[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6NV05TYVQ51GCNFVCJ5YNZM":3,"skill-same:01M6NV05TYVQ51GCNFVCJ5YNZM":72},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":50,"commitSha":51,"skillDirectory":52,"forksCount":14,"repositoryHtmlUrl":53,"repositoryHomepageUrl":6,"ownerHtmlUrl":54,"ownerBlogUrl":55,"ownerDescription":56,"updatedAt":57,"install":58,"resources":71},"01M6NV05TYVQ51GCNFVCJ5YNZM","harvest-structured",null,"Structured data extraction - tables, pricing, products, API endpoints with schema","rubicanjr\u002FFinCognis","rubicanjr","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F234912519?v=4","01M6NT156NND8J474G34SB3923","Rubi","01M6NT15B70RWXE1N3YV0BZY8A",0,"MIT","https:\u002F\u002Fgithub.com\u002Frubicanjr\u002FFinCognis\u002Fblob\u002Fmain\u002Fskills\u002Fharvest-structured\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"harvest structured","harvest","structured","write","with","Data Extraction","endpoints","schema","webfetch","extract","structured data","read","json","Bash","scrape","api","data","csv","product","pricing","2026-11-10 10:12:30",false,"---\nname: harvest-structured\ndescription: Structured data extraction - tables, pricing, products, API endpoints with schema\nallowed-tools: [Bash, Read, Write, WebFetch]\nkeywords: [scrape, structured, data, extract, schema, table, pricing, product, json, csv]\n---\n\n# Harvest Structured\n\nExtract structured data from web pages using user-defined schemas. Turns messy HTML into clean JSON\u002FCSV - pricing tables, product listings, API endpoint docs, comparison matrices.\n\n## Usage\n\n```\n\u002Fscrape \u003Curl> --schema \"\u003Cfield descriptions>\"\n```\n\n## Examples\n\n```bash\n# Extract pricing data\n\u002Fscrape https:\u002F\u002Fexample.com\u002Fpricing --schema \"plan_name, price, features[], cta_text\"\n\n# Extract product listings\n\u002Fscrape https:\u002F\u002Fstore.example.com\u002Fproducts --schema \"name, price, rating, reviews_count, image_url\"\n\n# Extract API endpoints\n\u002Fscrape https:\u002F\u002Fdocs.api.com\u002Freference --schema \"method, path, description, parameters[], response_code\"\n```\n\n## Schema Definition\n\nDefine fields as comma-separated names. Use `[]` for arrays:\n\n```\nname            → Single text value\nprice           → Single value (auto-detects currency)\nfeatures[]      → Array of items\ndescription     → Long text\nurl             → Auto-detects links\nimage_url       → Auto-detects image sources\n```\n\n## How It Works\n\n1. Fetch page content\n2. Parse schema definition\n3. Use CSS selectors or LLM extraction to match fields\n4. Validate extracted data against schema\n5. Output as JSON (default) or CSV\n\n## Output Format\n\n### JSON (default)\n```json\n[\n  {\n    \"plan_name\": \"Pro\",\n    \"price\": \"$29\u002Fmo\",\n    \"features\": [\"Unlimited projects\", \"Priority support\", \"API access\"],\n    \"source_url\": \"https:\u002F\u002Fexample.com\u002Fpricing\"\n  }\n]\n```\n\n### CSV\n```csv\nplan_name,price,features,source_url\nPro,\"$29\u002Fmo\",\"Unlimited projects; Priority support; API access\",https:\u002F\u002Fexample.com\u002Fpricing\n```\n\n## Integration\n\n- **growth**: Competitor pricing extraction\n- **migrator**: Changelog\u002Fbreaking changes extraction\n- **tech-radar**: Feature comparison across tools\n- **data-analyst**: Structured data for analysis\n\n## Rules\n\n- Only extract publicly visible data\n- Respect rate limits (1 req\u002Fsec)\n- Validate schema before extraction\n- Report confidence per field (high\u002Fmedium\u002Flow)\n- Output includes source URL for every record\n","# Harvest Structured\n\nExtract structured data from web pages using user-defined schemas. Turns messy HTML into clean JSON\u002FCSV - pricing tables, product listings, API endpoint docs, comparison matrices.\n\n## Usage\n\n```\n\u002Fscrape \u003Curl> --schema \"\u003Cfield descriptions>\"\n```\n\n## Examples\n\n```bash\n# Extract pricing data\n\u002Fscrape https:\u002F\u002Fexample.com\u002Fpricing --schema \"plan_name, price, features[], cta_text\"\n\n# Extract product listings\n\u002Fscrape https:\u002F\u002Fstore.example.com\u002Fproducts --schema \"name, price, rating, reviews_count, image_url\"\n\n# Extract API endpoints\n\u002Fscrape https:\u002F\u002Fdocs.api.com\u002Freference --schema \"method, path, description, parameters[], response_code\"\n```\n\n## Schema Definition\n\nDefine fields as comma-separated names. Use `[]` for arrays:\n\n```\nname            → Single text value\nprice           → Single value (auto-detects currency)\nfeatures[]      → Array of items\ndescription     → Long text\nurl             → Auto-detects links\nimage_url       → Auto-detects image sources\n```\n\n## How It Works\n\n1. Fetch page content\n2. Parse schema definition\n3. Use CSS selectors or LLM extraction to match fields\n4. Validate extracted data against schema\n5. Output as JSON (default) or CSV\n\n## Output Format\n\n### JSON (default)\n```json\n[\n  {\n    \"plan_name\": \"Pro\",\n    \"price\": \"$29\u002Fmo\",\n    \"features\": [\"Unlimited projects\", \"Priority support\", \"API access\"],\n    \"source_url\": \"https:\u002F\u002Fexample.com\u002Fpricing\"\n  }\n]\n```\n\n### CSV\n```csv\nplan_name,price,features,source_url\nPro,\"$29\u002Fmo\",\"Unlimited projects; Priority support; API access\",https:\u002F\u002Fexample.com\u002Fpricing\n```\n\n## Integration\n\n- **growth**: Competitor pricing extraction\n- **migrator**: Changelog\u002Fbreaking changes extraction\n- **tech-radar**: Feature comparison across tools\n- **data-analyst**: Structured data for analysis\n\n## Rules\n\n- Only extract publicly visible data\n- Respect rate limits (1 req\u002Fsec)\n- Validate schema before extraction\n- Report confidence per field (high\u002Fmedium\u002Flow)\n- Output includes source URL for every record\n",{"name":5,"keywords":44,"description":7,"allowed-tools":46},[33,21,35,28,26,45,38,37,31,36],"table",[32,47,48,49],"Read","Write","WebFetch","main","70e1c350500ee750987420bbae48837afa906b7e","skills\u002Fharvest-structured","https:\u002F\u002Fgithub.com\u002Frubicanjr\u002FFinCognis","https:\u002F\u002Fgithub.com\u002Frubicanjr","linktr.ee\u002Ffinanskodu","Industrial Engineer & CIO @FinansKodu. Architecting AI-driven financial agents and autonomous workflows. 🏗️ Building systems, not just prompts.","2026-06-09 13:50:15",{"source":8,"skillName":5,"commands":59,"prompt":69,"zipAvailable":70},[60,63,66],{"tool":61,"command":62},"npx","npx skills add rubicanjr\u002FFinCognis --skill harvest-structured",{"tool":64,"command":65},"bunx","bunx skills add rubicanjr\u002FFinCognis --skill harvest-structured",{"tool":67,"command":68},"pnpm","pnpm dlx skills add rubicanjr\u002FFinCognis --skill harvest-structured","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Frubicanjr\u002FFinCognis\u002Fblob\u002Fmain\u002Fskills\u002Fharvest-structured\u002FSKILL.md",true,[],[73,94,103,123,153,172],{"skillNo":74,"name":75,"nameZh":6,"description":76,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":77,"categories":78,"keywords":84,"publishedAt":39},"01M6NWS9DAXJTADT4T5MB49X8W","workflow-router","Goal-based workflow orchestration - routes tasks to specialist agents based on user goals","https:\u002F\u002Fgithub.com\u002Frubicanjr\u002FFinCognis\u002Fblob\u002Fmain\u002Fskills\u002Fworkflow-router\u002FSKILL.md",[79],{"categoryNo":80,"categoryName":81,"taxonomyType":82,"taxonomyTypeDesc":83},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[85,86,87,88,89,90,91,92,93],"workflow router","workflow","router","orchestration","goals","goal","user","workflow orchestration","tasks",{"skillNo":95,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":98,"categories":99,"keywords":100,"publishedAt":39},"01M6NWS3RETSC0SHP16HP66E14","wiring","Wiring Verification","https:\u002F\u002Fgithub.com\u002Frubicanjr\u002FFinCognis\u002Fblob\u002Fmain\u002Fskills\u002Fwiring\u002FSKILL.md",[],[96,101,102],"verification","false",{"skillNo":104,"name":105,"nameZh":6,"description":106,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":107,"categories":108,"keywords":112,"publishedAt":39},"01M6NWS0XW9CVQZBDA1EGW0TWC","websocket-patterns","Connection management, room patterns, reconnection strategies, message buffering, and binary protocol design.","https:\u002F\u002Fgithub.com\u002Frubicanjr\u002FFinCognis\u002Fblob\u002Fmain\u002Fskills\u002Fwebsocket-patterns\u002Fskill.md",[109],{"categoryNo":110,"categoryName":111,"taxonomyType":82,"taxonomyTypeDesc":83},"01JBSEEDCAT000000000000015","视觉设计",[113,114,115,116,117,118,119,120,121,122],"websocket","patterns","websocket patterns","design","protocol","management","message","strategies","binary","connection",{"skillNo":124,"name":125,"nameZh":6,"description":126,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":127,"categories":128,"keywords":133,"publishedAt":39},"01M6NWRDQDX9ZNETAWRRMQWV52","visual-verdict","Screenshot comparison QA for frontend development. Takes a screenshot of the current implementation, scores it across multiple visual dimensions, and returns a structured PASS\u002FREVISE\u002FFAIL verdict with concrete fixes. Use when implementing UI from a design reference or verifying visual correctness.","https:\u002F\u002Fgithub.com\u002Frubicanjr\u002FFinCognis\u002Fblob\u002Fmain\u002Fskills\u002Fvisual-verdict\u002FSKILL.md",[129,132],{"categoryNo":130,"categoryName":131,"taxonomyType":82,"taxonomyTypeDesc":83},"01JBSEEDCAT000000000000009","前端开发",{"categoryNo":80,"categoryName":81,"taxonomyType":82,"taxonomyTypeDesc":83},[134,135,136,137,138,139,140,141,142,143,144,145,146,116,147,148,149,150,151,152],"visual","verdict","visual verdict","ui","across","revise","comparison","correctness","implementing","for","fixes","dimensions","frontend","development","qa","screenshot","returns","use","frontend development",{"skillNo":154,"name":155,"nameZh":6,"description":156,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":157,"categories":158,"keywords":159,"publishedAt":39},"01M6NWR8HSNRS7MNDK2J02QYMN","verification-loop","Comprehensive verification system covering build, types, lint, tests, security, and diff review before a PR.","https:\u002F\u002Fgithub.com\u002Frubicanjr\u002FFinCognis\u002Fblob\u002Fmain\u002Fskills\u002Fverification-loop\u002FSKILL.md",[],[160,161,101,162,163,164,165,166,167,168,169,170,171],"verification loop","loop","lint","review","security","pr","system","diff","build","tests","diff review","types",{"skillNo":173,"name":174,"nameZh":6,"description":175,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":176,"categories":177,"keywords":178,"publishedAt":39},"01M6NWR4HHSFR0VR5EXFRWA747","vector-db-patterns","Embedding strategies, ANN algorithms, hybrid search, RAG chunking strategies, and reranking for semantic search and retrieval.","https:\u002F\u002Fgithub.com\u002Frubicanjr\u002FFinCognis\u002Fblob\u002Fmain\u002Fskills\u002Fvector-db-patterns\u002Fskill.md",[],[179,180,181,182,114,183,184,185,186,120,187,188,189,190,191,143,192,193],"vector db patterns","vector db","db","vector","semantic search","search","embedding strategies","algorithms","chunking","semantic","retrieval","embedding","Hybrid Search","hybrid","rag"]