[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71NX935EDEN05BMFMB9SWXG":3,"skill-same:01M71NX935EDEN05BMFMB9SWXG":76},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":15,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":53,"ownerHtmlUrl":54,"ownerBlogUrl":55,"ownerDescription":6,"updatedAt":56,"install":57,"resources":70},"01M71NX935EDEN05BMFMB9SWXG","search",null,"Search across all connected sources in one query. Trigger with \"find that doc about...\", \"what did we decide on...\", \"where was the conversation about...\", or when looking for a decision, document, or discussion that could live in chat, email, cloud storage, or a project tracker.","monoes\u002Fmonomind","monoes","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F276744696?v=4","01M71KWF37AJ2NJBP3KWBVSDGT","01M71KWF4CSF8ADH0M6HA09VD2",23,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fsearch\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fsearch\u002FSKILL.md",[],[5,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"across","Enterprise","trigger","for","email","live","doc","storage","tracker","work","query","when","knowledge","Cloud Storage","decision","decide","project","sources","conversation","2026-11-10 10:56:23",false,"---\nname: search\ndescription: \"Search across all connected sources in one query. Trigger with \\\"find that doc about...\\\", \\\"what did we decide on...\\\", \\\"where was the conversation about...\\\", or when looking for a decision, document, or discussion that could live in chat, email, cloud storage, or a project tracker.\"\ntags: []\ntools: []\nlicense: Apache-2.0\nsource: https:\u002F\u002Fgithub.com\u002Fanthropics\u002Fknowledge-work-plugins\nsource_path: \"enterprise-search\u002Fskills\u002Fsearch\"\nsource_commit: 8444efcd48f7012f09797778a36a33e73d0861f4\n---\n# Search Command\n\n> If you see unfamiliar placeholders or need to check which tools are connected, see [CONNECTORS.md](..\u002F..\u002FCONNECTORS.md).\n\nSearch across all connected MCP sources in a single query. Decompose the user's question, run parallel searches, and synthesize results.\n\n## Instructions\n\n### 1. Check Available Sources\n\nBefore searching, determine which MCP sources are available. Attempt to identify connected tools from the available tool list. Common sources:\n\n- **~~chat** — chat platform tools\n- **~~email** — email tools\n- **~~cloud storage** — cloud storage tools\n- **~~project tracker** — project tracking tools\n- **~~CRM** — CRM tools\n- **~~knowledge base** — knowledge base tools\n\nIf no MCP sources are connected:\n```\nTo search across your tools, you'll need to connect at least one source.\nCheck your MCP settings to add ~~chat, ~~email, ~~cloud storage, or other tools.\n\nSupported sources: ~~chat, ~~email, ~~cloud storage, ~~project tracker, ~~CRM, ~~knowledge base,\nand any other MCP-connected service.\n```\n\n### 2. Parse the User's Query\n\nAnalyze the search query to understand:\n\n- **Intent**: What is the user looking for? (a decision, a document, a person, a status update, a conversation)\n- **Entities**: People, projects, teams, tools mentioned\n- **Time constraints**: Recency signals (\"this week\", \"last month\", specific dates)\n- **Source hints**: References to specific tools (\"in ~~chat\", \"that email\", \"the doc\")\n- **Filters**: Extract explicit filters from the query:\n  - `from:` — Filter by sender\u002Fauthor\n  - `in:` — Filter by channel, folder, or location\n  - `after:` — Only results after this date\n  - `before:` — Only results before this date\n  - `type:` — Filter by content type (message, email, doc, thread, file)\n\n### 3. Decompose into Sub-Queries\n\nFor each available source, create a targeted sub-query using that source's native search syntax:\n\n**~~chat:**\n- Use available search and read tools for your chat platform\n- Translate filters: `from:` maps to sender, `in:` maps to channel\u002Froom, dates map to time range filters\n- Use natural language queries for semantic search when appropriate\n- Use keyword queries for exact matches\n\n**~~email:**\n- Use available email search tools\n- Translate filters: `from:` maps to sender, dates map to time range filters\n- Map `type:` to attachment filters or subject-line searches as appropriate\n\n**~~cloud storage:**\n- Use available file search tools\n- Translate to file query syntax: name contains, full text contains, modified date, file type\n- Consider both file names and content\n\n**~~project tracker:**\n- Use available task search or typeahead tools\n- Map to task text search, assignee filters, date filters, project filters\n\n**~~CRM:**\n- Use available CRM query tools\n- Search across Account, Contact, Opportunity, and other relevant objects\n\n**~~knowledge base:**\n- Use semantic search for conceptual questions\n- Use keyword search for exact matches\n\n### 4. Execute Searches in Parallel\n\nRun all sub-queries simultaneously across available sources. Do not wait for one source before searching another.\n\nFor each source:\n- Execute the translated query\n- Capture results with metadata (timestamps, authors, links, source type)\n- Note any sources that fail or return errors — do not let one failure block others\n\n### 5. Rank and Deduplicate Results\n\n**Deduplication:**\n- Identify the same information appearing across sources (e.g., a decision discussed in ~~chat AND confirmed via email)\n- Group related results together rather than showing duplicates\n- Prefer the most authoritative or complete version\n\n**Ranking factors:**\n- **Relevance**: How well does the result match the query intent?\n- **Freshness**: More recent results rank higher for status\u002Fdecision queries\n- **Authority**: Official docs > wiki > chat messages for factual questions; conversations > docs for \"what did we discuss\" queries\n- **Completeness**: Results with more context rank higher\n\n### 6. Present Unified Results\n\nFormat the response as a synthesized answer, not a raw list of results:\n\n**For factual\u002Fdecision queries:**\n```\n[Direct answer to the question]\n\nSources:\n- [Source 1: brief description] (~~chat, #channel, date)\n- [Source 2: brief description] (~~email, from person, date)\n- [Source 3: brief description] (~~cloud storage, doc name, last modified)\n```\n\n**For exploratory queries (\"what do we know about X\"):**\n```\n[Synthesized summary combining information from all sources]\n\nFound across:\n- ~~chat: X relevant messages in Y channels\n- ~~email: X relevant threads\n- ~~cloud storage: X related documents\n- [Other sources as applicable]\n\nKey sources:\n- [Most important source with link\u002Freference]\n- [Second most important source]\n```\n\n**For \"find\" queries (looking for a specific thing):**\n```\n[The thing they're looking for, with direct reference]\n\nAlso found:\n- [Related items from other sources]\n```\n\n### 7. Handle Edge Cases\n\n**Ambiguous queries:**\nIf the query could mean multiple things, ask one clarifying question before searching:\n```\n\"API redesign\" could refer to a few things. Are you looking for:\n1. The REST API v2 redesign (Project Aurora)\n2. The internal SDK API changes\n3. Something else?\n```\n\n**No results:**\n```\nI couldn't find anything matching \"[query]\" across [list of sources searched].\n\nTry:\n- Broader terms (e.g., \"database\" instead of \"PostgreSQL migration\")\n- Different time range (currently searching [time range])\n- Checking if the relevant source is connected (currently searching: [sources])\n```\n\n**Partial results (some sources failed):**\n```\n[Results from successful sources]\n\nNote: I couldn't reach [failed source(s)] during this search.\nResults above are from [successful sources] only.\n```\n\n## Notes\n\n- Always search multiple sources in parallel — never sequentially\n- Synthesize results into answers, do not just list raw search results\n- Include source attribution so users can dig deeper\n- Respect the user's filter syntax and apply it appropriately per source\n- When a query mentions a specific person, search for their messages\u002Fdocs\u002Fmentions across all sources\n- For time-sensitive queries, prioritize recency in ranking\n- If only one source is connected, still provide useful results from that source\n","# Search Command\n\n> If you see unfamiliar placeholders or need to check which tools are connected, see [CONNECTORS.md](..\u002F..\u002FCONNECTORS.md).\n\nSearch across all connected MCP sources in a single query. Decompose the user's question, run parallel searches, and synthesize results.\n\n## Instructions\n\n### 1. Check Available Sources\n\nBefore searching, determine which MCP sources are available. Attempt to identify connected tools from the available tool list. Common sources:\n\n- **~~chat** — chat platform tools\n- **~~email** — email tools\n- **~~cloud storage** — cloud storage tools\n- **~~project tracker** — project tracking tools\n- **~~CRM** — CRM tools\n- **~~knowledge base** — knowledge base tools\n\nIf no MCP sources are connected:\n```\nTo search across your tools, you'll need to connect at least one source.\nCheck your MCP settings to add ~~chat, ~~email, ~~cloud storage, or other tools.\n\nSupported sources: ~~chat, ~~email, ~~cloud storage, ~~project tracker, ~~CRM, ~~knowledge base,\nand any other MCP-connected service.\n```\n\n### 2. Parse the User's Query\n\nAnalyze the search query to understand:\n\n- **Intent**: What is the user looking for? (a decision, a document, a person, a status update, a conversation)\n- **Entities**: People, projects, teams, tools mentioned\n- **Time constraints**: Recency signals (\"this week\", \"last month\", specific dates)\n- **Source hints**: References to specific tools (\"in ~~chat\", \"that email\", \"the doc\")\n- **Filters**: Extract explicit filters from the query:\n  - `from:` — Filter by sender\u002Fauthor\n  - `in:` — Filter by channel, folder, or location\n  - `after:` — Only results after this date\n  - `before:` — Only results before this date\n  - `type:` — Filter by content type (message, email, doc, thread, file)\n\n### 3. Decompose into Sub-Queries\n\nFor each available source, create a targeted sub-query using that source's native search syntax:\n\n**~~chat:**\n- Use available search and read tools for your chat platform\n- Translate filters: `from:` maps to sender, `in:` maps to channel\u002Froom, dates map to time range filters\n- Use natural language queries for semantic search when appropriate\n- Use keyword queries for exact matches\n\n**~~email:**\n- Use available email search tools\n- Translate filters: `from:` maps to sender, dates map to time range filters\n- Map `type:` to attachment filters or subject-line searches as appropriate\n\n**~~cloud storage:**\n- Use available file search tools\n- Translate to file query syntax: name contains, full text contains, modified date, file type\n- Consider both file names and content\n\n**~~project tracker:**\n- Use available task search or typeahead tools\n- Map to task text search, assignee filters, date filters, project filters\n\n**~~CRM:**\n- Use available CRM query tools\n- Search across Account, Contact, Opportunity, and other relevant objects\n\n**~~knowledge base:**\n- Use semantic search for conceptual questions\n- Use keyword search for exact matches\n\n### 4. Execute Searches in Parallel\n\nRun all sub-queries simultaneously across available sources. Do not wait for one source before searching another.\n\nFor each source:\n- Execute the translated query\n- Capture results with metadata (timestamps, authors, links, source type)\n- Note any sources that fail or return errors — do not let one failure block others\n\n### 5. Rank and Deduplicate Results\n\n**Deduplication:**\n- Identify the same information appearing across sources (e.g., a decision discussed in ~~chat AND confirmed via email)\n- Group related results together rather than showing duplicates\n- Prefer the most authoritative or complete version\n\n**Ranking factors:**\n- **Relevance**: How well does the result match the query intent?\n- **Freshness**: More recent results rank higher for status\u002Fdecision queries\n- **Authority**: Official docs > wiki > chat messages for factual questions; conversations > docs for \"what did we discuss\" queries\n- **Completeness**: Results with more context rank higher\n\n### 6. Present Unified Results\n\nFormat the response as a synthesized answer, not a raw list of results:\n\n**For factual\u002Fdecision queries:**\n```\n[Direct answer to the question]\n\nSources:\n- [Source 1: brief description] (~~chat, #channel, date)\n- [Source 2: brief description] (~~email, from person, date)\n- [Source 3: brief description] (~~cloud storage, doc name, last modified)\n```\n\n**For exploratory queries (\"what do we know about X\"):**\n```\n[Synthesized summary combining information from all sources]\n\nFound across:\n- ~~chat: X relevant messages in Y channels\n- ~~email: X relevant threads\n- ~~cloud storage: X related documents\n- [Other sources as applicable]\n\nKey sources:\n- [Most important source with link\u002Freference]\n- [Second most important source]\n```\n\n**For \"find\" queries (looking for a specific thing):**\n```\n[The thing they're looking for, with direct reference]\n\nAlso found:\n- [Related items from other sources]\n```\n\n### 7. Handle Edge Cases\n\n**Ambiguous queries:**\nIf the query could mean multiple things, ask one clarifying question before searching:\n```\n\"API redesign\" could refer to a few things. Are you looking for:\n1. The REST API v2 redesign (Project Aurora)\n2. The internal SDK API changes\n3. Something else?\n```\n\n**No results:**\n```\nI couldn't find anything matching \"[query]\" across [list of sources searched].\n\nTry:\n- Broader terms (e.g., \"database\" instead of \"PostgreSQL migration\")\n- Different time range (currently searching [time range])\n- Checking if the relevant source is connected (currently searching: [sources])\n```\n\n**Partial results (some sources failed):**\n```\n[Results from successful sources]\n\nNote: I couldn't reach [failed source(s)] during this search.\nResults above are from [successful sources] only.\n```\n\n## Notes\n\n- Always search multiple sources in parallel — never sequentially\n- Synthesize results into answers, do not just list raw search results\n- Include source attribution so users can dig deeper\n- Respect the user's filter syntax and apply it appropriately per source\n- When a query mentions a specific person, search for their messages\u002Fdocs\u002Fmentions across all sources\n- For time-sensitive queries, prioritize recency in ranking\n- If only one source is connected, still provide useful results from that source\n",{"name":5,"tags":43,"tools":44,"source":45,"license":14,"description":7,"source_path":46,"source_commit":47},[],[],"https:\u002F\u002Fgithub.com\u002Fanthropics\u002Fknowledge-work-plugins","enterprise-search\u002Fskills\u002Fsearch","8444efcd48f7012f09797778a36a33e73d0861f4","main","f7cd4595d0f8959822163e14f9787117765c931a","packages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fsearch",2,"https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind","https:\u002F\u002Fmonoes.github.io\u002Fmonomind\u002F","https:\u002F\u002Fgithub.com\u002Fmonoes","https:\u002F\u002Fmonoes.me","2026-11-10 01:53:48",{"source":8,"skillName":5,"commands":58,"prompt":68,"zipAvailable":69},[59,62,65],{"tool":60,"command":61},"npx","npx skills add monoes\u002Fmonomind --skill search",{"tool":63,"command":64},"bunx","bunx skills add monoes\u002Fmonomind --skill search",{"tool":66,"command":67},"pnpm","pnpm dlx skills add monoes\u002Fmonomind --skill search","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fsearch\u002FSKILL.md",true,[71],{"path":72,"resourceType":73,"resourceTypeDesc":74,"sizeBytes":75,"sourceHtmlUrl":15},"LICENSE.txt","LICENSE","许可证",11607,[77,103,139,165,189,216],{"skillNo":78,"name":79,"nameZh":6,"description":80,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":81,"categories":82,"keywords":83,"publishedAt":102},"01M71PB3SHWKMNJM6MD65VX8D6","zk-steward","Org role guidance for a ZK steward: engineer zero-knowledge proof systems with circuit design, SNARK vs STARK choice and security review. This is zero-knowledge cryptography, not Zettelkasten note-taking.","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fzk-steward\u002FSKILL.md",[],[84,85,86,87,88,89,90,31,91,29,92,93,94,95,96,97,98,99,100,101],"zk","zk steward","steward","zero-knowledge","engineer","choice","design","impact","snark","review","monomind","security review","stark","zettelkasten","cryptography","security","org","blockchain","2026-11-10 13:02:02",{"skillNo":104,"name":105,"nameZh":6,"description":106,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":107,"licenseFileUrl":108,"sourceHtmlUrl":109,"categories":110,"keywords":121,"publishedAt":102},"01M71PB18SDG28WBKPKJNB814K","writing-plans","Use when you have a spec or requirements for a multi-step coding task and must write an implementation plan before touching code. Produces bite-sized TDD tasks with exact file paths, code and commands for an engineer with zero context.","MIT","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fwriting-plans\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fwriting-plans\u002FSKILL.md",[111,116],{"categoryNo":112,"categoryName":113,"taxonomyType":114,"taxonomyTypeDesc":115},"01JBSEEDCAT000000000000018","写作与文案","SCENARIO","使用场景",{"categoryNo":117,"categoryName":118,"taxonomyType":119,"taxonomyTypeDesc":120},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[122,123,124,88,125,126,30,127,29,128,129,130,131,132,133,134,135,136,137,138],"writing","writing plans","plans","superpowers","implementation plan","you","code","tasks","plan","product","write","commands","paths","suggest","coding","context","ZeRO",{"skillNo":140,"name":141,"nameZh":6,"description":142,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":143,"sourceHtmlUrl":144,"categories":145,"keywords":149,"publishedAt":102},"01M71PAXFM488X9ARXK0T04TF5","write-spec","Write a feature spec or PRD from a problem statement or feature idea. 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