[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71GSZMK0AE7MFEPNKXZSCP8":3,"skill-same:01M71GSZMK0AE7MFEPNKXZSCP8":91},{"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":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":64,"commitSha":65,"skillDirectory":66,"forksCount":14,"repositoryHtmlUrl":67,"repositoryHomepageUrl":6,"ownerHtmlUrl":68,"ownerBlogUrl":6,"ownerDescription":69,"updatedAt":70,"install":71,"resources":84},"01M71GSZMK0AE7MFEPNKXZSCP8","query",null,"Answer questions using the brain's knowledge with 3-layer search, synthesis,\nand citation propagation. Use when the user asks a question, wants a lookup,\nor needs information from the brain.","weareturnone\u002Fgbrain","weareturnone","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F106660686?v=4","01M71GRFW4YZ9DFYK6J17YXQNB","Roelof Stoelwinder ","01M71GRFWVQF5ASVB08TP5VKWG",0,"MIT","https:\u002F\u002Fgithub.com\u002Fweareturnone\u002Fgbrain\u002Fblob\u002Fmaster\u002Fskills\u002Fquery\u002FSKILL.md",[],[5,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"notes","page","for","backlinks","do","graph","layer","list","brain","me","relationship","when","false","information","question","knowledge","up","search","get","2026-11-10 10:12:30",false,"---\nname: query\nversion: 1.0.0\ndescription: |\n  Answer questions using the brain's knowledge with 3-layer search, synthesis,\n  and citation propagation. Use when the user asks a question, wants a lookup,\n  or needs information from the brain.\ntriggers:\n  - \"what do we know about\"\n  - \"tell me about\"\n  - \"who is\"\n  - \"what happened\"\n  - \"search for\"\n  - \"look up\"\n  - \"background on\"\n  - \"notes on\"\n  - \"who knows who\"\n  - \"relationship between\"\n  - \"connections\"\n  - \"graph query\"\ntools:\n  - search\n  - query\n  - get_page\n  - list_pages\n  - get_backlinks\n  - traverse_graph\n  - get_timeline\nmutating: false\n---\n\n# Query Skill\n\nAnswer questions using the brain's knowledge with 3-layer search and synthesis.\n\n## Contract\n\nThis skill guarantees:\n- Every answer is grounded in brain content (no hallucination)\n- Every claim has a citation tracing back to a specific page slug\n- Gaps are flagged explicitly (\"the brain doesn't have information on X\")\n- Source precedence is respected (user statements > compiled truth > timeline > external)\n- Conflicting sources are noted with both citations\n\n## Phases\n\n1. **Decompose the question** into search strategies:\n   - Keyword search for specific names, dates, terms\n   - Semantic query for conceptual questions\n   - Structured queries (list by type, backlinks) for relational questions\n2. **Execute searches:**\n   - Keyword search gbrain for FTS matches (search)\n   - Hybrid search gbrain for semantic+keyword with expansion (query)\n   - List pages in gbrain by type or check backlinks for structural queries\n3. **Read top results.** Read the top 3-5 pages from gbrain to get full context.\n4. **Synthesize answer** with citations. Every claim traces back to a specific page slug.\n5. **Flag gaps.** If the brain doesn't have info, say \"the brain doesn't have information on X\" rather than hallucinating.\n\n## Anti-Patterns\n\n- Answering from general knowledge when the brain has relevant content\n- Hallucinating facts not in the brain\n- Silently picking one source when sources conflict\n- Loading full pages when search chunks are sufficient\n- Ignoring source precedence (user statements are highest authority)\n\n## Output Format\n\nAnswers should include:\n- Direct response to the question\n- Citations: \"According to [Source: people\u002Fjane-doe, compiled truth]...\"\n- Gap flags: \"The brain doesn't have information on X\"\n- Conflict notes when sources disagree\n\n## Quality Rules\n\n- Never hallucinate. Only answer from brain content.\n- Cite sources: \"According to concepts\u002Fdo-things-that-dont-scale...\"\n- Flag stale results: if a search result shows [STALE], note that the info may be outdated\n- For \"who\" questions, use backlinks and typed links to find connections\n- For \"what happened\" questions, use timeline entries\n- For \"what do we know\" questions, read compiled_truth directly\n\n## Token-Budget Awareness\n\nSearch returns **chunks**, not full pages. Read the excerpts first before deciding\nwhether to load a full page.\n\n- `gbrain search` \u002F `gbrain query` return ranked chunks with context snippets.\n  These are often enough to answer the question directly.\n- Only use `gbrain get \u003Cslug>` to load the full page when a chunk confirms the\n  page is relevant and you need more context (e.g., compiled truth, timeline).\n- **\"Tell me about X\"** -- get the full page (the user wants the complete picture).\n- **\"Did anyone mention Y?\"** -- search results are enough (the user wants a yes\u002Fno with evidence).\n\n### Source precedence\n\nWhen multiple sources provide conflicting information, follow this precedence:\n\n1. **User's direct statements** (highest authority -- what the user told you directly)\n2. **Compiled truth** (the brain's synthesized, cited understanding)\n3. **Timeline entries** (raw evidence, reverse-chronological)\n4. **External sources** (web search, API enrichment -- lowest authority)\n\nWhen sources conflict, note the contradiction with both citations. Don't silently\npick one.\n\n## Citation in Answers\n\nWhen referencing brain pages in your answer, propagate inline citations:\n- Cite the page: \"According to [Source: people\u002Fjane-doe, compiled truth]...\"\n- When brain pages have inline `[Source: ...]` citations, propagate them so\n  the user can trace facts to their origin\n- When you synthesize across multiple pages, cite all sources\n\n## Graph Traversal (v0.10.1+)\n\nFor relationship questions (\"who knows who at X?\", \"connections between A and B\",\n\"who works at Acme?\", \"who attended the standup?\"), use the graph layer instead\nof full-text search:\n\n- `gbrain graph-query \u003Cslug> --type \u003Clink_type> --depth N --direction in|out|both`\n- Available link types: `attended`, `works_at`, `invested_in`, `founded`, `advises`, `mentions`, `source`\n- `--direction in` answers \"who points to X?\" (e.g., who works at company X)\n- `--direction out` answers \"what does X point to?\" (default)\n- `--depth N` controls multi-hop traversal (default 5)\n\nExamples:\n- \"Who works at Acme?\" → `gbrain graph-query companies\u002Facme --type works_at --direction in`\n- \"Who attended Demo Day W26?\" → `gbrain graph-query meetings\u002Fdemo-day-w26 --type attended --direction out`\n- \"What companies has Emily advised?\" → `gbrain graph-query people\u002Femily --type advises --direction out`\n- \"Who has Alice met (via meetings)?\" → `gbrain graph-query people\u002Falice --type attended --depth 2`\n\nCombine with `gbrain query` for queries that need BOTH semantic similarity AND\ngraph structure. Search results are ranked with a small backlink boost so well-\nconnected entities surface higher.\n\n## Search Quality Awareness\n\nIf search results seem off (wrong results, missing known pages, irrelevant hits):\n- Run `gbrain doctor --json` to check index health\n- Check embedding coverage -- partial embeddings degrade hybrid search\n- Compare keyword search (`gbrain search`) vs hybrid search (`gbrain query`)\n  for the same query to isolate whether the issue is embedding-related\n- Report search quality issues in the maintain workflow (see maintain skill)\n\n## Tools Used\n\n- Keyword search gbrain (search)\n- Hybrid search gbrain (query)\n- Read a page from gbrain (get_page)\n- List pages in gbrain with filters (list_pages)\n- Check backlinks in gbrain (get_backlinks)\n- Traverse the link graph in gbrain (traverse_graph)\n- View timeline entries in gbrain (get_timeline)\n","# Query Skill\n\nAnswer questions using the brain's knowledge with 3-layer search and synthesis.\n\n## Contract\n\nThis skill guarantees:\n- Every answer is grounded in brain content (no hallucination)\n- Every claim has a citation tracing back to a specific page slug\n- Gaps are flagged explicitly (\"the brain doesn't have information on X\")\n- Source precedence is respected (user statements > compiled truth > timeline > external)\n- Conflicting sources are noted with both citations\n\n## Phases\n\n1. **Decompose the question** into search strategies:\n   - Keyword search for specific names, dates, terms\n   - Semantic query for conceptual questions\n   - Structured queries (list by type, backlinks) for relational questions\n2. **Execute searches:**\n   - Keyword search gbrain for FTS matches (search)\n   - Hybrid search gbrain for semantic+keyword with expansion (query)\n   - List pages in gbrain by type or check backlinks for structural queries\n3. **Read top results.** Read the top 3-5 pages from gbrain to get full context.\n4. **Synthesize answer** with citations. Every claim traces back to a specific page slug.\n5. **Flag gaps.** If the brain doesn't have info, say \"the brain doesn't have information on X\" rather than hallucinating.\n\n## Anti-Patterns\n\n- Answering from general knowledge when the brain has relevant content\n- Hallucinating facts not in the brain\n- Silently picking one source when sources conflict\n- Loading full pages when search chunks are sufficient\n- Ignoring source precedence (user statements are highest authority)\n\n## Output Format\n\nAnswers should include:\n- Direct response to the question\n- Citations: \"According to [Source: people\u002Fjane-doe, compiled truth]...\"\n- Gap flags: \"The brain doesn't have information on X\"\n- Conflict notes when sources disagree\n\n## Quality Rules\n\n- Never hallucinate. Only answer from brain content.\n- Cite sources: \"According to concepts\u002Fdo-things-that-dont-scale...\"\n- Flag stale results: if a search result shows [STALE], note that the info may be outdated\n- For \"who\" questions, use backlinks and typed links to find connections\n- For \"what happened\" questions, use timeline entries\n- For \"what do we know\" questions, read compiled_truth directly\n\n## Token-Budget Awareness\n\nSearch returns **chunks**, not full pages. Read the excerpts first before deciding\nwhether to load a full page.\n\n- `gbrain search` \u002F `gbrain query` return ranked chunks with context snippets.\n  These are often enough to answer the question directly.\n- Only use `gbrain get \u003Cslug>` to load the full page when a chunk confirms the\n  page is relevant and you need more context (e.g., compiled truth, timeline).\n- **\"Tell me about X\"** -- get the full page (the user wants the complete picture).\n- **\"Did anyone mention Y?\"** -- search results are enough (the user wants a yes\u002Fno with evidence).\n\n### Source precedence\n\nWhen multiple sources provide conflicting information, follow this precedence:\n\n1. **User's direct statements** (highest authority -- what the user told you directly)\n2. **Compiled truth** (the brain's synthesized, cited understanding)\n3. **Timeline entries** (raw evidence, reverse-chronological)\n4. **External sources** (web search, API enrichment -- lowest authority)\n\nWhen sources conflict, note the contradiction with both citations. Don't silently\npick one.\n\n## Citation in Answers\n\nWhen referencing brain pages in your answer, propagate inline citations:\n- Cite the page: \"According to [Source: people\u002Fjane-doe, compiled truth]...\"\n- When brain pages have inline `[Source: ...]` citations, propagate them so\n  the user can trace facts to their origin\n- When you synthesize across multiple pages, cite all sources\n\n## Graph Traversal (v0.10.1+)\n\nFor relationship questions (\"who knows who at X?\", \"connections between A and B\",\n\"who works at Acme?\", \"who attended the standup?\"), use the graph layer instead\nof full-text search:\n\n- `gbrain graph-query \u003Cslug> --type \u003Clink_type> --depth N --direction in|out|both`\n- Available link types: `attended`, `works_at`, `invested_in`, `founded`, `advises`, `mentions`, `source`\n- `--direction in` answers \"who points to X?\" (e.g., who works at company X)\n- `--direction out` answers \"what does X point to?\" (default)\n- `--depth N` controls multi-hop traversal (default 5)\n\nExamples:\n- \"Who works at Acme?\" → `gbrain graph-query companies\u002Facme --type works_at --direction in`\n- \"Who attended Demo Day W26?\" → `gbrain graph-query meetings\u002Fdemo-day-w26 --type attended --direction out`\n- \"What companies has Emily advised?\" → `gbrain graph-query people\u002Femily --type advises --direction out`\n- \"Who has Alice met (via meetings)?\" → `gbrain graph-query people\u002Falice --type attended --depth 2`\n\nCombine with `gbrain query` for queries that need BOTH semantic similarity AND\ngraph structure. Search results are ranked with a small backlink boost so well-\nconnected entities surface higher.\n\n## Search Quality Awareness\n\nIf search results seem off (wrong results, missing known pages, irrelevant hits):\n- Run `gbrain doctor --json` to check index health\n- Check embedding coverage -- partial embeddings degrade hybrid search\n- Compare keyword search (`gbrain search`) vs hybrid search (`gbrain query`)\n  for the same query to isolate whether the issue is embedding-related\n- Report search quality issues in the maintain workflow (see maintain skill)\n\n## Tools Used\n\n- Keyword search gbrain (search)\n- Hybrid search gbrain (query)\n- Read a page from gbrain (get_page)\n- List pages in gbrain with filters (list_pages)\n- Check backlinks in gbrain (get_backlinks)\n- Traverse the link graph in gbrain (traverse_graph)\n- View timeline entries in gbrain (get_timeline)\n",{"name":5,"tools":43,"version":49,"mutating":39,"triggers":50,"description":63},[36,5,44,45,46,47,48],"get_page","list_pages","get_backlinks","traverse_graph","get_timeline","1.0.0",[51,52,53,54,55,56,57,58,59,60,61,62],"what do we know about","tell me about","who is","what happened","search for","look up","background on","notes on","who knows who","relationship between","connections","graph query","Answer questions using the brain's knowledge with 3-layer search, synthesis,\nand citation propagation. Use when the user asks a question, wants a lookup,\nor needs information from the brain.\n","master","1fd9e273fe234ffb8d2a7705955f087f861a5c3d","skills\u002Fquery","https:\u002F\u002Fgithub.com\u002Fweareturnone\u002Fgbrain","https:\u002F\u002Fgithub.com\u002Fweareturnone","I have a passion for operations, systems and doing good for the world.","2026-07-08 23:38:19",{"source":8,"skillName":5,"commands":72,"prompt":82,"zipAvailable":83},[73,76,79],{"tool":74,"command":75},"npx","npx skills add weareturnone\u002Fgbrain --skill query",{"tool":77,"command":78},"bunx","bunx skills add weareturnone\u002Fgbrain --skill query",{"tool":80,"command":81},"pnpm","pnpm dlx skills add weareturnone\u002Fgbrain --skill query","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fweareturnone\u002Fgbrain\u002Fblob\u002Fmaster\u002Fskills\u002Fquery\u002FSKILL.md",true,[85],{"path":86,"resourceType":87,"resourceTypeDesc":88,"sizeBytes":89,"sourceHtmlUrl":90},"routing-eval.jsonl","OTHER","其他",535,"https:\u002F\u002Fgithub.com\u002Fweareturnone\u002Fgbrain\u002Fblob\u002Fmaster\u002Fskills\u002Fquery\u002Frouting-eval.jsonl",[92,108,118,133,149,170],{"skillNo":93,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":96,"categories":97,"keywords":98,"publishedAt":38},"01M71GTZ2PH49PD2R6RR7MHJZP","signal-detector","Always-on ambient signal capture for the OpenClaw reference fixture.","https:\u002F\u002Fgithub.com\u002Fweareturnone\u002Fgbrain\u002Fblob\u002Fmaster\u002Ftest\u002Ffixtures\u002Fopenclaw-reference-minimal\u002Fskills\u002Fsignal-detector\u002FSKILL.md",[],[99,100,101,21,102,103,104,105,106,107],"signal","signal detector","detector","openclaw","capture","reference","message","fixture","ambient",{"skillNo":109,"name":5,"nameZh":6,"description":110,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":111,"categories":112,"keywords":113,"publishedAt":38},"01M71GTY1250DC73PGRWDE82KW","Look up brain pages in the OpenClaw reference fixture.","https:\u002F\u002Fgithub.com\u002Fweareturnone\u002Fgbrain\u002Fblob\u002Fmaster\u002Ftest\u002Ffixtures\u002Fopenclaw-reference-minimal\u002Fskills\u002Fquery\u002FSKILL.md",[],[5,23,104,114,102,115,116,35,27,36,117,21,106],"lookup","look","pages","about",{"skillNo":119,"name":120,"nameZh":6,"description":121,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":122,"categories":123,"keywords":124,"publishedAt":38},"01M71GTX0T1T9224P29SD7CSG7","context-now","ALWAYS-ON time-sensitivity discipline for the OpenClaw reference fixture.","https:\u002F\u002Fgithub.com\u002Fweareturnone\u002Fgbrain\u002Fblob\u002Fmaster\u002Ftest\u002Ffixtures\u002Fopenclaw-reference-minimal\u002Fskills\u002Fcontext-now\u002FSKILL.md",[],[125,126,127,128,129,102,21,130,104,106,131,132],"context","context now","now","time","how","discipline","sensitivity","long",{"skillNo":134,"name":135,"nameZh":6,"description":136,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":137,"categories":138,"keywords":139,"publishedAt":38},"01M71GTVZJTSWXBM4ZRF4A7QVA","brain-ops","Core read\u002Fwrite cycle for the OpenClaw reference fixture.","https:\u002F\u002Fgithub.com\u002Fweareturnone\u002Fgbrain\u002Fblob\u002Fmaster\u002Ftest\u002Ffixtures\u002Fopenclaw-reference-minimal\u002Fskills\u002Fbrain-ops\u002FSKILL.md",[],[140,27,141,142,114,102,143,104,144,21,145,146,147,106,148],"brain ops","ops","Citation","people","true","read","cycle","core","write",{"skillNo":150,"name":151,"nameZh":6,"description":152,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":153,"categories":154,"keywords":155,"publishedAt":38},"01M71GTT4F64V9RMNZ0WRTKWNG","webhook-transforms","Generic framework for converting external events (SMS, meetings, social mentions)\ninto brain-ingestible signals. Define a transform function, register a webhook URL,\nand incoming events get processed through the brain pipeline.","https:\u002F\u002Fgithub.com\u002Fweareturnone\u002Fgbrain\u002Fblob\u002Fmaster\u002Fskills\u002Fwebhook-transforms\u002FSKILL.md",[],[156,157,158,159,160,35,161,162,163,164,144,165,36,166,167,20,21,168,169,37],"webhook","transforms","webhook transforms","SET","register","meetings","signals","URL","define","social","event","pipeline","sms","generic",{"skillNo":171,"name":172,"nameZh":6,"description":173,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":174,"categories":175,"keywords":189,"publishedAt":38},"01M71GTRDKSM500PRZEXFNQHF9","testing","Skill validation framework. Validates every skill has SKILL.md with frontmatter,\nevery reference exists, every env var is declared. The testing contract for the\nskill system itself.","https:\u002F\u002Fgithub.com\u002Fweareturnone\u002Fgbrain\u002Fblob\u002Fmaster\u002Fskills\u002Ftesting\u002FSKILL.md",[176,181,184],{"categoryNo":177,"categoryName":178,"taxonomyType":179,"taxonomyTypeDesc":180},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",{"categoryNo":182,"categoryName":183,"taxonomyType":179,"taxonomyTypeDesc":180},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":185,"categoryName":186,"taxonomyType":187,"taxonomyTypeDesc":188},"01JBSEEDCAT000000000000037","律师与法务","PROFESSION","适用职业",[172,190,191,192,193,194,195,196,197,198,199,31,200,201,116,202,36,203,204,21],"test skills","validation","run","health check","test","with","health","check","env","skill validation","contract","tests","skill health","system","validate skills"]