[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6N283Z0C9PCW93CEFDSPDTG":3,"skill-same:01M6N283Z0C9PCW93CEFDSPDTG":78},{"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":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":44,"commitSha":45,"skillDirectory":46,"forksCount":47,"repositoryHtmlUrl":48,"repositoryHomepageUrl":6,"ownerHtmlUrl":49,"ownerBlogUrl":6,"ownerDescription":50,"updatedAt":51,"install":52,"resources":65},"01M6N283Z0C9PCW93CEFDSPDTG","research",null,"Get AI-synthesized research on any topic with citations, directly in your terminal. Supports structured JSON output for pipelines. Use when you need comprehensive research grounded in web data without writing code.","Kernel8901\u002Fai-agent-skills-classification","Kernel8901","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F72647553?v=4","01M6KV388J2H5PNC8D8P940BJD","01M6KV38CS5B3AY63RKZB410YM",7,"MIT","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fresearch-2\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[5,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"json","for","you","with","output","get","structured","pipelines","use","writing","Citations","data","JSON Output","code","web","terminal","2026-11-10 10:12:30",false,"---\nname: research\ndescription: \"Get AI-synthesized research on any topic with citations, directly in your terminal. Supports structured JSON output for pipelines. Use when you need comprehensive research grounded in web data without writing code.\"\n---\n\n# Research Skill\n\nConduct comprehensive research on any topic with automatic source gathering, analysis, and response generation with citations.\n\n## Prerequisites\n\n**Tavily API Key Required** - Get your key at https:\u002F\u002Ftavily.com\n\nAdd to `~\u002F.claude\u002Fsettings.json`:\n```json\n{\n  \"env\": {\n    \"TAVILY_API_KEY\": \"tvly-your-api-key-here\"\n  }\n}\n```\n\n## Quick Start\n\n> **Tip**: Research can take 30-120 seconds. Press **Ctrl+B** to run in the background.\n\n### Using the Script\n\n```bash\n.\u002Fscripts\u002Fresearch.sh '\u003Cjson>' [output_file]\n```\n\n**Examples:**\n```bash\n# Basic research\n.\u002Fscripts\u002Fresearch.sh '{\"input\": \"quantum computing trends\"}'\n\n# With pro model for comprehensive analysis\n.\u002Fscripts\u002Fresearch.sh '{\"input\": \"AI agents comparison\", \"model\": \"pro\"}'\n\n# Save to file\n.\u002Fscripts\u002Fresearch.sh '{\"input\": \"market analysis for EVs\", \"model\": \"pro\"}' .\u002Fev-report.md\n\n# With custom citation format\n.\u002Fscripts\u002Fresearch.sh '{\"input\": \"climate change impacts\", \"model\": \"mini\", \"citation_format\": \"apa\"}'\n\n# With structured output schema\n.\u002Fscripts\u002Fresearch.sh '{\"input\": \"fintech startups 2025\", \"model\": \"pro\", \"output_schema\": {\"properties\": {\"summary\": {\"type\": \"string\"}, \"companies\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}}}, \"required\": [\"summary\"]}}'\n```\n\n### Basic Research\n\n```bash\ncurl --request POST \\\n  --url https:\u002F\u002Fapi.tavily.com\u002Fresearch \\\n  --header \"Authorization: Bearer $TAVILY_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"input\": \"Latest developments in quantum computing\",\n    \"model\": \"mini\",\n    \"stream\": false,\n    \"citation_format\": \"numbered\"\n  }'\n```\n\n> **Note**: Streaming is disabled for token management. The call waits until research completes and returns clean JSON.\n\n### With Custom Schema\n\n```bash\ncurl --request POST \\\n  --url https:\u002F\u002Fapi.tavily.com\u002Fresearch \\\n  --header \"Authorization: Bearer $TAVILY_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"input\": \"Electric vehicle market analysis\",\n    \"model\": \"pro\",\n    \"stream\": false,\n    \"citation_format\": \"numbered\",\n    \"output_schema\": {\n      \"properties\": {\n        \"market_overview\": {\n          \"type\": \"string\",\n          \"description\": \"2-3 sentence overview of the market\"\n        },\n        \"key_players\": {\n          \"type\": \"array\",\n          \"description\": \"Major companies in this market\",\n          \"items\": {\n            \"type\": \"object\",\n            \"properties\": {\n              \"name\": {\"type\": \"string\", \"description\": \"Company name\"},\n              \"market_share\": {\"type\": \"string\", \"description\": \"Approximate market share\"}\n            },\n            \"required\": [\"name\"]\n          }\n        }\n      },\n      \"required\": [\"market_overview\", \"key_players\"]\n    }\n  }'\n```\n\n## API Reference\n\n### Endpoint\n\n```\nPOST https:\u002F\u002Fapi.tavily.com\u002Fresearch\n```\n\n### Headers\n\n| Header | Value |\n|--------|-------|\n| `Authorization` | `Bearer \u003CTAVILY_API_KEY>` |\n| `Content-Type` | `application\u002Fjson` |\n\n### Request Body\n\n| Field | Type | Default | Description |\n|-------|------|---------|-------------|\n| `input` | string | Required | Research topic or question |\n| `model` | string | `\"mini\"` | Model: `mini`, `pro`, `auto` |\n| `stream` | boolean | `false` | Streaming disabled for token management |\n| `output_schema` | object | null | JSON schema for structured output |\n| `citation_format` | string | `\"numbered\"` | Citation format: `numbered`, `mla`, `apa`, `chicago` |\n\n### Response Format (JSON)\n\nWith `stream: false`, the response is clean JSON:\n\n```json\n{\n  \"content\": \"# Research Results\\n\\n...\",\n  \"sources\": [{\"url\": \"https:\u002F\u002F...\", \"title\": \"Source Title\"}],\n  \"response_time\": 45.2\n}\n```\n\n## Model Selection\n\n**Rule of thumb**: \"what does X do?\" -> mini. \"X vs Y vs Z\" or \"best way to...\" -> pro.\n\n| Model | Use Case | Speed |\n|-------|----------|-------|\n| `mini` | Single topic, targeted research | ~30s |\n| `pro` | Comprehensive multi-angle analysis | ~60-120s |\n| `auto` | API chooses based on complexity | Varies |\n\n## Schema Usage\n\nSchemas make output structured and predictable. Every property **MUST** include both `type` and `description`.\n\n```json\n{\n  \"properties\": {\n    \"summary\": {\n      \"type\": \"string\",\n      \"description\": \"2-3 sentence executive summary\"\n    },\n    \"key_points\": {\n      \"type\": \"array\",\n      \"description\": \"Main takeaways\",\n      \"items\": {\"type\": \"string\"}\n    }\n  },\n  \"required\": [\"summary\", \"key_points\"]\n}\n```\n\n## Examples\n\n### Market Research\n\n```bash\ncurl --request POST \\\n  --url https:\u002F\u002Fapi.tavily.com\u002Fresearch \\\n  --header \"Authorization: Bearer $TAVILY_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"input\": \"Fintech startup landscape 2025\",\n    \"model\": \"pro\",\n    \"stream\": false,\n    \"citation_format\": \"numbered\",\n    \"output_schema\": {\n      \"properties\": {\n        \"market_overview\": {\"type\": \"string\", \"description\": \"Executive summary of fintech market\"},\n        \"top_startups\": {\n          \"type\": \"array\",\n          \"description\": \"Notable fintech startups\",\n          \"items\": {\n            \"type\": \"object\",\n            \"properties\": {\n              \"name\": {\"type\": \"string\", \"description\": \"Startup name\"},\n              \"focus\": {\"type\": \"string\", \"description\": \"Primary business focus\"},\n              \"funding\": {\"type\": \"string\", \"description\": \"Total funding raised\"}\n            },\n            \"required\": [\"name\", \"focus\"]\n          }\n        },\n        \"trends\": {\"type\": \"array\", \"description\": \"Key market trends\", \"items\": {\"type\": \"string\"}}\n      },\n      \"required\": [\"market_overview\", \"top_startups\"]\n    }\n  }'\n```\n\n### Technical Comparison\n\n```bash\ncurl --request POST \\\n  --url https:\u002F\u002Fapi.tavily.com\u002Fresearch \\\n  --header \"Authorization: Bearer $TAVILY_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"input\": \"LangGraph vs CrewAI for multi-agent systems\",\n    \"model\": \"pro\",\n    \"stream\": false,\n    \"citation_format\": \"mla\"\n  }'\n```\n\n### Quick Overview\n\n```bash\ncurl --request POST \\\n  --url https:\u002F\u002Fapi.tavily.com\u002Fresearch \\\n  --header \"Authorization: Bearer $TAVILY_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"input\": \"What is retrieval augmented generation?\",\n    \"model\": \"mini\",\n    \"stream\": false\n  }'\n```\n","# Research Skill\n\nConduct comprehensive research on any topic with automatic source gathering, analysis, and response generation with citations.\n\n## Prerequisites\n\n**Tavily API Key Required** - Get your key at https:\u002F\u002Ftavily.com\n\nAdd to `~\u002F.claude\u002Fsettings.json`:\n```json\n{\n  \"env\": {\n    \"TAVILY_API_KEY\": \"tvly-your-api-key-here\"\n  }\n}\n```\n\n## Quick Start\n\n> **Tip**: Research can take 30-120 seconds. Press **Ctrl+B** to run in the background.\n\n### Using the Script\n\n```bash\n.\u002Fscripts\u002Fresearch.sh '\u003Cjson>' [output_file]\n```\n\n**Examples:**\n```bash\n# Basic research\n.\u002Fscripts\u002Fresearch.sh '{\"input\": \"quantum computing trends\"}'\n\n# With pro model for comprehensive analysis\n.\u002Fscripts\u002Fresearch.sh '{\"input\": \"AI agents comparison\", \"model\": \"pro\"}'\n\n# Save to file\n.\u002Fscripts\u002Fresearch.sh '{\"input\": \"market analysis for EVs\", \"model\": \"pro\"}' .\u002Fev-report.md\n\n# With custom citation format\n.\u002Fscripts\u002Fresearch.sh '{\"input\": \"climate change impacts\", \"model\": \"mini\", \"citation_format\": \"apa\"}'\n\n# With structured output schema\n.\u002Fscripts\u002Fresearch.sh '{\"input\": \"fintech startups 2025\", \"model\": \"pro\", \"output_schema\": {\"properties\": {\"summary\": {\"type\": \"string\"}, \"companies\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}}}, \"required\": [\"summary\"]}}'\n```\n\n### Basic Research\n\n```bash\ncurl --request POST \\\n  --url https:\u002F\u002Fapi.tavily.com\u002Fresearch \\\n  --header \"Authorization: Bearer $TAVILY_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"input\": \"Latest developments in quantum computing\",\n    \"model\": \"mini\",\n    \"stream\": false,\n    \"citation_format\": \"numbered\"\n  }'\n```\n\n> **Note**: Streaming is disabled for token management. The call waits until research completes and returns clean JSON.\n\n### With Custom Schema\n\n```bash\ncurl --request POST \\\n  --url https:\u002F\u002Fapi.tavily.com\u002Fresearch \\\n  --header \"Authorization: Bearer $TAVILY_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"input\": \"Electric vehicle market analysis\",\n    \"model\": \"pro\",\n    \"stream\": false,\n    \"citation_format\": \"numbered\",\n    \"output_schema\": {\n      \"properties\": {\n        \"market_overview\": {\n          \"type\": \"string\",\n          \"description\": \"2-3 sentence overview of the market\"\n        },\n        \"key_players\": {\n          \"type\": \"array\",\n          \"description\": \"Major companies in this market\",\n          \"items\": {\n            \"type\": \"object\",\n            \"properties\": {\n              \"name\": {\"type\": \"string\", \"description\": \"Company name\"},\n              \"market_share\": {\"type\": \"string\", \"description\": \"Approximate market share\"}\n            },\n            \"required\": [\"name\"]\n          }\n        }\n      },\n      \"required\": [\"market_overview\", \"key_players\"]\n    }\n  }'\n```\n\n## API Reference\n\n### Endpoint\n\n```\nPOST https:\u002F\u002Fapi.tavily.com\u002Fresearch\n```\n\n### Headers\n\n| Header | Value |\n|--------|-------|\n| `Authorization` | `Bearer \u003CTAVILY_API_KEY>` |\n| `Content-Type` | `application\u002Fjson` |\n\n### Request Body\n\n| Field | Type | Default | Description |\n|-------|------|---------|-------------|\n| `input` | string | Required | Research topic or question |\n| `model` | string | `\"mini\"` | Model: `mini`, `pro`, `auto` |\n| `stream` | boolean | `false` | Streaming disabled for token management |\n| `output_schema` | object | null | JSON schema for structured output |\n| `citation_format` | string | `\"numbered\"` | Citation format: `numbered`, `mla`, `apa`, `chicago` |\n\n### Response Format (JSON)\n\nWith `stream: false`, the response is clean JSON:\n\n```json\n{\n  \"content\": \"# Research Results\\n\\n...\",\n  \"sources\": [{\"url\": \"https:\u002F\u002F...\", \"title\": \"Source Title\"}],\n  \"response_time\": 45.2\n}\n```\n\n## Model Selection\n\n**Rule of thumb**: \"what does X do?\" -> mini. \"X vs Y vs Z\" or \"best way to...\" -> pro.\n\n| Model | Use Case | Speed |\n|-------|----------|-------|\n| `mini` | Single topic, targeted research | ~30s |\n| `pro` | Comprehensive multi-angle analysis | ~60-120s |\n| `auto` | API chooses based on complexity | Varies |\n\n## Schema Usage\n\nSchemas make output structured and predictable. Every property **MUST** include both `type` and `description`.\n\n```json\n{\n  \"properties\": {\n    \"summary\": {\n      \"type\": \"string\",\n      \"description\": \"2-3 sentence executive summary\"\n    },\n    \"key_points\": {\n      \"type\": \"array\",\n      \"description\": \"Main takeaways\",\n      \"items\": {\"type\": \"string\"}\n    }\n  },\n  \"required\": [\"summary\", \"key_points\"]\n}\n```\n\n## Examples\n\n### Market Research\n\n```bash\ncurl --request POST \\\n  --url https:\u002F\u002Fapi.tavily.com\u002Fresearch \\\n  --header \"Authorization: Bearer $TAVILY_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"input\": \"Fintech startup landscape 2025\",\n    \"model\": \"pro\",\n    \"stream\": false,\n    \"citation_format\": \"numbered\",\n    \"output_schema\": {\n      \"properties\": {\n        \"market_overview\": {\"type\": \"string\", \"description\": \"Executive summary of fintech market\"},\n        \"top_startups\": {\n          \"type\": \"array\",\n          \"description\": \"Notable fintech startups\",\n          \"items\": {\n            \"type\": \"object\",\n            \"properties\": {\n              \"name\": {\"type\": \"string\", \"description\": \"Startup name\"},\n              \"focus\": {\"type\": \"string\", \"description\": \"Primary business focus\"},\n              \"funding\": {\"type\": \"string\", \"description\": \"Total funding raised\"}\n            },\n            \"required\": [\"name\", \"focus\"]\n          }\n        },\n        \"trends\": {\"type\": \"array\", \"description\": \"Key market trends\", \"items\": {\"type\": \"string\"}}\n      },\n      \"required\": [\"market_overview\", \"top_startups\"]\n    }\n  }'\n```\n\n### Technical Comparison\n\n```bash\ncurl --request POST \\\n  --url https:\u002F\u002Fapi.tavily.com\u002Fresearch \\\n  --header \"Authorization: Bearer $TAVILY_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"input\": \"LangGraph vs CrewAI for multi-agent systems\",\n    \"model\": \"pro\",\n    \"stream\": false,\n    \"citation_format\": \"mla\"\n  }'\n```\n\n### Quick Overview\n\n```bash\ncurl --request POST \\\n  --url https:\u002F\u002Fapi.tavily.com\u002Fresearch \\\n  --header \"Authorization: Bearer $TAVILY_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"input\": \"What is retrieval augmented generation?\",\n    \"model\": \"mini\",\n    \"stream\": false\n  }'\n```\n",{"name":5,"description":7},"main","f4cb2d49f7667e79ef7804f50396d5aaffdf1f56","人工智能与大型语言模型\u002Fresearch-2",1,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification","https:\u002F\u002Fgithub.com\u002FKernel8901","a little little little dobe in life but science geek","2026-04-05 16:43:56",{"source":8,"skillName":5,"commands":53,"prompt":63,"zipAvailable":64},[54,57,60],{"tool":55,"command":56},"npx","npx skills add Kernel8901\u002Fai-agent-skills-classification --skill research",{"tool":58,"command":59},"bunx","bunx skills add Kernel8901\u002Fai-agent-skills-classification --skill research",{"tool":61,"command":62},"pnpm","pnpm dlx skills add Kernel8901\u002Fai-agent-skills-classification --skill research","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fresearch-2\u002FSKILL.md",true,[66,72],{"path":67,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":70,"sourceHtmlUrl":71},"_meta.json","REFERENCE","参考文档",272,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fresearch-2\u002F_meta.json",{"path":73,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":76,"sourceHtmlUrl":77},"scripts\u002Fresearch.sh","SCRIPT","脚本",2412,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fresearch-2\u002Fscripts\u002Fresearch.sh",[79,102,136,147,157,186],{"skillNo":80,"name":81,"nameZh":6,"description":82,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":83,"categories":84,"keywords":85,"publishedAt":39},"01M6Q5R6WZ06RRB9RQTW54B34B","zyfai","Earn yield on any Ethereum wallet on Base, Arbitrum, and Plasma. Use when a user wants passive DeFi yield on their funds. Deploys a non-custodial subaccount (Safe) linked to their EOA, enables automated yield optimization, and lets them deposit\u002Fwithdraw anytime.","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzyfai-sdk\u002FSKILL.md",[],[81,86,87,88,89,90,31,91,92,93,94,95,96,97,98,99,100,101],"safe","ethereum","defi","Optimization","user","Wallet","base","deposit","withdraw","yield","arbitrum","non-custodial","passive","defi yield","earn","yield optimization",{"skillNo":103,"name":104,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":105,"categories":106,"keywords":118,"publishedAt":39},"01M6Q5R337B5JSNER4P4YS03TN","zerion-api","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api\u002FSKILL.md",[107,110,113],{"categoryNo":108,"categoryName":109,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":111,"categoryName":112,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":114,"categoryName":115,"taxonomyType":116,"taxonomyTypeDesc":117},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[119,120,121,122,123,124,125,88,126,91,127,128,129,130,131,132,133,134,135],"api","zerion api","zerion","MCP","mcp server","server","blockchain","transactions","crypto wallet","crypto","evm","solana","query","across","positions","token","prices",{"skillNo":137,"name":138,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":139,"categories":140,"keywords":144,"publishedAt":39},"01M6Q5QZFYTDAZMZ27BN5VZXAR","zerion-api-skill","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api-skill\u002FSKILL.md",[141,142,143],{"categoryNo":108,"categoryName":109,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":111,"categoryName":112,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":114,"categoryName":115,"taxonomyType":116,"taxonomyTypeDesc":117},[119,145,146,120,121,122,123,124,125,88,126,91,128,129,130,131,132,133,134,135],"api skill","zerion api skill",{"skillNo":148,"name":149,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":150,"categories":151,"keywords":155,"publishedAt":39},"01M6Q5QW17QW98RA3FE45E4RD8","zerion-api-mcp","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api-mcp\u002FSKILL.md",[152,153,154],{"categoryNo":108,"categoryName":109,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":111,"categoryName":112,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":114,"categoryName":115,"taxonomyType":116,"taxonomyTypeDesc":117},[122,119,156,120,121,123,124,88,126,91,127,128,129,130,131,132,133,134,135],"zerion api mcp",{"skillNo":158,"name":159,"nameZh":6,"description":160,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":161,"categories":162,"keywords":166,"publishedAt":39},"01M6Q5QQYZB7A501BDEQWKGSJT","yahoo-finance-forex","Fetches real-time FOREX news and market data from Yahoo Finance for major currency pairs (EUR\u002FUSD, GBP\u002FUSD, USD\u002FJPY, etc.). Analyzes sentiment and provides trading context.","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fyahoo-finance-forex\u002FSKILL.md",[163],{"categoryNo":164,"categoryName":165,"taxonomyType":116,"taxonomyTypeDesc":117},"01JBSEEDCAT000000000000040","财务",[167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,24],"finance","yahoo finance","forex","yahoo","yahoo finance forex","github","https","sentiment","real-time","python3","install","Market","usd","news","time","currency","gbp","pip","market data",{"skillNo":187,"name":188,"nameZh":6,"description":189,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":190,"categories":191,"keywords":193,"publishedAt":39},"01M6Q5QM6VS84WZVM7BKXXPF32","yahoo-finance","This skill should be used when the user asks to \"get stock prices\", \"check stock quotes\", \"look up earnings\", \"get financial data\", \"find trending stocks\", or needs stock market data from Yahoo Finance.","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fyahoo-finance-cli\u002FSKILL.md",[192],{"categoryNo":164,"categoryName":165,"taxonomyType":116,"taxonomyTypeDesc":117},[167,168,170,194,195,196,197,198,199,178,200,28,201,202,203,204,205,206,135,185],"cli","homebrew","find","check","brew","up","local","stock","link","trending","sf","quotes","ln"]