🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking like caveman
GitHub-native skill catalog for Claude Code teams
Agent Skill Harbor helps teams collect, publish, and audit AI agent skills across repositories. It runs as a serverless web app with a collector runtime, then commits the catalog data back to Git so the skill library stays in version control.

Builders who want a private, shared skill catalog for Claude Code and other agents.
You can keep team skills organized, reviewed, and traceable without managing a separate database.
What it does
Skill cataloging
Collects and publishes agent skills from multiple repositories into one catalog.
Governance labels
Lets you mark skills as recommended, discouraged, or prohibited.
Provenance tracking
Tracks copied or installed skills back to their source.
Skill scanning
Includes `builtin.audit-skill-scanner` to inspect collected skills for safety issues.
Slack summaries
Includes `builtin.notify-slack` to send post-collection updates.
GitHub-native storage
Stores collected data in `data/` and commits it back through GitHub Actions.
How to get it
- 1Daily project operations are exposed through the generated root scripts
pnpm collect pnpm post-collect pnpm dev pnpm build pnpm preview
- 2Optional runtime files are scaffolded with harbor setup
harbor setup example-user-defined-plugin harbor setup builtin.audit-promptfoo-security harbor setup builtin.audit-skill-scanner
README
Agent Skill Harbor
Agent Skill Harbor is a skill management platform for teams and organizations.
It helps teams collect, share, audit, and publish AI agent skills across repositories, with provenance tracking, governance support, and safety checks built in.
It is designed to be serverless, DB-less, and Git- and GitHub-native, because skills are mostly text artifacts that already fit naturally in Git.
Screenshots
| Card View | List View |
|---|---|
![]() | ![]() |
Stats View

Graph View

Features
- Skill cataloging: collect and publish AI agent skills across repositories
- Governance: mark skills as recommended, discouraged, or prohibited
- Provenance: track copied or installed skills back to their origin
- Skill analysis:
builtin.audit-skill-scanneranalyzes collected skills and audits safety - Slack notification:
builtin.notify-slacksends post-collection summaries
Technical Highlights
- Serverless: the catalog UI is a prerendered static web app
- DB-less & Git-native: collected data is stored in
data/as YAML/JSON and committed back to Git - GitHub-native: data is updated with GitHub Actions and hosted on GitHub Pages
Demo site:
Quick Start
npx agent-skill-harbor init my-skill-harbor
cd my-skill-harbor
pnpm install
pnpm install --dir collector
# edit .env and set GH_ORG
gh auth login && GH_TOKEN=$(gh auth token) pnpm collect
# Or edit .env and set GH_TOKEN, then run:
# pnpm collect
pnpm dev
pnpm install installs the root package (agent-skill-harbor) for CLI + web.
pnpm install --dir collector installs the collector runtime used by pnpm collect and pnpm post-collect.
CLI Commands
When installed, the main CLI is available as harbor or agent-skill-harbor.
| Command | Description |
|---|---|
harbor init [dir] | Scaffold a new project |
harbor setup <plugin-id> | Scaffold optional plugin runtime files |
Daily project operations are exposed through the generated root scripts:
pnpm collect
pnpm post-collect
pnpm dev
pnpm build
pnpm preview
Organization Setup
- Create a new project with
npx agent-skill-harbor init. - Push it to a private repository in your organization.
- Configure
GH_TOKENas a GitHub Actions secret. - Enable GitHub Pages or Cloudflare Pages.
- Run the generated
CollectSkillsworkflow once.
The generated CollectSkills workflow is a thin caller pinned to Harbor's reusable workflow at wf-v0.
Inside the reusable workflow:
collectinstalls onlycollector/core dependencies and runs collectionpost_collectrestores the collected artifact, installscollector/core dependencies again, then installs only enabled optional plugin manifests- the final
data/directory is committed back to the repository
This keeps GitHub collection and optional post-collect dependencies structurally separate.
See Organization Setup for details.
Project Structure
my-skill-harbor/
├── .github/workflows/
│
├── config/
│ ├── harbor.yaml # General application settings
│ └── governance.yaml # Additional governance settings
│
├── collector/ # Batch processing for skill collection
│ ├── package.json
│ └── plugins/
│ └── <plugin-id>/ # Per-plugin manifests and code
│
├── data/
│ ├── assets/
│ ├── collects.yaml # History of skill collection runs
│ ├── plugins/ # Outputs produced by each plugin
│ ├── skills.yaml # Index of collected skills
│ └── skills/ # Cached files for collected skills
│
├── .env
│
├── guide/
│
└── package.json # Manifest for the web UI
Notes:
- root
package.jsondepends only onagent-skill-harbor collector/package.jsonis a Harbor-managed runtime manifest foragent-skill-harbor-collector- optional plugin manifests and example user-defined plugins live under
collector/plugins/<plugin-id>/
Post-Collect Plugins
Built-in plugins are enabled from config/harbor.yaml.
Examples:
builtin.detect-driftbuiltin.notify-slackbuiltin.audit-promptfoo-securitybuiltin.audit-skill-scanner
Optional runtime files are scaffolded with harbor setup:
harbor setup example-user-defined-plugin
harbor setup builtin.audit-promptfoo-security
harbor setup builtin.audit-skill-scanner
Generated files go under collector/plugins/<plugin-id>/.
See Post-Collect Plugins.
Documentation
- Organization Setup
- Skill Catalog Guide
- Post-Collect Plugins
- Governance Guide
- Local Development
- Release
FAQ
Is it okay to store this much data in Git?
Yes. Harbor mainly stores text data such as YAML, JSON, Markdown, and cached skill files. It does not assume large multimedia assets like images or videos, and the total volume is usually limited enough that Git's compression works well.
GitHub's official documentation says repositories should ideally stay under 1 GB, and keeping them under 5 GB is strongly recommended. In Harbor's case, reaching that scale is highly unlikely unless you intentionally store large non-text assets or collect an unusually large amount of unrelated data.
See GitHub Docs: About large files on GitHub
You say this is for teams and organizations. Can I use it personally?
Yes, absolutely. You can use Harbor to collect, manage, and catalog skills across your own repositories.
The main caveat is hosting. For personal use, GitHub Pages cannot be private, so you would likely want to host the generated site somewhere else you control securely. If there is enough demand, the documentation and workflows can be expanded to support that path more explicitly.
Or you may simply decide to publish your own skill catalog openly and not worry about that. That is entirely up to you.
Can I add custom properties to the YAML frontmatter in SKILL.md?
Yes. The Agent Skills specification is shared across agents, but there is no restriction on YAML frontmatter keys that are not defined by the standard. In practice, agents often carry their own custom properties, and unknown properties are generally ignored.
Also, the _from property used by Harbor typically consumes only around 10 to 20 tokens. Even if a project loads dozens of skills, the impact is usually negligible.
License
MIT
Files in the repo
- .claude
- .github
- .storybook
- bin
- collector
- docs
- scripts
- shared
- src
- static
- templates
- .gitignore
- .prettierignore
- .prettierrc
- CHANGELOG_ja.md
- CHANGELOG.md
- components.json
- eslint.config.js
- LICENSE
- package.json
- pnpm-lock.yaml
- pnpm-workspace.yaml
- README_ja.md
- README.md
- svelte.config.js
- tsconfig.cli.json
- tsconfig.json
- tsup.config.ts
- vite.config.ts
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