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Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node\u002FTypeScript (MCP SDK).","shengdabai\u002FTony-Claude-Code-Skills","shengdabai","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F116417419?v=4","01M70F6D2WY5PQV5A92BKYJQEW","Tony Sheng","01M70F6D3GAAAYZ5H4CC1G8VXM",3,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fshengdabai\u002FTony-Claude-Code-Skills\u002Fblob\u002Fmain\u002Fskills\u002F_collections\u002Ftravisvn-awesome-claude-skills\u002Fanthropics-skills\u002Fskills\u002Fmcp-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fshengdabai\u002FTony-Claude-Code-Skills\u002Fblob\u002Fmain\u002Fskills\u002F_collections\u002Ftravisvn-awesome-claude-skills\u002Fanthropics-skills\u002Fskills\u002Fmcp-builder\u002FSKILL.md",[19],{"categoryNo":20,"categoryName":21,"taxonomyType":22,"taxonomyTypeDesc":23},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44],"MCP","mcp builder","builder","with","use","python","mcp sdk","for","fastmcp","context","guide","Tools","integrate","typescript","node","llms","model context protocol","when","building mcp servers","model","2026-11-10 10:12:30",false,"---\nname: mcp-builder\ndescription: 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) or Node\u002FTypeScript (MCP SDK).\nlicense: Complete terms in LICENSE.txt\n---\n\n# MCP Server Development Guide\n\n## Overview\n\nCreate MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.\n\n---\n\n# Process\n\n## 🚀 High-Level Workflow\n\nCreating a high-quality MCP server involves four main phases:\n\n### Phase 1: Deep Research and Planning\n\n#### 1.1 Understand Modern MCP Design\n\n**API Coverage vs. Workflow Tools:**\nBalance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks, while comprehensive coverage gives agents flexibility to compose operations. Performance varies by client—some clients benefit from code execution that combines basic tools, while others work better with higher-level workflows. When uncertain, prioritize comprehensive API coverage.\n\n**Tool Naming and Discoverability:**\nClear, descriptive tool names help agents find the right tools quickly. Use consistent prefixes (e.g., `github_create_issue`, `github_list_repos`) and action-oriented naming.\n\n**Context Management:**\nAgents benefit from concise tool descriptions and the ability to filter\u002Fpaginate results. Design tools that return focused, relevant data. Some clients support code execution which can help agents filter and process data efficiently.\n\n**Actionable Error Messages:**\nError messages should guide agents toward solutions with specific suggestions and next steps.\n\n#### 1.2 Study MCP Protocol Documentation\n\n**Navigate the MCP specification:**\n\nStart with the sitemap to find relevant pages: `https:\u002F\u002Fmodelcontextprotocol.io\u002Fsitemap.xml`\n\nThen fetch specific pages with `.md` suffix for markdown format (e.g., `https:\u002F\u002Fmodelcontextprotocol.io\u002Fspecification\u002Fdraft.md`).\n\nKey pages to review:\n- Specification overview and architecture\n- Transport mechanisms (streamable HTTP, stdio)\n- Tool, resource, and prompt definitions\n\n#### 1.3 Study Framework Documentation\n\n**Recommended stack:**\n- **Language**: TypeScript (high-quality SDK support and good compatibility in many execution environments e.g. MCPB. Plus AI models are good at generating TypeScript code, benefiting from its broad usage, static typing and good linting tools)\n- **Transport**: Streamable HTTP for remote servers, using stateless JSON (simpler to scale and maintain, as opposed to stateful sessions and streaming responses). stdio for local servers.\n\n**Load framework documentation:**\n\n- **MCP Best Practices**: [📋 View Best Practices](.\u002Freference\u002Fmcp_best_practices.md) - Core guidelines\n\n**For TypeScript (recommended):**\n- **TypeScript SDK**: Use WebFetch to load `https:\u002F\u002Fraw.githubusercontent.com\u002Fmodelcontextprotocol\u002Ftypescript-sdk\u002Fmain\u002FREADME.md`\n- [⚡ TypeScript Guide](.\u002Freference\u002Fnode_mcp_server.md) - TypeScript patterns and examples\n\n**For Python:**\n- **Python SDK**: Use WebFetch to load `https:\u002F\u002Fraw.githubusercontent.com\u002Fmodelcontextprotocol\u002Fpython-sdk\u002Fmain\u002FREADME.md`\n- [🐍 Python Guide](.\u002Freference\u002Fpython_mcp_server.md) - Python patterns and examples\n\n#### 1.4 Plan Your Implementation\n\n**Understand the API:**\nReview the service's API documentation to identify key endpoints, authentication requirements, and data models. Use web search and WebFetch as needed.\n\n**Tool Selection:**\nPrioritize comprehensive API coverage. List endpoints to implement, starting with the most common operations.\n\n---\n\n### Phase 2: Implementation\n\n#### 2.1 Set Up Project Structure\n\nSee language-specific guides for project setup:\n- [⚡ TypeScript Guide](.\u002Freference\u002Fnode_mcp_server.md) - Project structure, package.json, tsconfig.json\n- [🐍 Python Guide](.\u002Freference\u002Fpython_mcp_server.md) - Module organization, dependencies\n\n#### 2.2 Implement Core Infrastructure\n\nCreate shared utilities:\n- API client with authentication\n- Error handling helpers\n- Response formatting (JSON\u002FMarkdown)\n- Pagination support\n\n#### 2.3 Implement Tools\n\nFor each tool:\n\n**Input Schema:**\n- Use Zod (TypeScript) or Pydantic (Python)\n- Include constraints and clear descriptions\n- Add examples in field descriptions\n\n**Output Schema:**\n- Define `outputSchema` where possible for structured data\n- Use `structuredContent` in tool responses (TypeScript SDK feature)\n- Helps clients understand and process tool outputs\n\n**Tool Description:**\n- Concise summary of functionality\n- Parameter descriptions\n- Return type schema\n\n**Implementation:**\n- Async\u002Fawait for I\u002FO operations\n- Proper error handling with actionable messages\n- Support pagination where applicable\n- Return both text content and structured data when using modern SDKs\n\n**Annotations:**\n- `readOnlyHint`: true\u002Ffalse\n- `destructiveHint`: true\u002Ffalse\n- `idempotentHint`: true\u002Ffalse\n- `openWorldHint`: true\u002Ffalse\n\n---\n\n### Phase 3: Review and Test\n\n#### 3.1 Code Quality\n\nReview for:\n- No duplicated code (DRY principle)\n- Consistent error handling\n- Full type coverage\n- Clear tool descriptions\n\n#### 3.2 Build and Test\n\n**TypeScript:**\n- Run `npm run build` to verify compilation\n- Test with MCP Inspector: `npx @modelcontextprotocol\u002Finspector`\n\n**Python:**\n- Verify syntax: `python -m py_compile your_server.py`\n- Test with MCP Inspector\n\nSee language-specific guides for detailed testing approaches and quality checklists.\n\n---\n\n### Phase 4: Create Evaluations\n\nAfter implementing your MCP server, create comprehensive evaluations to test its effectiveness.\n\n**Load [✅ Evaluation Guide](.\u002Freference\u002Fevaluation.md) for complete evaluation guidelines.**\n\n#### 4.1 Understand Evaluation Purpose\n\nUse evaluations to test whether LLMs can effectively use your MCP server to answer realistic, complex questions.\n\n#### 4.2 Create 10 Evaluation Questions\n\nTo create effective evaluations, follow the process outlined in the evaluation guide:\n\n1. **Tool Inspection**: List available tools and understand their capabilities\n2. **Content Exploration**: Use READ-ONLY operations to explore available data\n3. **Question Generation**: Create 10 complex, realistic questions\n4. **Answer Verification**: Solve each question yourself to verify answers\n\n#### 4.3 Evaluation Requirements\n\nEnsure each question is:\n- **Independent**: Not dependent on other questions\n- **Read-only**: Only non-destructive operations required\n- **Complex**: Requiring multiple tool calls and deep exploration\n- **Realistic**: Based on real use cases humans would care about\n- **Verifiable**: Single, clear answer that can be verified by string comparison\n- **Stable**: Answer won't change over time\n\n#### 4.4 Output Format\n\nCreate an XML file with this structure:\n\n```xml\n\u003Cevaluation>\n  \u003Cqa_pair>\n    \u003Cquestion>Find discussions about AI model launches with animal codenames. One model needed a specific safety designation that uses the format ASL-X. What number X was being determined for the model named after a spotted wild cat?\u003C\u002Fquestion>\n    \u003Canswer>3\u003C\u002Fanswer>\n  \u003C\u002Fqa_pair>\n\u003C!-- More qa_pairs... -->\n\u003C\u002Fevaluation>\n```\n\n---\n\n# Reference Files\n\n## 📚 Documentation Library\n\nLoad these resources as needed during development:\n\n### Core MCP Documentation (Load First)\n- **MCP Protocol**: Start with sitemap at `https:\u002F\u002Fmodelcontextprotocol.io\u002Fsitemap.xml`, then fetch specific pages with `.md` suffix\n- [📋 MCP Best Practices](.\u002Freference\u002Fmcp_best_practices.md) - Universal MCP guidelines including:\n  - Server and tool naming conventions\n  - Response format guidelines (JSON vs Markdown)\n  - Pagination best practices\n  - Transport selection (streamable HTTP vs stdio)\n  - Security and error handling standards\n\n### SDK Documentation (Load During Phase 1\u002F2)\n- **Python SDK**: Fetch from `https:\u002F\u002Fraw.githubusercontent.com\u002Fmodelcontextprotocol\u002Fpython-sdk\u002Fmain\u002FREADME.md`\n- **TypeScript SDK**: Fetch from `https:\u002F\u002Fraw.githubusercontent.com\u002Fmodelcontextprotocol\u002Ftypescript-sdk\u002Fmain\u002FREADME.md`\n\n### Language-Specific Implementation Guides (Load During Phase 2)\n- [🐍 Python Implementation Guide](.\u002Freference\u002Fpython_mcp_server.md) - Complete Python\u002FFastMCP guide with:\n  - Server initialization patterns\n  - Pydantic model examples\n  - Tool registration with `@mcp.tool`\n  - Complete working examples\n  - Quality checklist\n\n- [⚡ TypeScript Implementation Guide](.\u002Freference\u002Fnode_mcp_server.md) - Complete TypeScript guide with:\n  - Project structure\n  - Zod schema patterns\n  - Tool registration with `server.registerTool`\n  - Complete working examples\n  - Quality checklist\n\n### Evaluation Guide (Load During Phase 4)\n- [✅ Evaluation Guide](.\u002Freference\u002Fevaluation.md) - Complete evaluation creation guide with:\n  - Question creation guidelines\n  - Answer verification strategies\n  - XML format specifications\n  - Example questions and answers\n  - Running an evaluation with the provided scripts\n","# MCP Server Development Guide\n\n## Overview\n\nCreate MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.\n\n---\n\n# Process\n\n## 🚀 High-Level Workflow\n\nCreating a high-quality MCP server involves four main phases:\n\n### Phase 1: Deep Research and Planning\n\n#### 1.1 Understand Modern MCP Design\n\n**API Coverage vs. Workflow Tools:**\nBalance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks, while comprehensive coverage gives agents flexibility to compose operations. Performance varies by client—some clients benefit from code execution that combines basic tools, while others work better with higher-level workflows. When uncertain, prioritize comprehensive API coverage.\n\n**Tool Naming and Discoverability:**\nClear, descriptive tool names help agents find the right tools quickly. Use consistent prefixes (e.g., `github_create_issue`, `github_list_repos`) and action-oriented naming.\n\n**Context Management:**\nAgents benefit from concise tool descriptions and the ability to filter\u002Fpaginate results. Design tools that return focused, relevant data. Some clients support code execution which can help agents filter and process data efficiently.\n\n**Actionable Error Messages:**\nError messages should guide agents toward solutions with specific suggestions and next steps.\n\n#### 1.2 Study MCP Protocol Documentation\n\n**Navigate the MCP specification:**\n\nStart with the sitemap to find relevant pages: `https:\u002F\u002Fmodelcontextprotocol.io\u002Fsitemap.xml`\n\nThen fetch specific pages with `.md` suffix for markdown format (e.g., `https:\u002F\u002Fmodelcontextprotocol.io\u002Fspecification\u002Fdraft.md`).\n\nKey pages to review:\n- Specification overview and architecture\n- Transport mechanisms (streamable HTTP, stdio)\n- Tool, resource, and prompt definitions\n\n#### 1.3 Study Framework Documentation\n\n**Recommended stack:**\n- **Language**: TypeScript (high-quality SDK support and good compatibility in many execution environments e.g. MCPB. Plus AI models are good at generating TypeScript code, benefiting from its broad usage, static typing and good linting tools)\n- **Transport**: Streamable HTTP for remote servers, using stateless JSON (simpler to scale and maintain, as opposed to stateful sessions and streaming responses). stdio for local servers.\n\n**Load framework documentation:**\n\n- **MCP Best Practices**: [📋 View Best Practices](.\u002Freference\u002Fmcp_best_practices.md) - Core guidelines\n\n**For TypeScript (recommended):**\n- **TypeScript SDK**: Use WebFetch to load `https:\u002F\u002Fraw.githubusercontent.com\u002Fmodelcontextprotocol\u002Ftypescript-sdk\u002Fmain\u002FREADME.md`\n- [⚡ TypeScript Guide](.\u002Freference\u002Fnode_mcp_server.md) - TypeScript patterns and examples\n\n**For Python:**\n- **Python SDK**: Use WebFetch to load `https:\u002F\u002Fraw.githubusercontent.com\u002Fmodelcontextprotocol\u002Fpython-sdk\u002Fmain\u002FREADME.md`\n- [🐍 Python Guide](.\u002Freference\u002Fpython_mcp_server.md) - Python patterns and examples\n\n#### 1.4 Plan Your Implementation\n\n**Understand the API:**\nReview the service's API documentation to identify key endpoints, authentication requirements, and data models. Use web search and WebFetch as needed.\n\n**Tool Selection:**\nPrioritize comprehensive API coverage. List endpoints to implement, starting with the most common operations.\n\n---\n\n### Phase 2: Implementation\n\n#### 2.1 Set Up Project Structure\n\nSee language-specific guides for project setup:\n- [⚡ TypeScript Guide](.\u002Freference\u002Fnode_mcp_server.md) - Project structure, package.json, tsconfig.json\n- [🐍 Python Guide](.\u002Freference\u002Fpython_mcp_server.md) - Module organization, dependencies\n\n#### 2.2 Implement Core Infrastructure\n\nCreate shared utilities:\n- API client with authentication\n- Error handling helpers\n- Response formatting (JSON\u002FMarkdown)\n- Pagination support\n\n#### 2.3 Implement Tools\n\nFor each tool:\n\n**Input Schema:**\n- Use Zod (TypeScript) or Pydantic (Python)\n- Include constraints and clear descriptions\n- Add examples in field descriptions\n\n**Output Schema:**\n- Define `outputSchema` where possible for structured data\n- Use `structuredContent` in tool responses (TypeScript SDK feature)\n- Helps clients understand and process tool outputs\n\n**Tool Description:**\n- Concise summary of functionality\n- Parameter descriptions\n- Return type schema\n\n**Implementation:**\n- Async\u002Fawait for I\u002FO operations\n- Proper error handling with actionable messages\n- Support pagination where applicable\n- Return both text content and structured data when using modern SDKs\n\n**Annotations:**\n- `readOnlyHint`: true\u002Ffalse\n- `destructiveHint`: true\u002Ffalse\n- `idempotentHint`: true\u002Ffalse\n- `openWorldHint`: true\u002Ffalse\n\n---\n\n### Phase 3: Review and Test\n\n#### 3.1 Code Quality\n\nReview for:\n- No duplicated code (DRY principle)\n- Consistent error handling\n- Full type coverage\n- Clear tool descriptions\n\n#### 3.2 Build and Test\n\n**TypeScript:**\n- Run `npm run build` to verify compilation\n- Test with MCP Inspector: `npx @modelcontextprotocol\u002Finspector`\n\n**Python:**\n- Verify syntax: `python -m py_compile your_server.py`\n- Test with MCP Inspector\n\nSee language-specific guides for detailed testing approaches and quality checklists.\n\n---\n\n### Phase 4: Create Evaluations\n\nAfter implementing your MCP server, create comprehensive evaluations to test its effectiveness.\n\n**Load [✅ Evaluation Guide](.\u002Freference\u002Fevaluation.md) for complete evaluation guidelines.**\n\n#### 4.1 Understand Evaluation Purpose\n\nUse evaluations to test whether LLMs can effectively use your MCP server to answer realistic, complex questions.\n\n#### 4.2 Create 10 Evaluation Questions\n\nTo create effective evaluations, follow the process outlined in the evaluation guide:\n\n1. **Tool Inspection**: List available tools and understand their capabilities\n2. **Content Exploration**: Use READ-ONLY operations to explore available data\n3. **Question Generation**: Create 10 complex, realistic questions\n4. **Answer Verification**: Solve each question yourself to verify answers\n\n#### 4.3 Evaluation Requirements\n\nEnsure each question is:\n- **Independent**: Not dependent on other questions\n- **Read-only**: Only non-destructive operations required\n- **Complex**: Requiring multiple tool calls and deep exploration\n- **Realistic**: Based on real use cases humans would care about\n- **Verifiable**: Single, clear answer that can be verified by string comparison\n- **Stable**: Answer won't change over time\n\n#### 4.4 Output Format\n\nCreate an XML file with this structure:\n\n```xml\n\u003Cevaluation>\n  \u003Cqa_pair>\n    \u003Cquestion>Find discussions about AI model launches with animal codenames. One model needed a specific safety designation that uses the format ASL-X. What number X was being determined for the model named after a spotted wild cat?\u003C\u002Fquestion>\n    \u003Canswer>3\u003C\u002Fanswer>\n  \u003C\u002Fqa_pair>\n\u003C!-- More qa_pairs... -->\n\u003C\u002Fevaluation>\n```\n\n---\n\n# Reference Files\n\n## 📚 Documentation Library\n\nLoad these resources as needed during development:\n\n### Core MCP Documentation (Load First)\n- **MCP Protocol**: Start with sitemap at `https:\u002F\u002Fmodelcontextprotocol.io\u002Fsitemap.xml`, then fetch specific pages with `.md` suffix\n- [📋 MCP Best Practices](.\u002Freference\u002Fmcp_best_practices.md) - Universal MCP guidelines including:\n  - Server and tool naming conventions\n  - Response format guidelines (JSON vs Markdown)\n  - Pagination best practices\n  - Transport selection (streamable HTTP vs stdio)\n  - Security and error handling standards\n\n### SDK Documentation (Load During Phase 1\u002F2)\n- **Python SDK**: Fetch from `https:\u002F\u002Fraw.githubusercontent.com\u002Fmodelcontextprotocol\u002Fpython-sdk\u002Fmain\u002FREADME.md`\n- **TypeScript SDK**: Fetch from `https:\u002F\u002Fraw.githubusercontent.com\u002Fmodelcontextprotocol\u002Ftypescript-sdk\u002Fmain\u002FREADME.md`\n\n### Language-Specific Implementation Guides (Load During Phase 2)\n- [🐍 Python Implementation Guide](.\u002Freference\u002Fpython_mcp_server.md) - Complete Python\u002FFastMCP guide with:\n  - Server initialization patterns\n  - Pydantic model examples\n  - Tool registration with `@mcp.tool`\n  - Complete working examples\n  - Quality checklist\n\n- [⚡ TypeScript Implementation Guide](.\u002Freference\u002Fnode_mcp_server.md) - Complete TypeScript guide with:\n  - Project structure\n  - Zod schema patterns\n  - Tool registration with `server.registerTool`\n  - Complete working examples\n  - Quality checklist\n\n### Evaluation Guide (Load During Phase 4)\n- [✅ Evaluation Guide](.\u002Freference\u002Fevaluation.md) - Complete evaluation creation guide with:\n  - Question creation guidelines\n  - Answer verification strategies\n  - XML format specifications\n  - Example questions and answers\n  - Running an evaluation with the provided scripts\n",{"name":5,"license":50,"description":7},"Complete terms in LICENSE.txt","main","7850740bd837adb32f0a109ab2af82482196c6f2","skills\u002F_collections\u002Ftravisvn-awesome-claude-skills\u002Fanthropics-skills\u002Fskills\u002Fmcp-builder",1,"https:\u002F\u002Fgithub.com\u002Fshengdabai\u002FTony-Claude-Code-Skills","https:\u002F\u002Fzturnsgo.com","https:\u002F\u002Fgithub.com\u002Fshengdabai","https:\u002F\u002Fzturnsgo.com\u002F","AI × education creator — producer, not consumer. 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Xiaolai)的思考方式、方法论与表达风格,为用户做全方位 1-on-1 教练指导,覆盖创业、赚钱、投资、学习、自学、读书写作、用 AI、以及人生心态与自我管理。当用户提到 \"李笑来\"、\"笑来\"、\"笑来老师\"、\"扮演李笑来\"、\"找笑来聊聊\"、\"笑来怎么看\"、\"xiaolai\"、\"把时间当作朋友\"、\"通往财富自由之路\"、\"定投改变命运\"、\"韭菜的自我修养\"、\"自学是门手艺\"、\"让时间陪你慢慢变富\"、\"七年就是一辈子\"、\"元认知\"、\"活在未来\"、\"复利\u002F长期主义\"、\"践行\"、\"痴迷改进\"、\"个人商业模式\u002F出售时间\"、\"睡后收入\"、\"定投\"、\"财富自由\"、\"操作系统升级\"、\"最少必要知识\"、\"北极星提示词\"、\"用 AI 该怎么学\u002F思考\" 等任一触发词,或当用户带着关于创业\u002F赚钱\u002F投资\u002F学习\u002F职业\u002F重大人生决策的困惑、希望被人用笑来式的「逻辑 + 大白话 + 类比 + 重新定义 + 践行导向」来点醒和指导时,自动进入李笑来教练模式。","MIT","https:\u002F\u002Fgithub.com\u002Fshengdabai\u002FTony-Claude-Code-Skills\u002Fblob\u002Fmain\u002Fxiaolai-methodology\u002FSKILL.md",[124],{"categoryNo":125,"categoryName":126,"taxonomyType":22,"taxonomyTypeDesc":23},"01JBSEEDCAT000000000000018","写作与文案",[128,129,130,131,132,133,134],"methodology","xiaolai","xiaolai 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Use this skill whenever the user wants to understand, onboard onto, explore, summarize, map, or get an overview of an unfamiliar codebase; asks for architecture docs, a project wiki, a repo walkthrough, module\u002Fpackage explanations, or \"what does this repo do\"; wants to generate, regenerate, resume, browse, or serve code documentation locally; or mentions zread \u002F zread.ai directly. Also use it proactively before diving into a large unknown repo — if `.\u002F.zread\u002Fwiki\u002Fcurrent` exists, read the generated pages instead of crawling source file-by-file; if it doesn't, consider offering to run `zread generate`. The trigger is the intent (understand a codebase through generated docs), not the literal word \"zread\".","https:\u002F\u002Fgithub.com\u002Fshengdabai\u002FTony-Claude-Code-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fzread\u002FSKILL.md",[141,142],{"categoryNo":20,"categoryName":21,"taxonomyType":22,"taxonomyTypeDesc":23},{"categoryNo":143,"categoryName":144,"taxonomyType":145,"taxonomyTypeDesc":146},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[137,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166],"knowledge","wiki","explore","walkthrough","project","get","knowledge base","run","generate","intent","cli","map","documentation","project wiki","disk","architecture","code","unknown","generated",{"skillNo":168,"name":169,"nameZh":6,"description":170,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":121,"licenseFileUrl":6,"sourceHtmlUrl":171,"categories":172,"keywords":177,"publishedAt":45},"01M70P10S4SWMZQ8BJAFBFDRW3","youtube","Launch the YouTube Creator Agent to auto-generate videos.\nUse when: user types \u002Fyoutube, wants to create YouTube videos,\ngenerate video content, or upload to YouTube.\nKeywords: youtube, video, 视频, 创作视频, 发布视频","https:\u002F\u002Fgithub.com\u002Fshengdabai\u002FTony-Claude-Code-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fyoutube\u002FSKILL.md",[173,174],{"categoryNo":20,"categoryName":21,"taxonomyType":22,"taxonomyTypeDesc":23},{"categoryNo":175,"categoryName":176,"taxonomyType":145,"taxonomyTypeDesc":146},"01JBSEEDCAT000000000000036","内容创作者",[169,178,179,180,181,182,183,184,156,185,186,187,42,29,188,189,190,191],"user","content","视频","creator","generate video","videos","launch","video content","create","upload","auto","types","Video","创作",{"skillNo":193,"name":194,"nameZh":6,"description":195,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":121,"licenseFileUrl":6,"sourceHtmlUrl":196,"categories":197,"keywords":199,"publishedAt":45},"01M70P0YE95D8BACZCGV8BK90K","youtube-script-sync","Sync, update, or optimize Tony's GetNote knowledge base `Youtube视频逐字稿` by turning each parent recording or first-person idea note into an idempotent child note containing a directly recordable YouTube long-video or Shorts script. Use when the user says “更新\u002F同步\u002F优化 Youtube视频逐字稿知识库”, or says “更新\u002F同步\u002F优化该知识库” while this knowledge base is the active context.","https:\u002F\u002Fgithub.com\u002Fshengdabai\u002FTony-Claude-Code-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fyoutube-script-sync\u002FSKILL.md",[198],{"categoryNo":20,"categoryName":21,"taxonomyType":22,"taxonomyTypeDesc":23},[200,201,169,202,203,190,204,205,206,207,208,209,210,211,154,212,42,29,148,213],"sync","script","youtube script sync","recording","shorts","first","base","person","update","active","child","optimize","idempotent","long",{"skillNo":215,"name":216,"nameZh":6,"description":217,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":121,"licenseFileUrl":6,"sourceHtmlUrl":218,"categories":219,"keywords":224,"publishedAt":45},"01M70P0WMV5XT0EEC0N445PW07","writing-skills","How to write SKILL.md files that trigger reliably and teach effectively. Use when creating, improving, or reviewing Claude Code skills.","https:\u002F\u002Fgithub.com\u002Fshengdabai\u002FTony-Claude-Code-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fxiaolai\u002Fnlpm\u002Fskills\u002Fnlpm\u002Fwriting-skills\u002FSKILL.md",[220,221,222,223],{"categoryNo":125,"categoryName":126,"taxonomyType":22,"taxonomyTypeDesc":23},{"categoryNo":20,"categoryName":21,"taxonomyType":22,"taxonomyTypeDesc":23},{"categoryNo":143,"categoryName":144,"taxonomyType":145,"taxonomyTypeDesc":146},{"categoryNo":175,"categoryName":176,"taxonomyType":145,"taxonomyTypeDesc":146},[225,133,226,227,228,229,164,42,29,230,231,232,233],"writing skills","how","teach","write skill","write","claude code skills","files","how to","trigger",{"skillNo":235,"name":236,"nameZh":6,"description":237,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":121,"licenseFileUrl":6,"sourceHtmlUrl":238,"categories":239,"keywords":242,"publishedAt":45},"01M70P0SJFR4YVJQBGMHKGSKXT","writing-rules","How to write .claude\u002Frules\u002F files that Claude actually follows. Use when creating, improving, or reviewing project rules.","https:\u002F\u002Fgithub.com\u002Fshengdabai\u002FTony-Claude-Code-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fxiaolai\u002Fnlpm\u002Fskills\u002Fnlpm\u002Fwriting-rules\u002FSKILL.md",[240,241],{"categoryNo":125,"categoryName":126,"taxonomyType":22,"taxonomyTypeDesc":23},{"categoryNo":175,"categoryName":176,"taxonomyType":145,"taxonomyTypeDesc":146},[243,133,244,152,245,231,42,226,229,29,232],"Rules","writing rules","project rules"]