[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6JBYRBM832N79M735PRGPRX":3,"skill-same:01M6JBYRBM832N79M735PRGPRX":75},{"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":17,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":43,"commitSha":44,"skillDirectory":45,"forksCount":46,"repositoryHtmlUrl":47,"repositoryHomepageUrl":48,"ownerHtmlUrl":49,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":50,"install":51,"resources":64},"01M6JBYRBM832N79M735PRGPRX","cognify-ops",null,"Operating patterns for Cognify knowledge graph ingestion — model selection, key sourcing, batch strategy, Drive\u002FTypeform extraction, and priority source ranking for the ramzy tenant.","S3YED\u002Fappie-kit","S3YED","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F62743867?v=4","01M6JBKBRRVP6KMS0VWZ27T3R6","01M6JBKBX0KG30284PW1DBYJT1",14,"MIT","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fcognify-ops\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"cognify ops","cognify","ops","patterns","tenant","sourcing","source","for","typeform","operating","ranking","model selection","selection","drive","ingestion","strategy","model","knowledge","knowledge graph","batch","2026-11-10 10:12:30",false,"---\nname: cognify-ops\ndescription: Operating patterns for Cognify knowledge graph ingestion — model selection, key sourcing, batch strategy, Drive\u002FTypeform extraction, and priority source ranking for the ramzy tenant.\n---\n\n# Cognify operations (ingestion patterns)\n\n## Model selection (CRITICAL)\nDefault to `openai\u002Fgpt-4o-mini` for entity extraction. DeepSeek V4 Flash hangs on\nmulti-chunk documents. gpt-4o-mini completes the same document in 25-40s.\n\nSet: `COGNIFY_LLM_MODEL=openai\u002Fgpt-4o-mini` in `\u002Froot\u002Fcognify\u002F.env`\n\n## Key sourcing\nCognify's `.env` key goes stale. When extraction fails with \"No LLM key\", source the\nworking key from Hermes' env. **Use Python to write `.env`, never shell heredocs** —\nspecial chars in API keys cause silent corruption.\n\n```python\nimport subprocess\nr = subprocess.run([\"grep\", \"-v\", \"^#\", \"\u002Froot\u002F.hermes\u002F.env\"], capture_output=True, text=True)\nfor line in r.stdout.split('\\n'):\n    if 'OPENROUTER_API_KEY' in line and '=' in line:\n        key = line.split('=', 1)[1].strip().strip('\"').strip(\"'\")\n        with open(\"\u002Froot\u002Fcognify\u002F.env\", \"w\") as f:\n            f.write(f\"OPENROUTER_API_KEY={key}\\n\")\n            f.write(\"COGNIFY_LLM_BASE=https:\u002F\u002Fopenrouter.ai\u002Fapi\u002Fv1\\n\")\n            f.write(\"COGNIFY_LLM_MODEL=openai\u002Fgpt-4o-mini\\n\")\n            f.write(\"COGNIFY_LLM_KEYENV=OPENROUTER_API_KEY\\n\")\n            f.write(\"COGNIFY_BACKEND=local\\n\")\n            f.write(\"COGNIFY_EXTRACT_WORKERS=4\\n\")\n        break\n```\n\n## Batch ingestion strategy\nCombine many small files into batches before ingesting. Use `ingest-dir` with workers:\n\n```bash\ncd \u002Froot\u002Fcognify && set -a && . .\u002F.env && set +a && export COGNIFY_DATA_DIR=\u002Froot\u002F.cognify\n.\u002F.venv\u002Fbin\u002Fcognify --tenant ramzy ingest-dir \u002Fpath\u002Fto\u002Fdir --workers 4\n```\n\nPerformance (gpt-4o-mini, 4 workers): ~17K chars\u002F25s, ~35K chars\u002F38s, ~42K chars\u002F42s.\n\n## Google Drive transcript extraction\n`gws drive files export` returns 401 even when `gws drive files list` works.\nWorkaround: direct Drive API with access token from `~\u002F.config\u002Fgws\u002Ftokens.json`.\n\nRefresh expired tokens: `python3 \u002Froot\u002F.hermes\u002Fscripts\u002Frefresh_google_token.py`\n\n## Typeform response extraction\nContact blocks have nested sub-fields. Recursively parse form definition for ref→label map\nbefore extracting response answers. See `references\u002Ftypeform-extraction.md`.\n\n## Priority sources for KG (ramzy tenant)\n1. Giveaway Notes — lead profiles with pain points, blocks, plays\n2. Call transcripts (Gemini notes in Google Drive) — conversation data, closes\n3. Typeform responses (form `N4LbJCHT`) — structured lead intake\n4. Testimonials (`~\u002Fibrahim-lowticket\u002F*.txt`) — client stories for voice\n5. Funnel blueprint, VSL scripts, roster — business strategy","# Cognify operations (ingestion patterns)\n\n## Model selection (CRITICAL)\nDefault to `openai\u002Fgpt-4o-mini` for entity extraction. DeepSeek V4 Flash hangs on\nmulti-chunk documents. gpt-4o-mini completes the same document in 25-40s.\n\nSet: `COGNIFY_LLM_MODEL=openai\u002Fgpt-4o-mini` in `\u002Froot\u002Fcognify\u002F.env`\n\n## Key sourcing\nCognify's `.env` key goes stale. When extraction fails with \"No LLM key\", source the\nworking key from Hermes' env. **Use Python to write `.env`, never shell heredocs** —\nspecial chars in API keys cause silent corruption.\n\n```python\nimport subprocess\nr = subprocess.run([\"grep\", \"-v\", \"^#\", \"\u002Froot\u002F.hermes\u002F.env\"], capture_output=True, text=True)\nfor line in r.stdout.split('\\n'):\n    if 'OPENROUTER_API_KEY' in line and '=' in line:\n        key = line.split('=', 1)[1].strip().strip('\"').strip(\"'\")\n        with open(\"\u002Froot\u002Fcognify\u002F.env\", \"w\") as f:\n            f.write(f\"OPENROUTER_API_KEY={key}\\n\")\n            f.write(\"COGNIFY_LLM_BASE=https:\u002F\u002Fopenrouter.ai\u002Fapi\u002Fv1\\n\")\n            f.write(\"COGNIFY_LLM_MODEL=openai\u002Fgpt-4o-mini\\n\")\n            f.write(\"COGNIFY_LLM_KEYENV=OPENROUTER_API_KEY\\n\")\n            f.write(\"COGNIFY_BACKEND=local\\n\")\n            f.write(\"COGNIFY_EXTRACT_WORKERS=4\\n\")\n        break\n```\n\n## Batch ingestion strategy\nCombine many small files into batches before ingesting. Use `ingest-dir` with workers:\n\n```bash\ncd \u002Froot\u002Fcognify && set -a && . .\u002F.env && set +a && export COGNIFY_DATA_DIR=\u002Froot\u002F.cognify\n.\u002F.venv\u002Fbin\u002Fcognify --tenant ramzy ingest-dir \u002Fpath\u002Fto\u002Fdir --workers 4\n```\n\nPerformance (gpt-4o-mini, 4 workers): ~17K chars\u002F25s, ~35K chars\u002F38s, ~42K chars\u002F42s.\n\n## Google Drive transcript extraction\n`gws drive files export` returns 401 even when `gws drive files list` works.\nWorkaround: direct Drive API with access token from `~\u002F.config\u002Fgws\u002Ftokens.json`.\n\nRefresh expired tokens: `python3 \u002Froot\u002F.hermes\u002Fscripts\u002Frefresh_google_token.py`\n\n## Typeform response extraction\nContact blocks have nested sub-fields. Recursively parse form definition for ref→label map\nbefore extracting response answers. See `references\u002Ftypeform-extraction.md`.\n\n## Priority sources for KG (ramzy tenant)\n1. Giveaway Notes — lead profiles with pain points, blocks, plays\n2. Call transcripts (Gemini notes in Google Drive) — conversation data, closes\n3. Typeform responses (form `N4LbJCHT`) — structured lead intake\n4. Testimonials (`~\u002Fibrahim-lowticket\u002F*.txt`) — client stories for voice\n5. Funnel blueprint, VSL scripts, roster — business strategy",{"name":5,"description":7},"master","8ec37df6d71fb664ea19d32c079e7d3ff931a8e0","skills\u002Fcognify-ops",3,"https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit","https:\u002F\u002Fweblyfe.ai","https:\u002F\u002Fgithub.com\u002FS3YED","2026-08-27 01:54:02",{"source":8,"skillName":5,"commands":52,"prompt":62,"zipAvailable":63},[53,56,59],{"tool":54,"command":55},"npx","npx skills add S3YED\u002Fappie-kit --skill cognify-ops",{"tool":57,"command":58},"bunx","bunx skills add S3YED\u002Fappie-kit --skill cognify-ops",{"tool":60,"command":61},"pnpm","pnpm dlx skills add S3YED\u002Fappie-kit --skill cognify-ops","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fcognify-ops\u002FSKILL.md",true,[65,71],{"path":66,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":69,"sourceHtmlUrl":70},"references\u002Fdrive-extraction.md","REFERENCE","参考文档",1228,"https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fcognify-ops\u002Freferences\u002Fdrive-extraction.md",{"path":72,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":73,"sourceHtmlUrl":74},"references\u002Ftypeform-extraction.md",1170,"https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fcognify-ops\u002Freferences\u002Ftypeform-extraction.md",[76,112,146,171,202,226],{"skillNo":77,"name":78,"nameZh":6,"description":79,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":80,"categories":81,"keywords":93,"publishedAt":38},"01M6JFD4M6N4DSGC7TXEJ5R3J2","ai-music","AI music generation and audio tools: HeartMuLa lyrics-to-music generation, songwriting craft (+ Suno prompts), and audio spectrogram\u002Ffeature visualization.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fwethlete\u002Fai-music\u002FSKILL.md",[82,87,90],{"categoryNo":83,"categoryName":84,"taxonomyType":85,"taxonomyTypeDesc":86},"01JBSEEDCAT000000000000013","分析与可视化","SCENARIO","使用场景",{"categoryNo":88,"categoryName":89,"taxonomyType":85,"taxonomyTypeDesc":86},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":91,"categoryName":92,"taxonomyType":85,"taxonomyTypeDesc":86},"01JBSEEDCAT000000000000023","Skill与智能体开发",[94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111],"music","ai music","humanizer","visualization","Tools","Audio","hermes","hermes agent","songwriting","suno","lyrics","prompts","heartmula","craft","generation","feature","ai music generation","music generation",{"skillNo":113,"name":114,"nameZh":6,"description":115,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":116,"categories":117,"keywords":126,"publishedAt":38},"01M6JFCZE4XNFQFMNZDHKHT5V5","agentic-webdesign-design-system-ingestion","Use v0 Design Systems 2.0, Bolt Design System Agents, or Lovable to generate production UI from a client's real design system components — not generic Tailwind. Use when building a client website where brand consistency matters.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fweb-design\u002Fagentic-webdesign-design-system-ingestion\u002FSKILL.md",[118,121],{"categoryNo":119,"categoryName":120,"taxonomyType":85,"taxonomyTypeDesc":86},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":122,"categoryName":123,"taxonomyType":124,"taxonomyTypeDesc":125},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[127,128,129,130,32,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145],"design","agentic","design system","system","webdesign","agentic webdesign design system ingestion","components","generate","design systems","website","ui","Tailwind","bolt","lovable","v0","design-system","wed","design system components","appie",{"skillNo":147,"name":148,"nameZh":6,"description":149,"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":154,"publishedAt":38},"01M6JFCVPX3913CFAS6QQJ33ZB","agentic-webdesign-agent-elements","Use 21st.dev Agent Elements — 25 shadcn\u002Fui components purpose-built for AI agent UIs. Tool cards (Bash, Edit, Search, Plan, Subagent, MCP), chat, input, streaming. Open source, shadcn-registry install, no runtime lock-in.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fweb-design\u002Fagentic-webdesign-agent-elements\u002FSKILL.md",[152,153],{"categoryNo":91,"categoryName":92,"taxonomyType":85,"taxonomyTypeDesc":86},{"categoryNo":122,"categoryName":123,"taxonomyType":124,"taxonomyTypeDesc":125},[128,155,131,156,157,158,133,159,160,161,162,163,164,165,166,167,168,169,170,24],"elements","agentic webdesign agent elements","MCP","ai agent","registry","search","streaming","open source","open","Bash","plan","subagent","edit","install","input","lock",{"skillNo":172,"name":173,"nameZh":6,"description":174,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":175,"categories":176,"keywords":181,"publishedAt":38},"01M6JFCQC7H65M9QJ6TRE71BS1","vercel-deployment","Deploy static sites and frontends to Vercel — handles both CLI and REST API paths, including the CLI token sanitization workaround.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fsoftware-development\u002Fvercel-deployment\u002FSKILL.md",[177,180],{"categoryNo":178,"categoryName":179,"taxonomyType":85,"taxonomyTypeDesc":86},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":91,"categoryName":92,"taxonomyType":85,"taxonomyTypeDesc":86},[182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201],"deployment","vercel deployment","vercel","macos","cli","linux","windows","deploy","vercel deploy","REST","api","site","deploy to vercel","token","rest api","host","sites","paths","sanitization","static site",{"skillNo":203,"name":204,"nameZh":6,"description":205,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":206,"categories":207,"keywords":209,"publishedAt":38},"01M6JFCM4SMTXBM5A01BK2YQG1","software-quality-workflows","Umbrella workflow for TDD, debugging, code simplification, spikes, pre-commit review, and debugger-assisted investigation.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fsoftware-development\u002Fsoftware-quality-workflows\u002FSKILL.md",[208],{"categoryNo":91,"categoryName":92,"taxonomyType":85,"taxonomyTypeDesc":86},[210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,25],"workflows","quality","software","software quality workflows","review","tdd","workflow","commit","debugging","code","debugger","pre-commit","investigation","code simplification","user","simplification",{"skillNo":227,"name":228,"nameZh":6,"description":229,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":230,"categories":231,"keywords":239,"publishedAt":38},"01M6JFCGD0M6CEATY01W7YN6DB","react-component-refactoring","Safely refactor large React components into smaller, maintainable pieces using proven patterns","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fsoftware-development\u002Freact-component-refactoring\u002FSKILL.md",[232,235,238],{"categoryNo":233,"categoryName":234,"taxonomyType":85,"taxonomyTypeDesc":86},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":236,"categoryName":237,"taxonomyType":85,"taxonomyTypeDesc":86},"01JBSEEDCAT000000000000009","前端开发",{"categoryNo":91,"categoryName":92,"taxonomyType":85,"taxonomyTypeDesc":86},[240,241,242,243,244,245,246,247,185,248,249,133,250,188,251,219,252,253,21,254],"react","component","refactoring","component refactoring","react component","react component refactoring","frontend","writing","safe","typescript","react components","modular","refactor","simplify","test-driven-development"]