[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M69B224K2SZR8VSVB4JJQAMR":3,"skill-same:01M69B224K2SZR8VSVB4JJQAMR":80},{"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":23,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":50,"commitSha":51,"skillDirectory":52,"forksCount":53,"repositoryHtmlUrl":54,"repositoryHomepageUrl":55,"ownerHtmlUrl":56,"ownerBlogUrl":57,"ownerDescription":58,"updatedAt":59,"install":60,"resources":73},"01M69B224K2SZR8VSVB4JJQAMR","wiki-llms-txt",null,"Generates llms.txt and llms-full.txt files for LLM-friendly project documentation following the llms.txt specification. Use when the user wants to create LLM-readable summaries, llms.txt files, or make their wiki accessible to language models.","microsoft\u002Fskills","microsoft","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6154722?v=4","01M698VYDXZ6JW5WH3CRV650R8","Microsoft","01M69AJYYW4E1RMSYCQDJ4FJSH",3204,"MIT","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fplugins\u002Fdeep-wiki\u002Fskills\u002Fwiki-llms-txt\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,9],"wiki llms txt","llms txt","wiki","llms","specification","when","language models","project documentation","summaries","for","full","project","language","models","files","use","user","create","documentation","2026-11-10 10:12:30",false,"---\nname: wiki-llms-txt\ndescription: Generates llms.txt and llms-full.txt files for LLM-friendly project documentation following the llms.txt specification. Use when the user wants to create LLM-readable summaries, llms.txt files, or make their wiki accessible to language models.\nlicense: MIT\nmetadata:\n  author: Microsoft\n  version: \"1.0.0\"\n---\n\n# llms.txt Generator\n\nGenerate `llms.txt` and `llms-full.txt` files that provide LLM-friendly access to wiki documentation, following the [llms.txt specification](https:\u002F\u002Fllmstxt.org\u002F).\n\n## When This Skill Activates\n\n- User asks to generate `llms.txt` or mentions the llms.txt standard\n- User wants to make documentation \"LLM-friendly\" or \"LLM-readable\"\n- User asks for a project summary file for language models\n- User mentions `llms-full.txt` or context-expanded documentation\n\n## Source Repository Resolution (MUST DO FIRST)\n\nBefore generating, resolve the source repository context:\n\n1. **Check for git remote**: Run `git remote get-url origin`\n2. **Ask the user**: _\"Is this a local-only repository, or do you have a source repository URL?\"_\n   - Remote URL → store as `REPO_URL`\n   - Local → use relative paths only\n3. **Determine default branch**: Run `git rev-parse --abbrev-ref HEAD`\n4. **Do NOT proceed** until resolved\n\n## llms.txt Format (Spec-Compliant)\n\nThe file follows the [llms.txt specification](https:\u002F\u002Fllmstxt.org\u002F):\n\n```markdown\n# {Project Name}\n\n> {Dense one-paragraph summary — what it does, who it's for, key technologies}\n\n{Important context paragraphs — constraints, architectural philosophy, non-obvious things}\n\n## {Section Name}\n\n- [{Page Title}]({relative-path-to-md}): {One-sentence description of what the reader will learn}\n\n## Optional\n\n- [{Page Title}]({relative-path-to-md}): {Description — these can be skipped for shorter context}\n```\n\n### Key Rules\n\n1. **H1** — Project name (exactly one, required)\n2. **Blockquote** — Dense, specific summary (required). Must be unique to THIS project.\n3. **Context paragraphs** — Non-obvious constraints, things LLMs would get wrong without being told\n4. **H2 sections** — Organized by topic, each with a list of `[Title](url): Description` entries\n5. **\"Optional\" H2** — Special meaning: links here can be skipped for shorter context\n6. **Relative links** — All paths relative to wiki directory\n7. **Dynamic** — ALL content derived from actual wiki pages, not templates\n8. **Section order** — Most important first: Onboarding → Architecture → Getting Started → Deep Dive → Optional\n\n### Description Quality\n\n| ❌ Bad | ✅ Good |\n|--------|---------|\n| \"Architecture overview\" | \"System architecture showing how Orleans grains communicate via message passing with at-least-once delivery\" |\n| \"Getting started guide\" | \"Prerequisites, local dev setup with Docker Compose, and first API call walkthrough\" |\n| \"The API reference\" | \"REST endpoints with auth requirements, rate limits, and request\u002Fresponse schemas\" |\n\n## llms-full.txt Format\n\nSame structure as `llms.txt` but with full content inlined:\n\n```markdown\n# {Project Name}\n\n> {Same summary}\n\n{Same context}\n\n## {Section Name}\n\n\u003Cdoc title=\"{Page Title}\" path=\"{relative-path}\">\n{Full markdown content — frontmatter stripped, citations and diagrams preserved}\n\u003C\u002Fdoc>\n```\n\n### Inlining Rules\n\n- **Strip YAML frontmatter** (`---` blocks) from each page\n- **Preserve Mermaid diagrams** — keep `` ```mermaid `` fences intact\n- **Preserve citations** — all `[file:line](URL)` links stay as-is\n- **Preserve tables** — all markdown tables stay intact\n- **Preserve `\u003C!-- Sources: -->` comments** — these provide diagram provenance\n\n## Prerequisites\n\nThis skill works best when wiki pages already exist (via `\u002Fdeep-wiki:generate` or `\u002Fdeep-wiki:page`). If no wiki exists yet:\n\n1. Suggest running `\u002Fdeep-wiki:generate` first\n2. OR generate a minimal `llms.txt` from README + source code scan (without wiki page links)\n\n## Output Files\n\nGenerate three files:\n\n| File | Purpose | Discoverability |\n|------|---------|-----------------|\n| `.\u002Fllms.txt` | Root discovery file | Standard path per llms.txt spec. GitHub MCP `get_file_contents` and `search_code` find this first. |\n| `wiki\u002Fllms.txt` | Wiki-relative links | For VitePress deployment and wiki-internal navigation. |\n| `wiki\u002Fllms-full.txt` | Full inlined content | Comprehensive reference for agents needing all docs in one file. |\n\nThe root `.\u002Fllms.txt` links into `wiki\u002F` (e.g., `[Guide](.\u002Fwiki\u002Fonboarding\u002Fcontributor-guide.md)`). The `wiki\u002Fllms.txt` uses wiki-relative paths (e.g., `[Guide](.\u002Fonboarding\u002Fcontributor-guide.md)`).\n\nIf a root `llms.txt` already exists and was NOT generated by deep-wiki, do NOT overwrite it.\n\n## Validation Checklist\n\nBefore finalizing:\n\n- [ ] All linked files in `llms.txt` actually exist\n- [ ] All `\u003Cdoc>` blocks in `llms-full.txt` have real content (not empty)\n- [ ] Blockquote is specific to this project (not generic boilerplate)\n- [ ] Sections ordered by importance\n- [ ] No duplicate page entries across sections\n- [ ] \"Optional\" section only contains truly optional content\n- [ ] `llms.txt` is concise (1-5 KB)\n- [ ] `llms-full.txt` contains all wiki pages\n","# llms.txt Generator\n\nGenerate `llms.txt` and `llms-full.txt` files that provide LLM-friendly access to wiki documentation, following the [llms.txt specification](https:\u002F\u002Fllmstxt.org\u002F).\n\n## When This Skill Activates\n\n- User asks to generate `llms.txt` or mentions the llms.txt standard\n- User wants to make documentation \"LLM-friendly\" or \"LLM-readable\"\n- User asks for a project summary file for language models\n- User mentions `llms-full.txt` or context-expanded documentation\n\n## Source Repository Resolution (MUST DO FIRST)\n\nBefore generating, resolve the source repository context:\n\n1. **Check for git remote**: Run `git remote get-url origin`\n2. **Ask the user**: _\"Is this a local-only repository, or do you have a source repository URL?\"_\n   - Remote URL → store as `REPO_URL`\n   - Local → use relative paths only\n3. **Determine default branch**: Run `git rev-parse --abbrev-ref HEAD`\n4. **Do NOT proceed** until resolved\n\n## llms.txt Format (Spec-Compliant)\n\nThe file follows the [llms.txt specification](https:\u002F\u002Fllmstxt.org\u002F):\n\n```markdown\n# {Project Name}\n\n> {Dense one-paragraph summary — what it does, who it's for, key technologies}\n\n{Important context paragraphs — constraints, architectural philosophy, non-obvious things}\n\n## {Section Name}\n\n- [{Page Title}]({relative-path-to-md}): {One-sentence description of what the reader will learn}\n\n## Optional\n\n- [{Page Title}]({relative-path-to-md}): {Description — these can be skipped for shorter context}\n```\n\n### Key Rules\n\n1. **H1** — Project name (exactly one, required)\n2. **Blockquote** — Dense, specific summary (required). Must be unique to THIS project.\n3. **Context paragraphs** — Non-obvious constraints, things LLMs would get wrong without being told\n4. **H2 sections** — Organized by topic, each with a list of `[Title](url): Description` entries\n5. **\"Optional\" H2** — Special meaning: links here can be skipped for shorter context\n6. **Relative links** — All paths relative to wiki directory\n7. **Dynamic** — ALL content derived from actual wiki pages, not templates\n8. **Section order** — Most important first: Onboarding → Architecture → Getting Started → Deep Dive → Optional\n\n### Description Quality\n\n| ❌ Bad | ✅ Good |\n|--------|---------|\n| \"Architecture overview\" | \"System architecture showing how Orleans grains communicate via message passing with at-least-once delivery\" |\n| \"Getting started guide\" | \"Prerequisites, local dev setup with Docker Compose, and first API call walkthrough\" |\n| \"The API reference\" | \"REST endpoints with auth requirements, rate limits, and request\u002Fresponse schemas\" |\n\n## llms-full.txt Format\n\nSame structure as `llms.txt` but with full content inlined:\n\n```markdown\n# {Project Name}\n\n> {Same summary}\n\n{Same context}\n\n## {Section Name}\n\n\u003Cdoc title=\"{Page Title}\" path=\"{relative-path}\">\n{Full markdown content — frontmatter stripped, citations and diagrams preserved}\n\u003C\u002Fdoc>\n```\n\n### Inlining Rules\n\n- **Strip YAML frontmatter** (`---` blocks) from each page\n- **Preserve Mermaid diagrams** — keep `` ```mermaid `` fences intact\n- **Preserve citations** — all `[file:line](URL)` links stay as-is\n- **Preserve tables** — all markdown tables stay intact\n- **Preserve `\u003C!-- Sources: -->` comments** — these provide diagram provenance\n\n## Prerequisites\n\nThis skill works best when wiki pages already exist (via `\u002Fdeep-wiki:generate` or `\u002Fdeep-wiki:page`). If no wiki exists yet:\n\n1. Suggest running `\u002Fdeep-wiki:generate` first\n2. OR generate a minimal `llms.txt` from README + source code scan (without wiki page links)\n\n## Output Files\n\nGenerate three files:\n\n| File | Purpose | Discoverability |\n|------|---------|-----------------|\n| `.\u002Fllms.txt` | Root discovery file | Standard path per llms.txt spec. GitHub MCP `get_file_contents` and `search_code` find this first. |\n| `wiki\u002Fllms.txt` | Wiki-relative links | For VitePress deployment and wiki-internal navigation. |\n| `wiki\u002Fllms-full.txt` | Full inlined content | Comprehensive reference for agents needing all docs in one file. |\n\nThe root `.\u002Fllms.txt` links into `wiki\u002F` (e.g., `[Guide](.\u002Fwiki\u002Fonboarding\u002Fcontributor-guide.md)`). The `wiki\u002Fllms.txt` uses wiki-relative paths (e.g., `[Guide](.\u002Fonboarding\u002Fcontributor-guide.md)`).\n\nIf a root `llms.txt` already exists and was NOT generated by deep-wiki, do NOT overwrite it.\n\n## Validation Checklist\n\nBefore finalizing:\n\n- [ ] All linked files in `llms.txt` actually exist\n- [ ] All `\u003Cdoc>` blocks in `llms-full.txt` have real content (not empty)\n- [ ] Blockquote is specific to this project (not generic boilerplate)\n- [ ] Sections ordered by importance\n- [ ] No duplicate page entries across sections\n- [ ] \"Optional\" section only contains truly optional content\n- [ ] `llms.txt` is concise (1-5 KB)\n- [ ] `llms-full.txt` contains all wiki pages\n",{"name":5,"license":15,"metadata":48,"description":7},{"author":12,"version":49},"1.0.0","main","3f5b461b2314e01c400564051e92469114c5b68f",".github\u002Fplugins\u002Fdeep-wiki\u002Fskills\u002Fwiki-llms-txt",368,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills","https:\u002F\u002Fmicrosoft.github.io\u002Fskills\u002F","https:\u002F\u002Fgithub.com\u002Fmicrosoft","https:\u002F\u002Fopensource.microsoft.com","Open source projects and samples from Microsoft","2026-11-14 06:48:25",{"source":8,"skillName":5,"commands":61,"prompt":71,"zipAvailable":72},[62,65,68],{"tool":63,"command":64},"npx","npx skills add microsoft\u002Fskills --skill wiki-llms-txt",{"tool":66,"command":67},"bunx","bunx skills add microsoft\u002Fskills --skill wiki-llms-txt",{"tool":69,"command":70},"pnpm","pnpm dlx skills add microsoft\u002Fskills --skill wiki-llms-txt","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fplugins\u002Fdeep-wiki\u002Fskills\u002Fwiki-llms-txt\u002FSKILL.md",true,[74],{"path":75,"resourceType":76,"resourceTypeDesc":77,"sizeBytes":78,"sourceHtmlUrl":79},"references\u002Fperformance-sensitive-components.md","REFERENCE","参考文档",2069,"https:\u002F\u002Fgithub.com\u002Fapache\u002Fairflow\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fairflow-publish-changes\u002Freferences\u002Fperformance-sensitive-components.md",[81,104,142,168,188,225],{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":88,"publishedAt":43},"01M69B4JCRQV5SPXAFCKXQRV0H","skill-creator","Guide for creating effective skills for AI coding agents working with Azure SDKs and Microsoft Foundry services. Use when creating new skills or updating existing skills.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fskill-creator\u002FSKILL.md",[87],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[89,90,91,9,92,93,94,95,96,97,98,39,99,100,101,33,102,29,103],"skill creator","creator","coding agents","foundry","microsoft foundry","ai coding agents","azure","services","coding","guide","ai coding","with","sdks","Existing","new",{"skillNo":105,"name":106,"nameZh":6,"description":107,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":108,"categories":109,"keywords":120,"publishedAt":43},"01M69B4FD57V1MYKRWAJJECTZ7","podcast-generation","Generate AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model via WebSocket. Use when building text-to-speech features, audio narrative generation, podcast creation from content, or integrating with Azure OpenAI Realtime API for real audio output. Covers full-stack implementation from React frontend to Python FastAPI backend with WebSocket streaming.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fpodcast-generation\u002FSKILL.md",[110,113,116,119],{"categoryNo":111,"categoryName":112,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",{"categoryNo":114,"categoryName":115,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":117,"categoryName":118,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[121,122,123,124,125,126,127,95,128,129,130,131,132,133,134,135,136,137,138,139,140,29,141],"podcast generation","podcast","generation","frontend","python","react","realtime","azure openai","generate","streaming","api","Audio","stack","text","model","fastapi","creation","python fastapi","narrative","features","fastapi backend",{"skillNo":143,"name":144,"nameZh":6,"description":145,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":146,"categories":147,"keywords":149,"publishedAt":43},"01M69B4CYPM5SESY5ZWEFDXEQZ","microsoft-docs","Understand Microsoft technologies by querying official documentation. Use whenever the user asks how something works, wants tutorials, needs configuration options, limits, quotas, or best practices for any Microsoft technology (Azure, .NET, M365, Windows, Power Platform, etc.)—even if they don't mention \"docs.\" If the question is about understanding a concept rather than writing code, this is the right skill.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fmicrosoft-docs\u002FSKILL.md",[148],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[150,9,151,152,153,154,155,156,157,158,42,95,159,160,161,39,162,63,163,164,165,166,167,33],"docs","microsoft docs","MCP","writing","cli","mcp server","windows","power platform","official","learn","best practices","question","power","back","technology","platform","learn mcp","concept",{"skillNo":169,"name":170,"nameZh":6,"description":171,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":172,"categories":173,"keywords":175,"publishedAt":43},"01M69B49C3YPD1ZJ3NC0HPCY58","mcp-builder","Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP), Node\u002FTypeScript (MCP SDK), or C#\u002F.NET (Microsoft MCP SDK).","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fmcp-builder\u002FSKILL.md",[174],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[152,176,177,178,125,27,179,180,9,181,182,135,183,184,98,39,185,186,187,100,33,29],"mcp builder","builder","typescript","sdk","model context protocol","fastmcp","Tools","node","context","integrate","mcp sdk","building mcp servers",{"skillNo":189,"name":190,"nameZh":6,"description":191,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":192,"categories":193,"keywords":206,"publishedAt":43},"01M69B467A7CDMFQ0T6Q0ZA12Q","kql","KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fkql\u002FSKILL.md",[194,197,198,203],{"categoryNo":195,"categoryName":196,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":199,"categoryName":200,"taxonomyType":201,"taxonomyTypeDesc":202},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",{"categoryNo":204,"categoryName":205,"taxonomyType":201,"taxonomyTypeDesc":202},"01JBSEEDCAT000000000000036","内容创作者",[190,153,207,208,209,95,210,211,212,213,214,215,216,217,218,35,219,220,221,33,222,223,224],"summarize","memory","analytics","vector","time series","tool","discipline","log","geo","exploration","pipe","time","regex","join","datetime","section","anomaly","parse",{"skillNo":226,"name":227,"nameZh":6,"description":228,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":229,"categories":230,"keywords":231,"publishedAt":43},"01M69B44HJQ7897EZ7NE7DWQX3","github-issue-creator","Convert raw notes, error logs, voice dictation, or screenshots into crisp GitHub-flavored markdown issue reports. Use when the user pastes bug info, error messages, or informal descriptions and wants a structured GitHub issue. Supports images\u002FGIFs for visual evidence.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills\u002Fblob\u002Fmain\u002F.github\u002Fskills\u002Fgithub-issue-creator\u002FSKILL.md",[],[232,233,234,235,90,236,237,238,239,240,241,242,39,243,244,245,246,247,248,33,29],"github","github issue creator","github issue","issue","issue creator","screenshots","notes","logs","error messages","messages","convert","evidence","reports","images","info","visual","error"]