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Leon-Drq openagentskill
The skill layer for AI agents: npm for AI Agent Skills.
Stars
352
Forks
27
Watchers: 284
Language
License: MIT License
Repository Radar Score
44 / 100
Growth
- 7d
- +0
- 30d
- +0
- %
- 0.0%
Not enough metric snapshots yet to chart growth for this repository.
Last observed: 4 days ago
Score breakdown
- popularity 44
- growth 0
- activity 75
- freshness 100
- community 54
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The skill layer for AI agents.
Find, compare, audit, and install the right reusable Agent Skill before an agent acts.
Try Resolve → · Install the CLI →
Agent Skills are easy to publish and increasingly hard to evaluate. A repository can be popular, recently updated, or well documented without being the right choice for a specific agent task.
OpenAgentSkill adds the decision layer between discovery and execution:
| Capability | What an agent gets |
|---|---|
| Task-to-skill resolve | One recommended Skill plus relevant alternatives |
| Trust and audit signals | License, maintenance, install safety, permission, and quality context |
| Install receipt | A stable, target-specific handoff for Codex, Claude Code, Cursor, or CLI |
| Outcome loop | Evidence from successful, failed, blocked, or setup-required agent runs |
| Machine-readable surfaces | JSON, text, OpenAPI, manifests, rankings, and public research datasets |
OpenAgentSkill is not a static list and does not claim third-party code is safe. It helps agents make a better, inspectable decision before installation.
Resolve a real task:
curl "https://www.openagentskill.com/api/agent/resolve?task=extract+tables+from+PDF+reports&agent=codex&max_risk=medium&format=text"Example response:
OpenAgentSkill Resolve
Task: extract tables from PDF reports
Best skill: <recommended skill>
Trust Score v5: <score and decision>
Install: <reviewed install command>
Risk: <risk level>
Alternatives: <ranked alternatives>
Receipt: <stable install handoff>
The same resolver is available as JSON, plain text, and a compact lockfile format.
Run the pinned, dependency-free GitHub Release:
npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz resolve "extract tables from PDF reports" --agent codexUseful commands:
# Search without installing
npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz find "browser automation"
# Inspect a reviewed install plan
npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add <skill-slug> --agent codex --dry-run
# Read the outcome reporting contract
npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz outcome-contractThe CLI refuses blocked Skills, requires explicit confirmation before execution, and supports --no-telemetry. Source and usage details live in packages/cli.
Before installing a third-party Skill, call:
GET https://www.openagentskill.com/api/agent/resolve
?task={TASK}
&agent={AGENT}
&max_risk=medium
&format=json
Inspect the recommended skill, alternatives, Trust Score v5, audit URL,
risk level, install command, and install receipt. Use a sandbox first.
After one narrow run, report the outcome to:
POST https://www.openagentskill.com/api/agent/outcome
Copy-ready templates for Codex, Claude Code, and Cursor are available in the Agent Integration Kit.
flowchart LR
A["Agent task"] --> B["Resolve API"]
B --> C["Candidate retrieval"]
C --> D["Task fit + Trust Score v5"]
D --> E["Best Skill + alternatives"]
E --> F["Audit + install receipt"]
F --> G["Sandboxed agent run"]
G --> H["Outcome feedback"]
H --> D
Ranking combines task relevance with repository evidence, install readiness, maintenance, license clarity, risk signals, and real agent outcomes. See Resolve Evals for the public evaluation surface.
| Interface | Purpose |
|---|---|
| Resolve Workbench | Turn a task into a recommended Skill and install plan |
| Skill Registry | Search and filter indexed Skills |
| Rankings | Compare trending, trusted, and Agent-Proven Skills |
| Audit Index | Inspect install, maintenance, license, and risk evidence |
| Skill Packs | Compose reviewed Skills into reusable workflows |
| Creator Kit | Submit, claim, badge, and share a Skill |
| API Docs | Integrate registry and agent endpoints |
Machine-readable entry points:
The dependency-free SDK source lives in packages/sdk:
import { OpenAgentSkill } from './packages/sdk/openagentskill.mjs'
const client = new OpenAgentSkill({
baseUrl: 'https://www.openagentskill.com',
})
const plan = await client.resolve('audit a repository', {
agent: 'codex',
maxRisk: 'medium',
})
await client.reportOutcome({
event_id: plan.feedback.event_id,
skill_slug: plan.recommendation.best_skill.slug,
task: plan.task,
outcome: 'success',
dry_run: true,
})The SDK package is prepared for npm publication but is not presented here as published until the public registry release is verifiable.
Paste a repository, subdirectory, or SKILL.md URL into Submit Skill. Submissions are saved first and reviewed asynchronously; GitHub stars, a predefined category, and perfect metadata are not required.
After indexing, authors receive:
- A canonical Skill page and machine-readable metadata.
- Trust, audit, quality, and Agent-Proven badge endpoints.
- Claim and verified-maintainer paths.
- Alternatives and use-case pages that can send qualified traffic back to the source.
Browse the curated GitHub Skill Index for domain and scenario maps.
OpenAgentSkill never treats popularity as proof of safety. Trust Score and audits are decision-support signals, not certifications or guarantees.
Before executing third-party code:
- Read the source and install scripts.
- Review permissions, network calls, dependencies, and required secrets.
- Start in a sandbox or low-risk workspace.
- Keep production credentials and customer data out of unreviewed Skills.
Report vulnerabilities privately through the repository's Security tab. Report risky or misleading third-party listings through the Skill data issue form. See SECURITY.md for scope and disclosure rules.
Requirements: Node.js 22 and pnpm 10.28.2.
git clone https://github.com/Leon-Drq/openagentskill.git
cd openagentskill
corepack enable
pnpm install
cp .env.example .env.local
pnpm devQuality checks:
pnpm run lint
pnpm run typecheck
pnpm test
pnpm run buildThe public website requires Supabase configuration. Pure parsing, resolver-contract, SDK, CLI, and circuit-breaker regression tests run without production credentials.
app/ Next.js pages, APIs, manifests, reports, and agent surfaces
components/ Product UI and client interactions
lib/ Resolve, ranking, audit, indexer, database, and growth logic
packages/ Publishable CLI and SDK packages
scripts/ Regression tests, migrations, importers, and maintenance jobs
skills/ Curated GitHub Skill index by domain and scenario
supabase/ Database functions and migrations
Contributions are welcome across product, APIs, indexing, trust, documentation, and Skill metadata.
- Read CONTRIBUTING.md.
- Look for
good first issueorhelp wanted. - Ask usage questions in GitHub Discussions.
- Use SUPPORT.md to choose the right support channel.
Project decisions and maintainer responsibilities are documented in GOVERNANCE.md. Releases are tracked in CHANGELOG.md, and planned work lives in ROADMAP.md.
The two-layer discovery, validation, deduplication, fast-track, and GitHub rate-safety design is documented in docs/candidate-intake-pipeline.md.
MIT © OpenAgentSkill contributors.
Repository Radar analysis
Deterministic insights derived from public metadata and our observations — not personal testing or reviews.
Why this repository is interesting
- Maintained recently (last push 2 weeks ago).
Who should use it
- Developers working primarily with TypeScript
- Teams exploring AI tooling, agents, or ML infrastructure
- Frontend engineers comparing UI frameworks and tools
Potential use cases
- Reference or evaluate TypeScript open-source approaches in this domain
- Prototype AI/agent workflows or study reference architectures
Strengths
- Recent repository activity
- README present in our index
- Declared license: MIT License
Limitations / considerations
- Insights are derived from public metadata and our observations — not a substitute for code review
What to watch
- Re-check last push, issues, and releases on GitHub before production adoption
Strong signals: Active maintenance
Source: GitHub (public metadata) + Repository Radar analysis. We do not claim ownership of third-party repositories.
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