[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6FNP3FRJ313QBXZPJM9SXJW":3,"skill-same:01M6FNP3FRJ313QBXZPJM9SXJW":74},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":42,"linkOnly":43,"markdownContent":44,"markdownBody":45,"frontMatter":46,"refName":47,"commitSha":48,"skillDirectory":49,"forksCount":50,"repositoryHtmlUrl":51,"repositoryHomepageUrl":6,"ownerHtmlUrl":52,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":53,"install":54,"resources":67},"01M6FNP3FRJ313QBXZPJM9SXJW","linkdapi",null,"Work with LinkdAPI Python SDK for accessing LinkedIn professional profile and company data. Use when you need to fetch profile information, company data, job listings, or search for people\u002Fjobs on LinkedIn. The skill uses uv script pattern for ephemeral Python scripts with inline dependencies.","kbarbel640-del\u002Fskills","kbarbel640-del","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F255315490?v=4","01M6CJPPQGCCESXMG3K7BBGQ5J","01M6CJPPX2PB2BCZERFVM2C2B3",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Ffoontinz\u002Flinkdapi\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[5,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41],"pattern","you","script","with","information","people","professional","scripts","listings","python","dependencies","uv","use","fetch","linkedin","work","python sdk","search","sdk","2026-11-10 10:12:30",false,"---\nname: linkdapi\ndescription: Work with LinkdAPI Python SDK for accessing LinkedIn professional profile and company data. Use when you need to fetch profile information, company data, job listings, or search for people\u002Fjobs on LinkedIn. The skill uses uv script pattern for ephemeral Python scripts with inline dependencies.\n---\n\n# LinkdAPI Python SDK\n\nPython SDK for LinkdAPI — professional profile and company data from LinkedIn with enterprise-grade reliability.\n\n> **Get your API key:** https:\u002F\u002Flinkdapi.com\u002Fsignup?ref=K_CZJSWF\n\n## Quick Start Pattern\n\nUse the **uv script pattern** for ephemeral Python scripts with inline dependencies:\n\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\n#     \"linkdapi\",\n# ]\n# \u002F\u002F\u002F\n\nfrom linkdapi import LinkdAPI\n\nclient = LinkdAPI(\"YOUR_API_KEY\")\nprofile = client.get_profile_overview(\"ryanroslansky\")\nprint(profile)\n```\n\nRun with:\n```bash\nuv run script.py\n```\n\nThis installs dependencies automatically, runs the script, and cleans up — perfect for one-off tasks.\n\n## Why This Pattern\n\n- **No global installs**: Dependencies are managed per-script\n- **Ephemeral by design**: Write, run, delete — no cleanup needed\n- **Reproducible**: Everything needed is in one file\n- **Fast**: uv handles dependency resolution and caching\n\n## Writing Scripts\n\n### Script Header Format\n\nAlways start with the uv script block:\n\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\n#     \"linkdapi\",\n#     # Add more if needed (e.g., \"rich\", \"pandas\")\n# ]\n# \u002F\u002F\u002F\n```\n\n### Common Tasks\n\n**Get profile overview:**\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\"linkdapi\"]\n# \u002F\u002F\u002F\n\nfrom linkdapi import LinkdAPI\n\nclient = LinkdAPI(\"YOUR_API_KEY\")\nprofile = client.get_profile_overview(\"ryanroslansky\")\n\nif profile.get('success'):\n    data = profile['data']\n    print(f\"{data['fullName']} - {data.get('headline', '')}\")\n    print(f\"Location: {data.get('location')}\")\n```\n\n**Get company info:**\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\"linkdapi\"]\n# \u002F\u002F\u002F\n\nfrom linkdapi import LinkdAPI\n\nclient = LinkdAPI(\"YOUR_API_KEY\")\ncompany = client.get_company_info(name=\"google\")\n\nif company.get('success'):\n    data = company['data']\n    print(f\"{data['name']}\")\n    print(f\"Industry: {data.get('industry')}\")\n    print(f\"Employees: {data.get('employeeCount', 'N\u002FA')}\")\n```\n\n**Search jobs:**\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\"linkdapi\"]\n# \u002F\u002F\u002F\n\nfrom linkdapi import LinkdAPI\n\nclient = LinkdAPI(\"YOUR_API_KEY\")\nresult = client.search_jobs(\n    keyword=\"Software Engineer\",\n    location=\"San Francisco, CA\",\n    time_posted=\"1week\"\n)\n\nif result.get('success'):\n    for job in result['data']['jobs'][:5]:\n        print(f\"{job['title']} at {job['company']}\")\n```\n\n**Batch profile enrichment (async):**\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\"linkdapi\"]\n# \u002F\u002F\u002F\n\nimport asyncio\nfrom linkdapi import AsyncLinkdAPI\n\nasync def enrich():\n    async with AsyncLinkdAPI(\"YOUR_API_KEY\") as api:\n        profiles = await asyncio.gather(\n            api.get_profile_overview(\"ryanroslansky\"),\n            api.get_profile_overview(\"satyanadella\"),\n            api.get_profile_overview(\"jeffweiner08\")\n        )\n        for p in profiles:\n            if p.get('success'):\n                print(p['data']['fullName'])\n\nasyncio.run(enrich())\n```\n\n## Agent Workflow\n\nWhen a user requests LinkedIn data:\n\n1. **Identify the task** (profile lookup, company data, job search, etc.)\n2. **Write a temporary script** in workspace with the uv script header\n3. **Add dependencies** (usually just `\"linkdapi\"`, add others if needed)\n4. **Import and use** LinkdAPI classes\n5. **Run with `uv run`**\n6. **Capture output** and report to user\n7. **Delete the script** after use (optional)\n\n### Example Workflow\n\nUser: *\"Get the profile for jeffweiner08\"*\n\nAgent:\n```bash\ncat > \u002Ftmp\u002Flinkdapi_query.py \u003C\u003C 'EOF'\n# \u002F\u002F\u002F script\n# dependencies = [\"linkdapi\"]\n# \u002F\u002F\u002F\n\nfrom linkdapi import LinkdAPI\nimport os\n\nclient = LinkdAPI(os.getenv(\"LINKDAPI_API_KEY\"))\nprofile = client.get_profile_overview(\"jeffweiner08\")\n\nif profile.get('success'):\n    data = profile['data']\n    print(f\"Name: {data['fullname']}\")\n    print(f\"Headline: {data.get('headline', 'N\u002FA')}\")\n    print(f\"Location: {data.get('location', 'N\u002FA')}\")\n    print(f\"Company: {data.get('company', 'N\u002FA')}\")\nelse:\n    print(f\"Error: {profile.get('message')}\")\nEOF\n\nuv run \u002Ftmp\u002Flinkdapi_query.py\nrm \u002Ftmp\u002Flinkdapi_query.py\n```\n\n## Getting an API Key\n\nTo use LinkdAPI, you'll need an API key. Sign up at:\n\n? **https:\u002F\u002Flinkdapi.com\u002Fsignup?ref=K_CZJSWF**\n\nOnce registered, you'll get an API key that you can use to authenticate your requests.\n\n## Authentication\n\nSet the API key as an environment variable:\n\n```bash\nexport LINKDAPI_API_KEY=\"your_api_key_here\"\n```\n\nUse it in scripts:\n```python\nimport os\nfrom linkdapi import LinkdAPI\n\nclient = LinkdAPI(os.getenv(\"LINKDAPI_API_KEY\"))\n```\n\n## Key API Methods\n\n### Profiles\n- `get_profile_overview(username)` — Basic profile info\n- `get_profile_details(urn)` — Detailed profile data\n- `get_contact_info(username)` — Email, phone, websites\n- `get_full_profile(username=None, urn=None)` — Complete profile\n- `get_full_experience(urn)` — Work history\n- `get_education(urn)` — Education history\n- `get_skills(urn)` — Skills & endorsements\n\n### Companies\n- `get_company_info(company_id=None, name=None)` — Company details\n- `company_name_lookup(query)` — Search by name\n- `get_company_employees_data(company_id)` — Employee stats\n- `get_company_jobs(company_ids)` — Job listings\n\n### Jobs\n- `search_jobs(keyword, location, ...)` — Search job postings\n- `get_job_details(job_id)` — Detailed job info\n\n### Search\n- `search_people(keyword, title, company, ...)` — Find people\n- `search_companies(keyword, industry, ...)` — Find companies\n- `search_posts(keyword, ...)` — Find posts\n\n## Performance Tips\n\n- Use `AsyncLinkdAPI` for batch operations (40x faster)\n- Add `return_exceptions=True` in `asyncio.gather()` for graceful error handling\n- Use context managers (`async with`) for proper resource cleanup\n\n## Error Handling\n\nCheck responses and handle errors:\n\n```python\nresult = client.get_profile_overview(\"username\")\n\nif result.get('success'):\n    data = result['data']\n    # Process data\nelse:\n    print(f\"API Error: {result.get('message')}\")\n```\n\n## References\n\nFull API documentation: https:\u002F\u002Flinkdapi.com\u002Fdocs","# LinkdAPI Python SDK\n\nPython SDK for LinkdAPI — professional profile and company data from LinkedIn with enterprise-grade reliability.\n\n> **Get your API key:** https:\u002F\u002Flinkdapi.com\u002Fsignup?ref=K_CZJSWF\n\n## Quick Start Pattern\n\nUse the **uv script pattern** for ephemeral Python scripts with inline dependencies:\n\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\n#     \"linkdapi\",\n# ]\n# \u002F\u002F\u002F\n\nfrom linkdapi import LinkdAPI\n\nclient = LinkdAPI(\"YOUR_API_KEY\")\nprofile = client.get_profile_overview(\"ryanroslansky\")\nprint(profile)\n```\n\nRun with:\n```bash\nuv run script.py\n```\n\nThis installs dependencies automatically, runs the script, and cleans up — perfect for one-off tasks.\n\n## Why This Pattern\n\n- **No global installs**: Dependencies are managed per-script\n- **Ephemeral by design**: Write, run, delete — no cleanup needed\n- **Reproducible**: Everything needed is in one file\n- **Fast**: uv handles dependency resolution and caching\n\n## Writing Scripts\n\n### Script Header Format\n\nAlways start with the uv script block:\n\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\n#     \"linkdapi\",\n#     # Add more if needed (e.g., \"rich\", \"pandas\")\n# ]\n# \u002F\u002F\u002F\n```\n\n### Common Tasks\n\n**Get profile overview:**\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\"linkdapi\"]\n# \u002F\u002F\u002F\n\nfrom linkdapi import LinkdAPI\n\nclient = LinkdAPI(\"YOUR_API_KEY\")\nprofile = client.get_profile_overview(\"ryanroslansky\")\n\nif profile.get('success'):\n    data = profile['data']\n    print(f\"{data['fullName']} - {data.get('headline', '')}\")\n    print(f\"Location: {data.get('location')}\")\n```\n\n**Get company info:**\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\"linkdapi\"]\n# \u002F\u002F\u002F\n\nfrom linkdapi import LinkdAPI\n\nclient = LinkdAPI(\"YOUR_API_KEY\")\ncompany = client.get_company_info(name=\"google\")\n\nif company.get('success'):\n    data = company['data']\n    print(f\"{data['name']}\")\n    print(f\"Industry: {data.get('industry')}\")\n    print(f\"Employees: {data.get('employeeCount', 'N\u002FA')}\")\n```\n\n**Search jobs:**\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\"linkdapi\"]\n# \u002F\u002F\u002F\n\nfrom linkdapi import LinkdAPI\n\nclient = LinkdAPI(\"YOUR_API_KEY\")\nresult = client.search_jobs(\n    keyword=\"Software Engineer\",\n    location=\"San Francisco, CA\",\n    time_posted=\"1week\"\n)\n\nif result.get('success'):\n    for job in result['data']['jobs'][:5]:\n        print(f\"{job['title']} at {job['company']}\")\n```\n\n**Batch profile enrichment (async):**\n```python\n# \u002F\u002F\u002F script\n# dependencies = [\"linkdapi\"]\n# \u002F\u002F\u002F\n\nimport asyncio\nfrom linkdapi import AsyncLinkdAPI\n\nasync def enrich():\n    async with AsyncLinkdAPI(\"YOUR_API_KEY\") as api:\n        profiles = await asyncio.gather(\n            api.get_profile_overview(\"ryanroslansky\"),\n            api.get_profile_overview(\"satyanadella\"),\n            api.get_profile_overview(\"jeffweiner08\")\n        )\n        for p in profiles:\n            if p.get('success'):\n                print(p['data']['fullName'])\n\nasyncio.run(enrich())\n```\n\n## Agent Workflow\n\nWhen a user requests LinkedIn data:\n\n1. **Identify the task** (profile lookup, company data, job search, etc.)\n2. **Write a temporary script** in workspace with the uv script header\n3. **Add dependencies** (usually just `\"linkdapi\"`, add others if needed)\n4. **Import and use** LinkdAPI classes\n5. **Run with `uv run`**\n6. **Capture output** and report to user\n7. **Delete the script** after use (optional)\n\n### Example Workflow\n\nUser: *\"Get the profile for jeffweiner08\"*\n\nAgent:\n```bash\ncat > \u002Ftmp\u002Flinkdapi_query.py \u003C\u003C 'EOF'\n# \u002F\u002F\u002F script\n# dependencies = [\"linkdapi\"]\n# \u002F\u002F\u002F\n\nfrom linkdapi import LinkdAPI\nimport os\n\nclient = LinkdAPI(os.getenv(\"LINKDAPI_API_KEY\"))\nprofile = client.get_profile_overview(\"jeffweiner08\")\n\nif profile.get('success'):\n    data = profile['data']\n    print(f\"Name: {data['fullname']}\")\n    print(f\"Headline: {data.get('headline', 'N\u002FA')}\")\n    print(f\"Location: {data.get('location', 'N\u002FA')}\")\n    print(f\"Company: {data.get('company', 'N\u002FA')}\")\nelse:\n    print(f\"Error: {profile.get('message')}\")\nEOF\n\nuv run \u002Ftmp\u002Flinkdapi_query.py\nrm \u002Ftmp\u002Flinkdapi_query.py\n```\n\n## Getting an API Key\n\nTo use LinkdAPI, you'll need an API key. Sign up at:\n\n? **https:\u002F\u002Flinkdapi.com\u002Fsignup?ref=K_CZJSWF**\n\nOnce registered, you'll get an API key that you can use to authenticate your requests.\n\n## Authentication\n\nSet the API key as an environment variable:\n\n```bash\nexport LINKDAPI_API_KEY=\"your_api_key_here\"\n```\n\nUse it in scripts:\n```python\nimport os\nfrom linkdapi import LinkdAPI\n\nclient = LinkdAPI(os.getenv(\"LINKDAPI_API_KEY\"))\n```\n\n## Key API Methods\n\n### Profiles\n- `get_profile_overview(username)` — Basic profile info\n- `get_profile_details(urn)` — Detailed profile data\n- `get_contact_info(username)` — Email, phone, websites\n- `get_full_profile(username=None, urn=None)` — Complete profile\n- `get_full_experience(urn)` — Work history\n- `get_education(urn)` — Education history\n- `get_skills(urn)` — Skills & endorsements\n\n### Companies\n- `get_company_info(company_id=None, name=None)` — Company details\n- `company_name_lookup(query)` — Search by name\n- `get_company_employees_data(company_id)` — Employee stats\n- `get_company_jobs(company_ids)` — Job listings\n\n### Jobs\n- `search_jobs(keyword, location, ...)` — Search job postings\n- `get_job_details(job_id)` — Detailed job info\n\n### Search\n- `search_people(keyword, title, company, ...)` — Find people\n- `search_companies(keyword, industry, ...)` — Find companies\n- `search_posts(keyword, ...)` — Find posts\n\n## Performance Tips\n\n- Use `AsyncLinkdAPI` for batch operations (40x faster)\n- Add `return_exceptions=True` in `asyncio.gather()` for graceful error handling\n- Use context managers (`async with`) for proper resource cleanup\n\n## Error Handling\n\nCheck responses and handle errors:\n\n```python\nresult = client.get_profile_overview(\"username\")\n\nif result.get('success'):\n    data = result['data']\n    # Process data\nelse:\n    print(f\"API Error: {result.get('message')}\")\n```\n\n## References\n\nFull API documentation: https:\u002F\u002Flinkdapi.com\u002Fdocs",{"name":5,"description":7},"main","e7e336ac628c3e3bd771aff1aaa469c93778f94a","skills\u002Ffoontinz\u002Flinkdapi",0,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del","2026-08-23 22:39:37",{"source":8,"skillName":5,"commands":55,"prompt":65,"zipAvailable":66},[56,59,62],{"tool":57,"command":58},"npx","npx skills add kbarbel640-del\u002Fskills --skill linkdapi",{"tool":60,"command":61},"bunx","bunx skills add kbarbel640-del\u002Fskills --skill linkdapi",{"tool":63,"command":64},"pnpm","pnpm dlx skills add kbarbel640-del\u002Fskills --skill linkdapi","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Ffoontinz\u002Flinkdapi\u002FSKILL.md",true,[68],{"path":69,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":72,"sourceHtmlUrl":73},"_meta.json","REFERENCE","参考文档",274,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Ffoontinz\u002Flinkdapi\u002F_meta.json",[75,105,129,149,155,175],{"skillNo":76,"name":77,"nameZh":6,"description":78,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":79,"categories":80,"keywords":86,"publishedAt":42},"01M6G8J55967D6281ACMKAKTEQ","crowd-prompting","A marketplace where AI agents improve prompts, system instructions, tool descriptions, and other text-based content with domain expertise from real-world operations — and earn tokens for valuable contributions.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzzadrian\u002Fcrowd-prompting\u002FSKILL.md",[81],{"categoryNo":82,"categoryName":83,"taxonomyType":84,"taxonomyTypeDesc":85},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[87,88,89,26,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104],"crowd prompting","prompting","api","tokens","domain","world","prompts","operations","instructions","text","tool","system","improve","productivity","marketplace","https","content","ai agents",{"skillNo":106,"name":107,"nameZh":6,"description":108,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":109,"categories":110,"keywords":112,"publishedAt":42},"01M6G8J0PKPAYVET6BWE8W4C26","dilemm-ai","Compete in DilemmAI, the prisoner's dilemma AI arena at dilemm.ai. Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[111],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[113,89,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,93,35],"dilemm ai","arena","analyze","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking",{"skillNo":130,"name":131,"nameZh":6,"description":132,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":133,"categories":134,"keywords":138,"publishedAt":42},"01M6G8HWAF3K9SW7NP3Z83CPJ6","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. Use when working with arXiv papers, fetching paper lists by date\u002Fcategory\u002Finterest, viewing paper details with comments, or submitting paper reviews via API at http:\u002F\u002F150.158.152.82:8000.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Fweak-accept\u002FSKILL.md",[135],{"categoryNo":136,"categoryName":137,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究",[139,140,141,142,143,144,145,26,36,127,35,146,89,147,148],"arxiv paper reviews","reviews","arxiv","paper","crawler","papers","comments","read","http","via",{"skillNo":150,"name":131,"nameZh":6,"description":132,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":151,"categories":152,"keywords":154,"publishedAt":42},"01M6G8HQJ7N7WMY6YV7D7SSJ16","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[153],{"categoryNo":136,"categoryName":137,"taxonomyType":20,"taxonomyTypeDesc":21},[142,141,140,139,148,144,145,26,143,127,35,36,146,89,147],{"skillNo":156,"name":157,"nameZh":6,"description":158,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":159,"categories":160,"keywords":161,"publishedAt":42},"01M6G8HM95Y64JNVFC2HN4E2BG","git-summary","Get a quick summary of the current Git repository including status, recent commits, branches, and contributors.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzweack\u002Fgit-summary\u002FSKILL.md",[],[162,163,164,165,166,167,168,169,170,171,172,173,174],"git","summary","git summary","commits","repository","win32","status","linux","contributors","true","quick","get","branches",{"skillNo":176,"name":177,"nameZh":6,"description":178,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":179,"categories":180,"keywords":185,"publishedAt":42},"01M6G8HGEGF05CNEJCGVYFSC4R","agent-constitution","Interact with AgentConstitution governance contracts on Base Sepolia. Check compliance, read rules, log actions, query governance state.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fztsalexey\u002Fagent-constitution\u002FSKILL.md",[181,182],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":183,"categoryName":184,"taxonomyType":84,"taxonomyTypeDesc":85},"01JBSEEDCAT000000000000037","律师与法务",[186,187,188,189,26,190,191,47,192,146,193,194,195,196,197,102,198,199,200],"agent constitution","constitution","contracts","tree","query","base","log","check","Rules","projects","compliance","actions","state","governance","github"]