[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6CSA5BPAA6F75CJZEZFFTCT":3,"skill-same:01M6CSA5BPAA6F75CJZEZFFTCT":83},{"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":26,"publishedAt":47,"linkOnly":48,"markdownContent":49,"markdownBody":50,"frontMatter":51,"refName":61,"commitSha":62,"skillDirectory":63,"forksCount":64,"repositoryHtmlUrl":65,"repositoryHomepageUrl":65,"ownerHtmlUrl":66,"ownerBlogUrl":6,"ownerDescription":67,"updatedAt":68,"install":69,"resources":82},"01M6CSA5BPAA6F75CJZEZFFTCT","bdistill-knowledge-extraction",null,"Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.","Sam-06060\u002Fjarvis-assistant","Sam-06060","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F208600848?v=4","01M6CRKT7C7FXD21V6HXF293S0","Samson Frank Ganta","01M6CRKTBEKYFD8YX5Z1GT99EE",6,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FSam-06060\u002Fjarvis-assistant\u002Fblob\u002Fmain\u002Fmodules\u002Fagent_skills\u002Fawesome-skills\u002Fplaybooks\u002Fbdistill-knowledge-extraction\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46],"bdistill knowledge extraction","extraction","knowledge","ollama","reference-data","data-moat","domain-specific","knowledge-extraction","domain","community","models","session","MCP","open","api","data","copilot","research","codex","safe","2026-11-10 10:12:30",false,"---\nname: bdistill-knowledge-extraction\ndescription: \"Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.\"\ncategory: ai-research\nrisk: safe\nsource: community\ndate_added: \"2026-03-20\"\nauthor: FrancyJGLisboa\ntags: [ai, knowledge-extraction, domain-specific, data-moat, mcp, reference-data]\ntools: [claude, cursor, codex, copilot]\n---\n\n# Knowledge Extraction\n\nExtract structured, quality-scored domain knowledge from any AI model — in-session from closed models (no API key) or locally from open-source models via Ollama.\n\n## Overview\n\nbdistill turns your AI subscription sessions into a compounding knowledge base. The agent answers targeted domain questions, bdistill structures and quality-scores the responses, and the output accumulates into a searchable, exportable reference dataset.\n\nAdversarial mode challenges the agent's claims — forcing evidence, corrections, and acknowledged limitations — producing validated knowledge entries.\n\n## When to Use This Skill\n\n- Use when you need structured reference data on any domain (medical, legal, finance, cybersecurity)\n- Use when building lookup tables, Q&A datasets, or research corpora\n- Use when generating training data for traditional ML models (regression, classification — NOT competing LLMs)\n- Use when you want cross-model comparison on domain knowledge\n\n## How It Works\n\n### Step 1: Install\n\n```bash\npip install bdistill\nclaude mcp add bdistill -- bdistill-mcp   # Claude Code\n```\n\n### Step 2: Extract knowledge in-session\n\n```\n\u002Fdistill medical cardiology                    # Preset domain\n\u002Fdistill --custom kubernetes docker helm       # Custom terms\n\u002Fdistill --adversarial medical                 # With adversarial validation\n```\n\n### Step 3: Search, export, compound\n\n```bash\nbdistill kb list                               # Show all domains\nbdistill kb search \"atrial fibrillation\"       # Keyword search\nbdistill kb export -d medical -f csv           # Export as spreadsheet\nbdistill kb export -d medical -f markdown      # Readable knowledge document\n```\n\n## Output Format\n\nStructured reference JSONL — not training data:\n\n```json\n{\n  \"question\": \"What causes myocardial infarction?\",\n  \"answer\": \"Myocardial infarction results from acute coronary artery occlusion...\",\n  \"domain\": \"medical\",\n  \"category\": \"cardiology\",\n  \"tags\": [\"mechanistic\", \"evidence-based\"],\n  \"quality_score\": 0.73,\n  \"confidence\": 1.08,\n  \"validated\": true,\n  \"source_model\": \"Claude Sonnet 4\"\n}\n```\n\n## Tabular ML Data Generation\n\nGenerate structured training data for traditional ML models:\n\n```\n\u002Fschema sepsis | hr:float, bp:float, temp:float, wbc:float | risk:category[low,moderate,high,critical]\n```\n\nExports as CSV ready for pandas\u002Fsklearn. Each row tracks source_model for cross-model analysis.\n\n## Local Model Extraction (Ollama)\n\nFor open-source models running locally:\n\n```bash\n# Install Ollama from https:\u002F\u002Follama.com\nollama serve\nollama pull qwen3:4b\n\nbdistill extract --domain medical --model qwen3:4b\n```\n\n## Security & Safety Notes\n\n- In-session extraction uses your existing subscription — no additional API keys\n- Local extraction runs entirely on your machine via Ollama\n- No data is sent to external services\n- Output is reference data, not LLM training format\n\n## Related Skills\n\n- `@bdistill-behavioral-xray` - X-ray a model's behavioral patterns\n","# Knowledge Extraction\n\nExtract structured, quality-scored domain knowledge from any AI model — in-session from closed models (no API key) or locally from open-source models via Ollama.\n\n## Overview\n\nbdistill turns your AI subscription sessions into a compounding knowledge base. The agent answers targeted domain questions, bdistill structures and quality-scores the responses, and the output accumulates into a searchable, exportable reference dataset.\n\nAdversarial mode challenges the agent's claims — forcing evidence, corrections, and acknowledged limitations — producing validated knowledge entries.\n\n## When to Use This Skill\n\n- Use when you need structured reference data on any domain (medical, legal, finance, cybersecurity)\n- Use when building lookup tables, Q&A datasets, or research corpora\n- Use when generating training data for traditional ML models (regression, classification — NOT competing LLMs)\n- Use when you want cross-model comparison on domain knowledge\n\n## How It Works\n\n### Step 1: Install\n\n```bash\npip install bdistill\nclaude mcp add bdistill -- bdistill-mcp   # Claude Code\n```\n\n### Step 2: Extract knowledge in-session\n\n```\n\u002Fdistill medical cardiology                    # Preset domain\n\u002Fdistill --custom kubernetes docker helm       # Custom terms\n\u002Fdistill --adversarial medical                 # With adversarial validation\n```\n\n### Step 3: Search, export, compound\n\n```bash\nbdistill kb list                               # Show all domains\nbdistill kb search \"atrial fibrillation\"       # Keyword search\nbdistill kb export -d medical -f csv           # Export as spreadsheet\nbdistill kb export -d medical -f markdown      # Readable knowledge document\n```\n\n## Output Format\n\nStructured reference JSONL — not training data:\n\n```json\n{\n  \"question\": \"What causes myocardial infarction?\",\n  \"answer\": \"Myocardial infarction results from acute coronary artery occlusion...\",\n  \"domain\": \"medical\",\n  \"category\": \"cardiology\",\n  \"tags\": [\"mechanistic\", \"evidence-based\"],\n  \"quality_score\": 0.73,\n  \"confidence\": 1.08,\n  \"validated\": true,\n  \"source_model\": \"Claude Sonnet 4\"\n}\n```\n\n## Tabular ML Data Generation\n\nGenerate structured training data for traditional ML models:\n\n```\n\u002Fschema sepsis | hr:float, bp:float, temp:float, wbc:float | risk:category[low,moderate,high,critical]\n```\n\nExports as CSV ready for pandas\u002Fsklearn. Each row tracks source_model for cross-model analysis.\n\n## Local Model Extraction (Ollama)\n\nFor open-source models running locally:\n\n```bash\n# Install Ollama from https:\u002F\u002Follama.com\nollama serve\nollama pull qwen3:4b\n\nbdistill extract --domain medical --model qwen3:4b\n```\n\n## Security & Safety Notes\n\n- In-session extraction uses your existing subscription — no additional API keys\n- Local extraction runs entirely on your machine via Ollama\n- No data is sent to external services\n- Output is reference data, not LLM training format\n\n## Related Skills\n\n- `@bdistill-behavioral-xray` - X-ray a model's behavioral patterns\n",{"name":5,"risk":46,"tags":52,"tools":55,"author":58,"source":36,"category":59,"date_added":60,"description":7},[53,34,33,32,54,31],"ai","mcp",[56,57,45,43],"claude","cursor","FrancyJGLisboa","ai-research","2026-03-20","main","a50a3aa6b39fb0e1b7db88bef1bfc9c93606e126","modules\u002Fagent_skills\u002Fawesome-skills\u002Fplaybooks\u002Fbdistill-knowledge-extraction",0,"https:\u002F\u002Fgithub.com\u002FSam-06060\u002Fjarvis-assistant","https:\u002F\u002Fgithub.com\u002FSam-06060","Mobile Application Developer | Kotlin | Flutter, KMP, Swfit, Android,Swift UI | Building at Saar It Resources | Creator of Jarvis (AI Assistant)","2026-06-23 05:13:38",{"source":8,"skillName":5,"commands":70,"prompt":80,"zipAvailable":81},[71,74,77],{"tool":72,"command":73},"npx","npx skills add Sam-06060\u002Fjarvis-assistant --skill bdistill-knowledge-extraction",{"tool":75,"command":76},"bunx","bunx skills add Sam-06060\u002Fjarvis-assistant --skill bdistill-knowledge-extraction",{"tool":78,"command":79},"pnpm","pnpm dlx skills add Sam-06060\u002Fjarvis-assistant --skill bdistill-knowledge-extraction","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FSam-06060\u002Fjarvis-assistant\u002Fblob\u002Fmain\u002Fmodules\u002Fagent_skills\u002Fawesome-skills\u002Fplaybooks\u002Fbdistill-knowledge-extraction\u002FSKILL.md",true,[],[84,95,111,135,154,180],{"skillNo":85,"name":86,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":87,"categories":88,"keywords":92,"publishedAt":47},"01M6GDRVS6FXX3ESH0C9DW01C0","test_skill","https:\u002F\u002Fgithub.com\u002FSam-06060\u002Fjarvis-assistant\u002Fblob\u002Fmain\u002Fscratch\u002Ftest_skill\u002FSKILL.md",[89],{"categoryNo":90,"categoryName":91,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",[93,94],"Test Skill","test",{"skillNo":96,"name":97,"nameZh":6,"description":98,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":99,"categories":100,"keywords":101,"publishedAt":47},"01M6GDRQ40HX22MA6XWC31RHHK","zustand-store-ts","Create Zustand stores following established patterns with proper TypeScript types and middleware.","https:\u002F\u002Fgithub.com\u002FSam-06060\u002Fjarvis-assistant\u002Fblob\u002Fmain\u002Fmodules\u002Fagent_skills\u002Fawesome-skills\u002Fplaybooks\u002Fzustand-store-ts\u002FSKILL.md",[],[102,103,104,105,106,107,108,36,109,110],"zustand store ts","zustand","store","with","types","middleware","patterns","create","typescript",{"skillNo":112,"name":113,"nameZh":6,"description":114,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":115,"categories":116,"keywords":118,"publishedAt":47},"01M6GDRKEA0WE670SPFWX5GKCN","zoom-automation","Automate Zoom meeting creation, management, recordings, webinars, and participant tracking via Rube MCP (Composio). 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Always search tools first for current schemas.","https:\u002F\u002Fgithub.com\u002FSam-06060\u002Fjarvis-assistant\u002Fblob\u002Fmain\u002Fmodules\u002Fagent_skills\u002Fawesome-skills\u002Fplaybooks\u002Fzoho-crm-automation\u002FSKILL.md",[141],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[143,119,144,145,146,147,148,36,124,149,131,150,128,127,123,151,109,152,39,153],"crm automation","zoho crm","crm","zoho crm automation","zoho","leads","contacts","records","update","tasks","manage",{"skillNo":155,"name":156,"nameZh":6,"description":157,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":158,"categories":159,"keywords":163,"publishedAt":47},"01M6GDRCKQBAVTGHX5XBH26KPZ","zod-validation-expert","Expert in Zod — TypeScript-first schema validation. 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Use for auditing C\u002FC++\u002FRust code handling secrets, keys, passwords, or other sensitive data.","https:\u002F\u002Fgithub.com\u002FSam-06060\u002Fjarvis-assistant\u002Fblob\u002Fmain\u002Fmodules\u002Fagent_skills\u002Fawesome-skills\u002Fplaybooks\u002Fzeroize-audit\u002FSKILL.md",[186],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[188,189,190,191,192,193,194,195,36,196,197,198,199,200,42,201,202,203,204,39],"zeroize audit","audit","write","passwords","get","project","c++","activate","assembly","read","Bash","secrets","analysis","flow","verification","code","rust"]