Xpersona

Crawler Summary

AgentSkillHub answer-first brief

Open skill registry & compatibility engine for AI agents. Define a skill once, validate, score, and export to any agent framework (LangGraph/CrewAI/Dify). <div align="center"> 🧩 AgentSkillHub **The open skill registry & compatibility engine for AI agents.** *Define a skill once — validate, score, and export it to any agent framework.* $1 $1 $1 $1 $1 $1 $1 · $1 · $1 · $1 · $1 · $1 </div> --- Agent 生态碎片化严重：LangGraph、CrewAI、Dify 各有一套工具/技能定义，同一个「搜索网页 + 总结」能力在每个框架里都要重复实现。**AgentSkillHub 用一份统一的 Skill Schema 解决这个问题** —— 技能带着输入/输出契约、依赖声明、Token 成本和成功率指标注册进 Hub；Compatibility En Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 10/9/2026.

Freshness

Last checked 10/9/2026

Best For

AgentSkillHub is best for crewai, multi-agent workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB REPOS, runtime-metrics, public facts pack

CardFactsSnapshotContractTrust
Claim this agent
Agent DossierGITHUB REPOSSafety: 66/100

AgentSkillHub

Open skill registry & compatibility engine for AI agents. Define a skill once, validate, score, and export to any agent framework (LangGraph/CrewAI/Dify). <div align="center"> 🧩 AgentSkillHub **The open skill registry & compatibility engine for AI agents.** *Define a skill once — validate, score, and export it to any agent framework.* $1 $1 $1 $1 $1 $1 $1 · $1 · $1 · $1 · $1 · $1 </div> --- Agent 生态碎片化严重：LangGraph、CrewAI、Dify 各有一套工具/技能定义，同一个「搜索网页 + 总结」能力在每个框架里都要重复实现。**AgentSkillHub 用一份统一的 Skill Schema 解决这个问题** —— 技能带着输入/输出契约、依赖声明、Token 成本和成功率指标注册进 Hub；Compatibility En

OpenClawself-declared

Public facts

5

Change events

1

Artifacts

0

Freshness

Oct 9, 2026

Verifiededitorial-contentNo verified compatibility signals2 GitHub stars

Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 10/9/2026.

2 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Oct 9, 2026

Vendor

Laolaola278 Dev

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 10/9/2026.

View Source

Setup snapshot

  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Laolaola278 Dev

profilemedium
Observed Oct 9, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Oct 9, 2026Source linkProvenance
Adoption (1)

Adoption signal

2 GitHub stars

profilemedium
Observed Oct 9, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB REPOS

Extracted files

0

Examples

6

Snippets

0

Languages

python

Executable Examples

mermaid

flowchart LR
    subgraph Frontend["Frontend · Next.js 14"]
        UI1["技能市场"]
        UI2["Composer 组合器"]
        UI3["Benchmark 展示"]
    end

    subgraph Backend["Backend · FastAPI"]
        REG["Skill Registry<br/>CRUD + 搜索"]
        COMP["Composer<br/>校验 + 成本估算"]
        CE["Compatibility Engine<br/>类型分析 · Risk Score · 修复建议"]
        EXP["Exporters<br/>LangGraph (AST 代码生成)"]
    end

    subgraph Data["Data"]
        DB[("SQLite / PostgreSQL<br/>Alembic migrations")]
    end

    UI1 & UI2 & UI3 -->|REST| REG
    UI2 -->|analyze / validate / export| COMP
    COMP --> CE
    COMP --> EXP
    REG --> DB
    COMP --> DB

bash

cd backend
python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -r requirements.txt
alembic upgrade head && python -m app.seed          # 建表 + 示例数据
uvicorn app.main:app --reload --port 8000

bash

cd frontend
npm install && npm run dev

bash

make setup      # 后端 venv + 依赖 + 迁移 + 前端依赖
make run        # 启动后端
make test       # 跑测试
make benchmark  # 跑 Compatibility Engine benchmark

bash

curl -X POST http://localhost:8000/api/compositions/analyze \
  -H "Content-Type: application/json" \
  -d '{"steps": [{"skill_id": "web-search"}, {"skill_id": "doc-summarizer"}]}'

bash

curl -X POST http://localhost:8000/api/compositions/analyze \
  -H "Content-Type: application/json" \
  -d '{"steps": [{"skill_id": "web-search"}, {"skill_id": "doc-summarizer"}]}'

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB REPOS

Docs source

GITHUB REPOS

Editorial quality

ready

Open skill registry & compatibility engine for AI agents. Define a skill once, validate, score, and export to any agent framework (LangGraph/CrewAI/Dify). <div align="center"> 🧩 AgentSkillHub **The open skill registry & compatibility engine for AI agents.** *Define a skill once — validate, score, and export it to any agent framework.* $1 $1 $1 $1 $1 $1 $1 · $1 · $1 · $1 · $1 · $1 </div> --- Agent 生态碎片化严重：LangGraph、CrewAI、Dify 各有一套工具/技能定义，同一个「搜索网页 + 总结」能力在每个框架里都要重复实现。**AgentSkillHub 用一份统一的 Skill Schema 解决这个问题** —— 技能带着输入/输出契约、依赖声明、Token 成本和成功率指标注册进 Hub；Compatibility En

Full README
<div align="center">

🧩 AgentSkillHub

The open skill registry & compatibility engine for AI agents.

Define a skill once — validate, score, and export it to any agent framework.

CI License: MIT Python 3.11+ FastAPI Next.js 14 Version

Quick Start · Features · API · Docs · Roadmap · Contributing

</div>

Agent 生态碎片化严重：LangGraph、CrewAI、Dify 各有一套工具/技能定义，同一个「搜索网页 + 总结」能力在每个框架里都要重复实现。AgentSkillHub 用一份统一的 Skill Schema 解决这个问题 —— 技能带着输入/输出契约、依赖声明、Token 成本和成功率指标注册进 Hub；Compatibility Engine 在你把技能拼成 Pipeline 时做深度兼容性分析（类型冲突、缺失字段、风险评分、自动修复建议）；最后一键导出为目标框架可运行的代码。

🏗️ Architecture

flowchart LR
    subgraph Frontend["Frontend · Next.js 14"]
        UI1["技能市场"]
        UI2["Composer 组合器"]
        UI3["Benchmark 展示"]
    end

    subgraph Backend["Backend · FastAPI"]
        REG["Skill Registry<br/>CRUD + 搜索"]
        COMP["Composer<br/>校验 + 成本估算"]
        CE["Compatibility Engine<br/>类型分析 · Risk Score · 修复建议"]
        EXP["Exporters<br/>LangGraph (AST 代码生成)"]
    end

    subgraph Data["Data"]
        DB[("SQLite / PostgreSQL<br/>Alembic migrations")]
    end

    UI1 & UI2 & UI3 -->|REST| REG
    UI2 -->|analyze / validate / export| COMP
    COMP --> CE
    COMP --> EXP
    REG --> DB
    COMP --> DB

✨ Features

| | 功能 | 说明 | |---|---|---| | 📦 | 统一 Skill Schema | Pydantic v2 契约：IO JSON Schema、依赖、Token 成本、成功率，一次定义处处使用 | | 🔍 | 技能市场 | 关键词 / 分类 / 实现类型搜索，Web UI 浏览 | | 🧠 | Compatibility Engine | 字段级类型分析（TypeMismatch / MissingRequiredField / UnusedOutputs）、0–100 Risk Score 四级评级、自动修复建议（Type Converter / JSON Mapper / Reorder） | | 🔗 | Composer | 线性 Pipeline 校验、依赖传递解析、循环依赖检测（完整路径报告）、链路成本估算 | | 🐍 | 安全代码导出 | 基于 Python AST 的 LangGraph 导出器 —— 用户输入永远只进入字符串字面量，注入免疫，产物保证 compile() 通过 | | 📊 | 可复现 Benchmark | 100+ 确定性生成的 workflow + ground truth，CI 每次 push 自动跑，95% 准确率门禁 | | 🛡️ | 工程化底座 | Alembic 迁移、统一错误信封、93%+ 测试覆盖、ruff/black/mypy/pre-commit |

🚀 Quick Start

后端（3 条命令）

cd backend
python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -r requirements.txt
alembic upgrade head && python -m app.seed          # 建表 + 示例数据
uvicorn app.main:app --reload --port 8000

打开 http://localhost:8000/docs 查看交互式 API 文档。

前端

cd frontend
npm install && npm run dev

http://localhost:3000 —— 技能市场 · http://localhost:3000/composer —— 组合器

或者直接用 Make

make setup      # 后端 venv + 依赖 + 迁移 + 前端依赖
make run        # 启动后端
make test       # 跑测试
make benchmark  # 跑 Compatibility Engine benchmark

30 秒体验 Compatibility Engine

curl -X POST http://localhost:8000/api/compositions/analyze \
  -H "Content-Type: application/json" \
  -d '{"steps": [{"skill_id": "web-search"}, {"skill_id": "doc-summarizer"}]}'

{
  "compatible": true,
  "risk_score": 88,
  "grade": "Excellent",
  "issues": [],
  "suggestions": [],
  "breakdown": { "field_compatibility": 1.0, "success_rate": 0.92, ... }
}

切换 PostgreSQL

export DATABASE_URL="postgresql+psycopg://user:pass@localhost:5432/agentskillhub"
alembic upgrade head

📁 Project Structure

├── backend/
│   ├── app/
│   │   ├── api/                 # 路由层（skills / compositions / benchmarks）
│   │   ├── models/              # SQLAlchemy ORM
│   │   ├── schemas/             # Pydantic 契约（Skill Schema · Compatibility Report）
│   │   ├── services/
│   │   │   ├── registry.py      # 技能 CRUD + 搜索
│   │   │   ├── composer.py      # Pipeline 校验 · 依赖解析 · 环检测
│   │   │   ├── compatibility.py # ⭐ Compatibility Engine
│   │   │   └── exporters/       # AST 代码生成（LangGraph）
│   │   ├── errors.py            # 统一错误信封
│   │   └── seed.py              # 示例数据
│   ├── alembic/                 # 数据库迁移
│   ├── benchmark/               # Benchmark & Evaluation Framework
│   └── tests/                   # 100+ 测试，93%+ 覆盖
├── frontend/                    # Next.js 14 · App Router · Tailwind
├── docs/                        # 架构 · 设计决策 · 引擎原理 · Schema 参考
└── examples/langgraph/          # 端到端集成示例

📚 API Overview

| 方法 | 路径 | 说明 | |---|---|---| | GET | /api/skills | 列出技能，支持 ?q=&category=&implementation_type= | | POST | /api/skills | 注册新技能 | | GET/PUT/DELETE | /api/skills/{id} | 技能详情 / 更新 / 删除 | | POST | /api/compositions/validate | 校验 Pipeline IO 兼容性并估算成本 | | POST | /api/compositions/analyze | ⭐ 深度兼容性分析：Risk Score + 修复建议 | | POST | /api/compositions/export?target=langgraph | 导出为可运行代码 | | GET | /api/benchmarks | Token 消耗统计 |

所有错误响应统一为 {"error": {"code", "message", "details"}}。完整 Schema 见 docs/schema.md。

📊 Benchmark

定位：Synthetic Benchmark（合成回归基线），不是真实世界准确率声明。

backend/benchmark/ 内置一套可复现的评估框架：确定性生成 108 个带 ground truth 的 workflow（9 类场景：正常链路 / 字段缺失 / 类型冲突 / 循环依赖 / Unused Outputs / 复杂 DAG / 多依赖 / 高 Token / 低成功率），回放 Compatibility Engine 并计算 Detection Accuracy、Precision / Recall、P95 耗时、峰值内存。

make benchmark   # 或 cd backend && python -m benchmark.runner

报告自动写入 backend/benchmark/results/report.md。由于 ground truth 由结构构造保证，健康状态下准确率应为 100% —— 它的价值是回归检测：任何引擎行为变化都会立刻打破基线。CI 中低于 95% 直接失败。真实世界技能库的评估在 Roadmap 中（沙箱运行时 Benchmark）。

设计细节见 docs/benchmark.md。

🗺️ Roadmap

  • v1.1 — CrewAI / Dify 导出器 · 技能语义搜索（Embedding）· Web 端技能提交表单
  • v1.2 — 技能版本管理（semver 兼容性检查）· Composer 可视化画布（React Flow）· 真实运行时 Benchmark（沙箱执行）
  • v2.0 — PostgreSQL 多用户 / 组织空间 · 技能评分社区 · CLI（ash install <skill-id>）

🤝 Contributing

欢迎 PR！请先阅读 CONTRIBUTING.md。

make setup && make lint && make test   # 提交前三连

❓ FAQ

<details> <summary><b>为什么不直接用 LangGraph / CrewAI 自己的工具定义？</b></summary>

它们的定义互不通用。AgentSkillHub 的 Skill Schema 是框架中立的中间层：注册一次，导出到任何目标框架。兼容性分析（类型检查、风险评分）也只在统一 Schema 上才可能做到。

</details> <details> <summary><b>导出的代码可以直接跑吗？</b></summary>

导出的是可运行的骨架：graph 结构、节点连线、状态类型都是完整的，compile() 保证通过；tool 节点的具体实现留有 NotImplementedError 桩等你填充，agent 节点已内置 LLM 调用。

</details> <details> <summary><b>Risk Score 是怎么算的？</b></summary>

四个分量加权：字段兼容率 40% + 链路成功率 30% + Token 成本 15% + 依赖数量 15%，映射到 Excellent（≥85）/ Good（≥70）/ Warning（≥50）/ Critical。存在阻断性错误的 workflow 硬性封顶 49 分。公式细节见 docs/compatibility_engine.md。

</details> <details> <summary><b>Benchmark 100% 准确率是真的吗？</b></summary>

是真的，但要正确理解：这是合成基线 —— 数据集的 ground truth 由构造保证，100% 表示引擎行为与规格完全一致。它是回归护栏，不是真实世界效果声明。见上文 Benchmark 章节。

</details> <details> <summary><b>生产环境可以用 SQLite 吗？</b></summary>

小规模只读为主的部署可以。写并发高时设置 DATABASE_URL 切 PostgreSQL，迁移由 Alembic 统一管理，代码零改动。

</details>

📄 License

MIT © 2026 AgentSkillHub Contributors

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB REPOS

Endpoints

Dossier APISnapshot APIContract APITrust API

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

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Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

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Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-10-09T18:49:13.664Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "crewai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "multi-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Laolaola278 Dev",
    "href": "https://github.com/laolaola278-dev/AgentSkillHub",
    "sourceUrl": "https://github.com/laolaola278-dev/AgentSkillHub",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-10-09T15:56:33.642Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-10-09T15:56:33.642Z",
    "isPublic": true
  },
  {
    "factKey": "traction",
    "category": "adoption",
    "label": "Adoption signal",
    "value": "2 GitHub stars",
    "href": "https://github.com/laolaola278-dev/AgentSkillHub",
    "sourceUrl": "https://github.com/laolaola278-dev/AgentSkillHub",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-10-09T15:56:33.642Z",
    "isPublic": true
  },
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-laolaola278-dev-agentskillhub/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

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