Die Skill-Schicht
fur AI agents.
Lass deinen AI agent automatisch den richtigen wiederverwendbaren Skill finden, vergleichen und installieren.
Daily leaderboards
Skills moving now, ranked with evidence.
Daily snapshots combine capped activity signals, quality, trust, GitHub adoption, and real agent outcomes.
- 1web-automation
Scrapling
32 views, 2 install copies, and excellent quality signals.
70K stars507 events - 2data-analysis
Data Science For Beginners
3 views, 0 install copies, and 4 compares across 1 active days, with capped anti-spam weighting and 1 agent outcomes.
36K stars7 events / 1d - 3coding-agents
Gpt Pilot
30 views, 0 install copies, and excellent quality signals.
34K stars97 events - 4agent-frameworks
Claude Code Best Practice
23 views, 3 install copies, and excellent quality signals.
61K stars76 events - 5ml-automation
Ray
34 views, 1 install copies, and excellent quality signals.
43K stars81 events
Agent resolve
Beschreibe die Aufgabe. Erhalte einen sicheren Skill-Plan.
Die API liefert ausgewahlten Skill, Alternativen, Policy-Entscheidung, Audit-Notizen und Installationsplan, bevor der Agent handelt.
Task-Fit
96/100
Empfohlen fur Web-Extraktions-Workflows
Wartung
Active
Stars, Aktualitat, Metadaten und Repo-Gesundheit
Install Review
Ready
Agent-sichere nachste Schritte vor Ausfuhrung
Why OpenAgentSkill
Schicke Agents nicht in zufallige Verzeichnisse.
Eine Skill Registry ist nur nutzlich, wenn ein Agent ihr vertrauen kann. OpenAgentSkill macht verstreute GitHub-Projekte zu sortierten, auditierbaren und installierbaren Fahigkeiten.
- 01
Von Aufgabe zu Skill
Agents starten mit Intention, nicht mit Kategorien. Die Registry mappt Jobs auf einen Skill, Alternativen und Fit-Grunde.
- 02
Sicherheit vor Installation
Stars, Aktualitat, Qualitat, Risiken und Readiness stehen neben dem Befehl, den der Agent ausfuhrt.
- 03
Menschen browsen, Agents nutzen API
Menschen durchsuchen den Index; Agents rufen dieselbe Registry uber Resolve-, Recommendation- und Skill-Endpunkte auf.
Registry response
Ein Call, sortierter Installationspfad.
{
"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
Vier Schichten zwischen Intention und Installation.
OpenAgentSkill ist keine weitere statische Liste, sondern ein Registry-Loop, den ein Agent vor Dateianderungen, Browseraktionen oder Drittcode-Installationen aufrufen kann.
Indexed
21,526
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
Wie sich OpenAgentSkill von anderen Skill-Plattformen unterscheidet.
Der Kern: Normale Verzeichnisse sind fur Menschen. OpenAgentSkill ist gebaut, damit ein AI Agent den richtigen Skill automatisch entdeckt, vergleicht und installiert.
| 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.