Agents pull what they need, when they need it.
• 🏠 One home for your skills. No more keeping ~/.claude/skills, ~/.cursor/skills, and ~/.factory/skills in sync by hand. Edit once, every agent sees it.
• 🚀 Share and version like code. Your registry is a Git repo. Branch it, PR it, fork your teammate's, restore old versions, the works.

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What's a "skill"?

A skill is a folder containing a SKILL.md (Markdown with optional YAML frontmatter) plus any supporting files the agent might need.

---
name: PDF Processing
description: Extract and summarize PDF documents
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# PDF Processing

When the user asks about a PDF, do the following:
1. Read the file with the pdf-text tool
2. Summarize section by section
...

That's it — one file, plus whatever reference docs or examples the agent should be able to see. Most modern AI coding tools already understand this format; skills-registry lets you keep them all in one place.

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Quick start

You need: GitHub CLI installed and authenticated (gh auth status should succeed) and git on PATH (only required the first time, for the bulk push). No Python or uv required.

curl -fsSL https://raw.githubusercontent.com/anand-92/skills-registry/main/install.sh | sh
skill-registry

The installer drops the skill-registry Go binary into ~/.local/bin/. The bare skill-registry invocation routes you to the right place automatically:

• First-time users land in the onboarding wizard (alt-screen TUI). Steps: scan dot-folders → pick repo name/visibility → push every skill with a single git push → pick agents to wire up → optionally delete the now-redundant local copies → install the skill-registry-mcp entry point → print the MCP JSON snippet.
• Returning users land in the dashboard hub with cards for Browse / Sync / Add / Publish / Remove / Settings.
• Piped / --json invocations print usage text instead of starting a TUI (so the binary is safe to drop into scripts).

The wizard auto-installs skill-registry-mcp (the Python FastMCP server) via uv tool install → pipx install → pip install --user, in that order. The first one that succeeds wins. Total failure prints a manual hint and continues — you'll still get the bootstrap, you'll just have to install the entry point yourself before the MCP server can launch. Opt out entirely with SKILLS_SKIP_INSTALL=1.

After it finishes, paste the printed JSON into your MCP client config, reload, and ask your agent something like:

"What skills do I have available?" "Get the code-review skill and use it on this PR."

The agent calls list_skills and get_skill automatically — you never touch the MCP tools directly.

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Daily use

Once you're set up, run a bare skill-registry to open the dashboard hub, or use the explicit subcommands:

What you want	Command
Open the dashboard	skill-registry
Browse what's in your registry	skill-registry list
Pull one skill into the current folder	skill-registry get <slug>
Push skills sitting in .claude/skills etc. into the registry	skill-registry sync
Pull a skill from someone else's repo into yours	skill-registry add <owner/repo>
Publish a new skill from a local folder	skill-registry publish <path>
Delete a skill from the registry + cache + agent dot-folders	skill-registry remove <slug>
Re-run the wizard / bootstrap (idempotent)	skill-registry bootstrap

Most users only ever touch list, get, and publish. The TUI is fuzzy-filterable; press / to search and Enter to preview.

remove: delete a skill end-to-end

skill-registry remove code-review

remove is destructive. It deletes the slug from three places in one go:

1. The GitHub registry repo — single atomic commit via the Git Data API.
2. The Python MCP server's local cache (~/.cache/skills-mcp/skills/<slug>/ + <slug>.meta.json).
3. Every known AI tool dot-folder copy (~/.claude/skills/<slug>/, ~/.factory/skills/<slug>/, .agents/skills/<slug>/, …).

Interactive runs surface a confirmation prompt before any of it fires. Pass --yes to skip the prompt for scripted use, or --json (which implies --yes) for machine-readable output. Removing a slug that isn't in the registry exits 1 cleanly — nothing destructive runs.

Programmatic use — --json

Every subcommand accepts a persistent --json flag. With it set, the CLI suppresses every TUI and prompt and emits a single JSON payload to stdout. Errors land as {"error": "..."} and the process exits non-zero. This is the right flag when an agent (or any script) is driving the binary itself.

Command	Payload shape
skill-registry list --json	[{"slug", "name", "description"}, …]
skill-registry get <slug> --json	{"slug", "path"} (on-disk dest)
skill-registry publish <path> --json	{"slug", "sha", "url"}
skill-registry sync --json	{"pushed": [...slugs], "skipped": [...slugs]}
skill-registry remove <slug> --json	{"slug", "repo", "sha", "removed_from": [...]}

Destructive commands (sync, remove) auto-promote --yes when --json is set, so a piped invocation never hangs on a Bubble Tea prompt that can't render.

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vs. the alternatives

	Local dot-folders	Dotfiles repo	skills-registry
One home for all your agents	❌ duplicated	✅	✅
Fetched on demand (no startup tokens)	❌	❌	✅
Versioned + branchable	❌	✅	✅
Works in every MCP client	partial	❌	✅
Share / fork between users	❌	clunky	✅ (just clone the repo)
No shell or SSH config needed	✅	❌	✅

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Configuration

Most people never touch these — the wizard sets up sensible defaults. Override them via your shell or MCP client environment when you need to:

Variable	Default	What it does
SKILLS_REGISTRY	(from config)	Point at a different registry for one command: owner/repo or owner/repo@branch. Great for browsing a teammate's.
SKILLS_LOG_LEVEL	INFO	Bump to DEBUG if something's misbehaving.
SKILLS_SKIP_INSTALL	unset	Set to 1 to keep the wizard from auto-installing skill-registry-mcp. Useful when you manage the entry point yourself.
SKILLS_REGISTRY_VERSION	latest	Pin install.sh to a specific release tag (v0.5.1, etc.).
SKILLS_BIN_DIR	~/.local/bin	Where install.sh drops the skill-registry binary.
XDG_CONFIG_HOME / XDG_CACHE_HOME	OS default	Where the registry config and skill cache live.

The registry repo URL itself is stored in ~/.config/skills-mcp/registry.toml.

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Troubleshooting

"gh not found" or exit code 3

Install GitHub CLI from https://cli.github.com/ and run gh auth login. skills-registry deliberately uses gh for every GitHub call — no SSH key shenanigans, no git config user.email required — so it has to be on your PATH (or in ~/.local/bin, /opt/homebrew/bin, /usr/local/bin, or /usr/bin).

"No registry configured"

You haven't run the wizard yet, or your config file at ~/.config/skills-mcp/registry.toml is missing. Run skill-registry (which opens the onboarding wizard the first time), or set SKILLS_REGISTRY=owner/repo directly.

The MCP server doesn't show up in my client

Make sure you pasted the JSON snippet the wizard printed at the end of onboarding (the absolute path to skill-registry-mcp matters — desktop MCP clients don't inherit your shell PATH). Then fully restart the client (not just reload). If the wizard couldn't auto-install the entry point, install it yourself with uv tool install skills-registry or pipx install skills-registry and re-run skill-registry to refresh the printed path.

Multiple GitHub accounts

skills-registry uses whichever account gh auth status says is active. Use gh auth switch before running skill-registry to pick the right one.

"git not found" during onboarding

The first-time bulk push uses a single git push to dodge GitHub's secondary rate limit. Install git (macOS: brew install git; Linux: apt install git / dnf install git; Windows: https://git-scm.com/downloads) and re-run skill-registry. After onboarding, git is no longer needed — the MCP server and the single-skill publish / remove commands all route through gh api.

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Manual MCP client config

The wizard prints platform-correct JSON at the end of onboarding, but if you prefer to set it up by hand:

Claude Code / Claude Desktop / Cursor / VS Code (mcp.json)

{
  "mcpServers": {
    "skill-registry": {
      "command": "/Users/you/.local/bin/skill-registry-mcp"
    }
  }
}

Codex (~/.codex/config.toml)

[mcp_servers.skill-registry]
command = "/Users/you/.local/bin/skill-registry-mcp"

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Project status

skills-registry is at v0.5 — usable day-to-day but pre-1.0. The MCP tool surface (list_skills, get_skill, publish_skill) is stable. The CLI commands are stable. Internals may shift between minor versions; pin to a specific version if that worries you.

Found a bug? Have an idea? Open an issue. PRs welcome — see CONTRIBUTING.md.

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More

• 📖 docs/registry.md — architecture deep dive (Git Data API, caching, atomic publish)
• 🛡️ SECURITY.md — threat model and reporting
• 🤖 AGENTS.md — contributor notes for AI assistants working in this repo

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Apache-2.0 · made by @anand-92