La capa de skills
para AI agents.
Permite que tu AI agent encuentre, compare e instale automaticamente el skill reutilizable correcto.
Daily leaderboards
Skills moving now, ranked with evidence.
Daily snapshots combine capped activity signals, quality, trust, GitHub adoption, and real agent outcomes.
- 1design-creative
Frontend Design
7 views, 0 install copies, and 13 compares across 2 active days, with capped anti-spam weighting and 2 agent outcomes.
170K stars21 events / 2d - 2design-creative
Taste Skill: Anti-Slop Frontend
9 views, 1 install copies, and 15 compares across 2 active days, with capped anti-spam weighting and 2 agent outcomes.
78K stars29 events / 2d - 3agent-frameworks
Firecrawl
1 views, 0 install copies, and 12 compares across 2 active days, with capped anti-spam weighting and 2 agent outcomes.
139K stars13 events / 2d - 4data-analysis
D3
1 views, 0 install copies, and 33 compares across 2 active days, with capped anti-spam weighting and 1 agent outcomes.
113K stars34 events / 2d - 5agent-skills
Agent Skills
3 views, 0 install copies, and 25 compares across 2 active days, with capped anti-spam weighting and 1 agent outcomes.
88K stars28 events / 2d
Agent resolve
Describe la tarea. Recibe un plan de skill seguro.
La API devuelve un skill elegido, alternativas, decision de politica, notas de auditoria y plan de instalacion antes de que actue el agent.
Ajuste de tarea
96/100
Recomendado para flujos de extraccion web
Mantenimiento
Active
Stars, frescura, metadatos y salud del repo
Revision de instalacion
Ready
Siguientes pasos seguros antes de ejecutar
Why OpenAgentSkill
No envies agentes a directorios aleatorios.
Una registry de skills solo sirve si un agent puede confiar en ella. OpenAgentSkill convierte proyectos dispersos de GitHub en capacidades ordenadas, auditables y listas para instalar.
- 01
De tarea a skill
Los agents empiezan con intencion, no con paginas de categorias. La registry mapea el trabajo a un skill elegido, alternativas y razones de ajuste.
- 02
Seguridad antes de instalar
Stars, frescura, quality score, riesgos y readiness aparecen junto al comando que ejecutara el agent.
- 03
UI para humanos, API para agents
Las personas exploran el indice; los agents llaman la misma registry via resolve, recommendation y skill endpoints.
Registry response
Una llamada, ruta de instalacion ordenada.
{
"task": "analyze stock news",
"agent_decision": {
"recommended_skill": "Last30days Skill",
"install_command": "npx skills add ...",
"why_recommended": [
"matches research workflow",
"strong Trust Score",
"audit warnings included"
],
"risk_summary": {
"safety": "review before install",
"notes": ["network access", "verify sources"]
}
}
}Architecture
Cuatro capas entre intencion e instalacion.
OpenAgentSkill no es otra lista estatica; es un loop de registry que un agent puede llamar antes de escribir archivos, abrir navegadores o instalar codigo externo.
Indexed
21,471
Signals
Fit · Risk
Surface
API · UI
- 01
Intent capture
A human or upstream agent describes the job in natural language.
Task · Agent · ContextIntent - 02
Recommendation engine
rankerSkills are ranked by workflow fit, maintenance, stars, and audit signals.
Fit · Quality · FreshnessRank - 03
Skill trust profile
Each candidate gets readiness notes, install commands, and review prompts.
Risk · Install · EvidenceAudit - 04
Agent install path
The registry returns the next action an agent can safely execute.
Codex · Claude Code · CursorInstall
Quickstart
From task description to install command.
- 01
Ask for a skill path
Resolve the task into one selected skill, alternatives, safety score, and install plan.
POST /api/agent/resolve - 02
Inspect the trust profile
Review fit, repository health, risks, and install readiness.
GET /api/agent/skills/crawl4ai - 03
Install in an agent workflow
Copy the command or hand it to Codex, Claude Code, Cursor, or a custom agent.
GET /api/skills/crawl4ai/install?format=text - 04
Automate discovery
Use the API as the registry layer behind your own agent runtime.
curl "https://www.openagentskill.com/api/agent/resolve?task=review+pull+requests&agent=codex"
Compare
Como OpenAgentSkill se diferencia de otras plataformas.
La apuesta es simple: los directorios normales son para humanos. OpenAgentSkill esta construido para que un AI agent descubra, compare e instale el skill correcto automaticamente.
| Feature | OpenAgentSkill | skills.sh | agentskills.io | Native docs |
|---|---|---|---|---|
| Primary job | Recommend, compare, and install skills from one registry | Browse and install reusable agent skills | Define the open skill format and learning path | Explain skills inside each native agent platform |
| Agent-facing API | Yes - task-to-skill recommendations for agents | Directory and install workflow | Spec and documentation first | Platform-specific APIs and docs |
| Cross-agent positioning | Codex, Claude Code, Cursor, MCP-compatible agents, and custom tools | Open agent skills ecosystem | Open format for extending agents | Best for the vendor platform |
| Trust and audit signals | Stars, quality score, readiness notes, install review | Directory metadata | Metadata guidance in SKILL.md | Native platform controls |
| Best for | Letting an agent find the right skill automatically | Finding installable skills quickly | Learning or authoring the standard | Using skills in one product |
Comparison is based on each project's public positioning and documentation. The point is not that one project replaces another; OpenAgentSkill focuses on the registry and recommendation layer agents can call.
Workflow starts
Start from the job your agent needs to do.
Web scraping
Monitor pricing and extract tables
Coding agents
Inspect repos, patch bugs, verify changes
RAG workflows
Turn documents into grounded answers
Workflow automation
Connect repeated ops across tools
Skill layer
Registry for humans. Skill layer for agents.
Browse when you are exploring. Call the recommendation API when your agent needs to pick, compare, and install a skill automatically.