AI agents를 위한
Skill layer.
AI agent가 올바른 재사용 가능 Skill을 자동으로 찾고, 비교하고, 설치하게 합니다.
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
작업을 설명하면 안전한 Skill 계획을 받습니다.
API는 Agent가 실행하기 전에 선택 Skill, 대안, 정책 판단, 감사 메모, 설치 계획을 반환합니다.
작업 적합도
96/100
웹 추출 워크플로에 추천
유지보수
Active
Stars, 최신성, 메타데이터, 저장소 상태
설치 검토
Ready
Agent 실행 전 안전한 다음 단계
Why OpenAgentSkill
Agent를 임의의 디렉터리로 보내지 마세요.
Skill 레지스트리는 Agent가 신뢰할 수 있을 때 유용합니다. OpenAgentSkill은 흩어진 GitHub 프로젝트를 정렬 가능하고 감사 가능하며 설치 가능한 능력으로 바꿉니다.
- 01
작업에서 Skill로
Agent는 카테고리 페이지가 아니라 의도에서 시작합니다. 레지스트리는 작업을 선택 Skill, 대안, 적합 이유로 매핑합니다.
- 02
설치 전 안전성
Stars, 최신성, 품질 점수, 위험, 준비 상태가 Agent가 실행할 명령과 함께 제공됩니다.
- 03
사람은 탐색, Agent는 API
사람은 인덱스를 탐색하고 Agent는 resolve, recommendation, skill endpoint로 같은 레지스트리를 호출합니다.
Registry response
한 번의 호출로 정렬된 설치 경로.
{
"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
의도와 설치 사이의 네 계층.
OpenAgentSkill은 정적 목록이 아니라 Agent가 파일 작성, 브라우저 실행, 외부 코드 설치 전에 호출할 수 있는 레지스트리 루프입니다.
Indexed
21,508
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
OpenAgentSkill이 다른 Skill 플랫폼과 다른 점.
일반 디렉터리는 사람이 탐색하기 위한 것입니다. OpenAgentSkill은 AI Agent가 올바른 Skill을 자동으로 발견, 비교, 설치하도록 설계되었습니다.
| 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.