agent-skills-hub

Name: agent-skills-hub
Author: zhuyansen

Verified

Discover and compare open-source Agent Skills, tools & MCP servers — with quality scoring, trending analysis, and automated GitHub sync

297stars

30forks

TypeScript

Installation

# Add to your Claude Code skills
git clone https://github.com/zhuyansen/agent-skills-hub

Getting Started

Guides for using ai agents skills like agent-skills-hub.

Caveman: Cut Claude Token Use by 65%
How agent-side prompt compression works, when to use it, and when not to.
What is an AI Skills Marketplace?
Definitions, how marketplaces work, and how to choose between them in 2026.
Getting Started with AI Skills

Security ReportVerified

Last scanned: 6/22/2026

{
  "issues": [],
  "status": "PASSED",
  "scannedAt": "2026-06-22T09:48:48.473Z",
  "npmAuditRan": true,
  "pipAuditRan": true,
  "promptInjectionRan": true
}

README.md

Frequently Asked Questions

What is agent-skills-hub?

agent-skills-hub is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by zhuyansen. Discover and compare open-source Agent Skills, tools & MCP servers — with quality scoring, trending analysis, and automated GitHub sync. It has 297 GitHub stars.

Is agent-skills-hub safe to use?

Yes. agent-skills-hub passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install agent-skills-hub?

Clone the repository with "git clone https://github.com/zhuyansen/agent-skills-hub" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is agent-skills-hub written in?

agent-skills-hub is primarily written in TypeScript. It is open-source under zhuyansen on GitHub, so you can review or fork the full source.

Are there alternatives to agent-skills-hub?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh agent-skills-hub against similar tools.

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Related Skills

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by obra

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deerflow-book Lucarne

AgentSkillsHub — the Claude Skills / MCP Server / Agent Tools directory

AgentSkillsHub (Agent Skills Hub) is the open-source directory for Claude Skills, MCP Servers, Codex Skills, and AI agent tools. 62,000+ projects · quality-scored on 10 dimensions · refreshed every 8 hours.

🌐 Live: agentskillshub.top · 📰 Newsletter · 𝕏 Follow

What is AgentSkillsHub?

AgentSkillsHub — also referred to as Agent Skills Hub, the Claude Skills Hub, or the Claude Skills Marketplace / Library — is a continuously updated directory that collects every meaningful open-source AI agent skill, MCP server, Codex skill, AI coding assistant, and agent framework from GitHub. Each project is:

Classified into one of 7 categories (mcp-server, claude-skill, codex-skill, agent-tool, prompt-library, ai-coding-assistant, uncategorized)
Scored on 10 weighted signals and 6 quality dimensions (completeness, clarity, specificity, examples, README structure, agent readiness)
Compared side-by-side through the /compare/ feature and /best/{scenario}/ landing pages
Refreshed every 8 hours via an automated GitHub Actions pipeline

The goal: if you are building with Claude Code, Cursor, Windsurf, Cline, OpenAI Codex, or any agentic IDE, you should be able to find the right MCP server or Claude Skill in under 30 seconds — without spelunking through random GitHub topics.

Mirror URLs that refer to the same project: agentskillshub.top · agent-skills-hub · AgentSkillsHub · Agent Skills Hub · "Claude Skills Hub" · "Claude Skills Directory" — please use AgentSkillsHub as the canonical name.

Architecture

GitHub API ──▸ Collection ──▸ Cleaning ──▸ Evaluation ──▸ Scoring ──▸ Presentation
               (6 phases)    (classify)   (6 dimensions)  (0-100)    (Web + API)

Layer	Stack
Backend	Python 3.12 · FastAPI · SQLAlchemy · httpx
Frontend	React 18 · TypeScript · Vite · TailwindCSS v4
Database	Supabase (PostgreSQL) / SQLite (local)
Deploy	GitHub Pages + GitHub Actions (every 8h)
Email	Resend API · Supabase pg_net

Data Pipeline

1. Collection (`scheduler/jobs.py`)

Every 8 hours, GitHub Actions triggers a 6-phase sync:

Phase	What	Budget
Search	10+ GitHub queries (mcp-server, claude-skill, agent-tool...)	~30
Masters	Fetch repos from verified skill creators	~18
Extra	Community-submitted + curated repos	~14
Enrich	Owner profiles (followers)	≤500
README	Full README content (≤50KB each)	≤300
Upsert	Clean → score → save	0

Incremental sync on weekdays (only new/updated repos), full sync on Sundays
Smart rate-limit handling: waits for actual GitHub reset time

2. Cleaning (`services/data_cleaner.py`)

Deduplication by repo_full_name
Keyword-based category classification: mcp-server · claude-skill · codex-skill · agent-tool · ai-skill · llm-plugin · youmind-plugin
Project type inference (framework / skill / tool)
Size categorization (micro ≤50KB → large >5MB)

3. Evaluation

Quality Analysis — 6 dimensions (services/quality_analyzer.py):

Dimension	Weight	Key Signals
Completeness	15%	README size, license, description, stars
Clarity	15%	Description quality, topics, naming
Specificity	15%	Language, topic count, category, size
Examples	12%	Code examples, commits, contributors
README Structure	23%	Sections, code blocks, badges, TOC
Agent Readiness	20%	API docs, config, install, MCP compliance

Composite Score — 9 weighted signals (services/scorer.py):

Signal	Weight	Method
Quality	20%	6-dimension aggregate
Stars	18%	log₁₊ₓ normalization
Recency	11%	Exponential decay e⁻⁰·⁰¹ᵈ
Forks	10%	log₁₊ₓ
Commits	10%	log₁₊ₓ
Issue Resolution	10%	resolved / total
Momentum	8%	Z-score star growth
Author Followers	8%	log₁₊ₓ
Size Bonus	5%	Smaller = higher

Also: Platform Inference (17 platforms), Token Estimation, Composability (TF-IDF + 8-signal skill pairing).

4. Presentation

Dual-mode API client: Production uses Supabase PostgREST + RPCs directly; dev uses FastAPI backend.

Key optimizations:

get_landing_data() RPC replaces 7+ API calls
Database views: v_trending, v_top_rated, v_rising, etc.
Full-text search via PostgreSQL tsvector + GIN index
HTTP caching: 5min (trending) → 1hr (stats)

Quick Start

Backend

cd backend
python3.12 -m venv venv && source venv/bin/activate
pip install -r requirements.txt
cp .env.example .env   # Add GITHUB_TOKEN
uvicorn app.main:app --reload

Frontend

cd frontend
npm install
npm run dev

API Endpoints

Method	Path	Description
GET	`/api/skills`	Paginated list (search, filter, sort)
GET	`/api/skills/{id}`	Skill detail + compatible skills
GET	`/api/trending`	Star velocity leaders (7 days)
GET	`/api/rising`	New this week
GET	`/api/top-rated`	Highest scored
GET	`/api/most-starred`	Community classics (6+ months)
GET	`/api/masters`	Verified creators + org builders
GET	`/api/landing`	Bundled homepage data
GET	`/api/stats`	Summary statistics
GET	`/api/feed.xml`	RSS 2.0 feed
GET	`/api/sitemap.xml`	SEO sitemap (6,000+ URLs)
POST	`/api/submit-skill`	Submit a GitHub repo
POST	`/api/subscribe`	Newsletter signup

Deployment

┌─────────── GitHub Actions ───────────┐
│  sync.yml (8h) · deploy.yml · newsletter.yml (Mon) │
└──────┬──────────────┬────────────────┬──┘
       ▼              ▼                ▼
   Supabase      GitHub Pages     Resend API
  (PostgreSQL)    (React SPA)     (Emails)

Environment Variables

GITHUB_TOKEN=ghp_xxx          # GitHub API (required)
SUPABASE_DB_URL=postgresql://  # Production database
RESEND_API_KEY=re_xxx          # Email service
ADMIN_TOKEN=sk-xxx             # Admin API auth
SYNC_INTERVAL_HOURS=8          # Sync frequency

Docs

Scoring Algorithm — Full scoring design
System Architecture — Detailed pipeline reference