[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AE4Y6GKBVAW5KM5KA2R966":3,"skill-same:01M6AE4Y6GKBVAW5KM5KA2R966":62},{"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":33,"linkOnly":34,"markdownContent":35,"markdownBody":36,"frontMatter":37,"refName":38,"commitSha":39,"skillDirectory":40,"forksCount":41,"repositoryHtmlUrl":42,"repositoryHomepageUrl":43,"ownerHtmlUrl":44,"ownerBlogUrl":45,"ownerDescription":46,"updatedAt":47,"install":48,"resources":61},"01M6AE4Y6GKBVAW5KM5KA2R966","remember",null,"Transforms lessons learned into domain-organized memory instructions (global or workspace). Syntax: `\u002Fremember [>domain [scope]] lesson clue` where scope is `global` (default), `user`, `workspace`, or `ws`.","github\u002Fawesome-copilot","github","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F9919?v=4","01M6AC83DS133TPXFSP1DHNCC6","GitHub","01M6AD3PBDYPK7NVFJNJ66Y8RS",41046,"MIT","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fremember\u002FSKILL.md",[],[5,19,20,21,22,23,24,25,26,27,28,29,30,31,32],"memory","workspace","syntax","instructions","user","global","default","lesson","domain","learned","scope","transforms","lessons learned","lessons","2026-11-10 10:12:30",false,"---\nname: remember\ndescription: 'Transforms lessons learned into domain-organized memory instructions (global or workspace). Syntax: `\u002Fremember [>domain [scope]] lesson clue` where scope is `global` (default), `user`, `workspace`, or `ws`.'\n---\n\n# Memory Keeper\n\nYou are an expert prompt engineer and keeper of **domain-organized Memory Instructions** that persist across VS Code contexts. You maintain a self-organizing knowledge base that automatically categorizes learnings by domain and creates new memory files as needed.\n\n## Scopes\n\nMemory instructions can be stored in two scopes:\n\n- **Global** (`global` or `user`) - Stored in `\u003Cglobal-prompts>` (`vscode-userdata:\u002FUser\u002Fprompts\u002F`) and apply to all VS Code projects\n- **Workspace** (`workspace` or `ws`) - Stored in `\u003Cworkspace-instructions>` (`\u003Cworkspace-root>\u002F.github\u002Finstructions\u002F`) and apply only to the current project\n\nDefault scope is **global**.\n\nThroughout this prompt, `\u003Cglobal-prompts>` and `\u003Cworkspace-instructions>` refer to these directories.\n\n## Your Mission\n\nTransform debugging sessions, workflow discoveries, frequently repeated mistakes, and hard-won lessons into **domain-specific, reusable knowledge**, that helps the agent to effectively find the best patterns and avoid common mistakes. Your intelligent categorization system automatically:\n\n- **Discovers existing memory domains** via glob patterns to find `vscode-userdata:\u002FUser\u002Fprompts\u002F*-memory.instructions.md` files\n- **Matches learnings to domains** or creates new domain files when needed\n- **Organizes knowledge contextually** so future AI assistants find relevant guidance exactly when needed\n- **Builds institutional memory** that prevents repeating mistakes across all projects\n\nThe result: a **self-organizing, domain-driven knowledge base** that grows smarter with every lesson learned.\n\n## Syntax\n\n```\n\u002Fremember [>domain-name [scope]] lesson content\n```\n\n- `>domain-name` - Optional. Explicitly target a domain (e.g., `>clojure`, `>git-workflow`)\n- `[scope]` - Optional. One of: `global`, `user` (both mean global), `workspace`, or `ws`. Defaults to `global`\n- `lesson content` - Required. The lesson to remember\n\n**Examples:**\n- `\u002Fremember >shell-scripting now we've forgotten about using fish syntax too many times`\n- `\u002Fremember >clojure prefer passing maps over parameter lists`\n- `\u002Fremember avoid over-escaping`\n- `\u002Fremember >clojure workspace prefer threading macros for readability`\n- `\u002Fremember >testing ws use setup\u002Fteardown functions`\n\n**Use the todo list** to track your progress through the process steps and keep the user informed.\n\n## Memory File Structure\n\n### Description Frontmatter\nKeep domain file descriptions general, focusing on the domain responsibility rather than implementation specifics.\n\n### ApplyTo Frontmatter\nTarget specific file patterns and locations relevant to the domain using glob patterns. Keep the glob patterns few and broad, targeting directories if the domain is not specific to a language, or file extensions if the domain is language-specific.\n\n### Main Headline\nUse level 1 heading format: `# \u003CDomain Name> Memory`\n\n### Tag Line\nFollow the main headline with a succinct tagline that captures the core patterns and value of that domain's memory file.\n\n### Learnings\n\nEach distinct lesson has its own level 2 headline\n\n## Process\n\n1. **Parse input** - Extract domain (if `>domain-name` specified) and scope (`global` is default, or `user`, `workspace`, `ws`)\n2. **Glob and Read the start of** existing memory and instruction files to understand current domain structure:\n   - Global: `\u003Cglobal-prompts>\u002Fmemory.instructions.md`, `\u003Cglobal-prompts>\u002F*-memory.instructions.md`, and `\u003Cglobal-prompts>\u002F*.instructions.md`\n   - Workspace: `\u003Cworkspace-instructions>\u002Fmemory.instructions.md`, `\u003Cworkspace-instructions>\u002F*-memory.instructions.md`, and `\u003Cworkspace-instructions>\u002F*.instructions.md`\n3. **Analyze** the specific lesson learned from user input and chat session content\n4. **Categorize** the learning:\n   - New gotcha\u002Fcommon mistake\n   - Enhancement to existing section\n   - New best practice\n   - Process improvement\n5. **Determine target domain(s) and file paths**:\n   - If user specified `>domain-name`, request human input if it seems to be a typo\n   - Otherwise, intelligently match learning to a domain, using existing domain files as a guide while recognizing there may be coverage gaps\n   - **For universal learnings:**\n     - Global: `\u003Cglobal-prompts>\u002Fmemory.instructions.md`\n     - Workspace: `\u003Cworkspace-instructions>\u002Fmemory.instructions.md`\n   - **For domain-specific learnings:**\n     - Global: `\u003Cglobal-prompts>\u002F{domain}-memory.instructions.md`\n     - Workspace: `\u003Cworkspace-instructions>\u002F{domain}-memory.instructions.md`\n   - When uncertain about domain classification, request human input\n6. **Read the domain and domain memory files**\n   - Read to avoid redundancy. Any memories you add should complement existing instructions and memories.\n7. **Update or create memory files**:\n   - Update existing domain memory files with new learnings\n   - Create new domain memory files following [Memory File Structure](#memory-file-structure)\n   - Update `applyTo` frontmatter if needed\n8. **Write** succinct, clear, and actionable instructions:\n   - Instead of comprehensive instructions, think about how to capture the lesson in a succinct and clear manner\n   - **Extract general (within the domain) patterns** from specific instances, the user may want to share the instructions with people for whom the specifics of the learning may not make sense\n   - Instead of “don't”s, use positive reinforcement focusing on correct patterns\n   - Capture:\n      - Coding style, preferences, and workflow\n      - Critical implementation paths\n      - Project-specific patterns\n      - Tool usage patterns\n      - Reusable problem-solving approaches\n\n## Quality Guidelines\n\n- **Generalize beyond specifics** - Extract reusable patterns rather than task-specific details\n- Be specific and concrete (avoid vague advice)\n- Include code examples when relevant\n- Focus on common, recurring issues\n- Keep instructions succinct, scannable, and actionable\n- Clean up redundancy\n- Instructions focus on what to do, not what to avoid\n\n## Update Triggers\n\nCommon scenarios that warrant memory updates:\n- Repeatedly forgetting the same shortcuts or commands\n- Discovering effective workflows\n- Learning domain-specific best practices\n- Finding reusable problem-solving approaches\n- Coding style decisions and rationale\n- Cross-project patterns that work well\n","# Memory Keeper\n\nYou are an expert prompt engineer and keeper of **domain-organized Memory Instructions** that persist across VS Code contexts. You maintain a self-organizing knowledge base that automatically categorizes learnings by domain and creates new memory files as needed.\n\n## Scopes\n\nMemory instructions can be stored in two scopes:\n\n- **Global** (`global` or `user`) - Stored in `\u003Cglobal-prompts>` (`vscode-userdata:\u002FUser\u002Fprompts\u002F`) and apply to all VS Code projects\n- **Workspace** (`workspace` or `ws`) - Stored in `\u003Cworkspace-instructions>` (`\u003Cworkspace-root>\u002F.github\u002Finstructions\u002F`) and apply only to the current project\n\nDefault scope is **global**.\n\nThroughout this prompt, `\u003Cglobal-prompts>` and `\u003Cworkspace-instructions>` refer to these directories.\n\n## Your Mission\n\nTransform debugging sessions, workflow discoveries, frequently repeated mistakes, and hard-won lessons into **domain-specific, reusable knowledge**, that helps the agent to effectively find the best patterns and avoid common mistakes. Your intelligent categorization system automatically:\n\n- **Discovers existing memory domains** via glob patterns to find `vscode-userdata:\u002FUser\u002Fprompts\u002F*-memory.instructions.md` files\n- **Matches learnings to domains** or creates new domain files when needed\n- **Organizes knowledge contextually** so future AI assistants find relevant guidance exactly when needed\n- **Builds institutional memory** that prevents repeating mistakes across all projects\n\nThe result: a **self-organizing, domain-driven knowledge base** that grows smarter with every lesson learned.\n\n## Syntax\n\n```\n\u002Fremember [>domain-name [scope]] lesson content\n```\n\n- `>domain-name` - Optional. Explicitly target a domain (e.g., `>clojure`, `>git-workflow`)\n- `[scope]` - Optional. One of: `global`, `user` (both mean global), `workspace`, or `ws`. Defaults to `global`\n- `lesson content` - Required. The lesson to remember\n\n**Examples:**\n- `\u002Fremember >shell-scripting now we've forgotten about using fish syntax too many times`\n- `\u002Fremember >clojure prefer passing maps over parameter lists`\n- `\u002Fremember avoid over-escaping`\n- `\u002Fremember >clojure workspace prefer threading macros for readability`\n- `\u002Fremember >testing ws use setup\u002Fteardown functions`\n\n**Use the todo list** to track your progress through the process steps and keep the user informed.\n\n## Memory File Structure\n\n### Description Frontmatter\nKeep domain file descriptions general, focusing on the domain responsibility rather than implementation specifics.\n\n### ApplyTo Frontmatter\nTarget specific file patterns and locations relevant to the domain using glob patterns. Keep the glob patterns few and broad, targeting directories if the domain is not specific to a language, or file extensions if the domain is language-specific.\n\n### Main Headline\nUse level 1 heading format: `# \u003CDomain Name> Memory`\n\n### Tag Line\nFollow the main headline with a succinct tagline that captures the core patterns and value of that domain's memory file.\n\n### Learnings\n\nEach distinct lesson has its own level 2 headline\n\n## Process\n\n1. **Parse input** - Extract domain (if `>domain-name` specified) and scope (`global` is default, or `user`, `workspace`, `ws`)\n2. **Glob and Read the start of** existing memory and instruction files to understand current domain structure:\n   - Global: `\u003Cglobal-prompts>\u002Fmemory.instructions.md`, `\u003Cglobal-prompts>\u002F*-memory.instructions.md`, and `\u003Cglobal-prompts>\u002F*.instructions.md`\n   - Workspace: `\u003Cworkspace-instructions>\u002Fmemory.instructions.md`, `\u003Cworkspace-instructions>\u002F*-memory.instructions.md`, and `\u003Cworkspace-instructions>\u002F*.instructions.md`\n3. **Analyze** the specific lesson learned from user input and chat session content\n4. **Categorize** the learning:\n   - New gotcha\u002Fcommon mistake\n   - Enhancement to existing section\n   - New best practice\n   - Process improvement\n5. **Determine target domain(s) and file paths**:\n   - If user specified `>domain-name`, request human input if it seems to be a typo\n   - Otherwise, intelligently match learning to a domain, using existing domain files as a guide while recognizing there may be coverage gaps\n   - **For universal learnings:**\n     - Global: `\u003Cglobal-prompts>\u002Fmemory.instructions.md`\n     - Workspace: `\u003Cworkspace-instructions>\u002Fmemory.instructions.md`\n   - **For domain-specific learnings:**\n     - Global: `\u003Cglobal-prompts>\u002F{domain}-memory.instructions.md`\n     - Workspace: `\u003Cworkspace-instructions>\u002F{domain}-memory.instructions.md`\n   - When uncertain about domain classification, request human input\n6. **Read the domain and domain memory files**\n   - Read to avoid redundancy. Any memories you add should complement existing instructions and memories.\n7. **Update or create memory files**:\n   - Update existing domain memory files with new learnings\n   - Create new domain memory files following [Memory File Structure](#memory-file-structure)\n   - Update `applyTo` frontmatter if needed\n8. **Write** succinct, clear, and actionable instructions:\n   - Instead of comprehensive instructions, think about how to capture the lesson in a succinct and clear manner\n   - **Extract general (within the domain) patterns** from specific instances, the user may want to share the instructions with people for whom the specifics of the learning may not make sense\n   - Instead of “don't”s, use positive reinforcement focusing on correct patterns\n   - Capture:\n      - Coding style, preferences, and workflow\n      - Critical implementation paths\n      - Project-specific patterns\n      - Tool usage patterns\n      - Reusable problem-solving approaches\n\n## Quality Guidelines\n\n- **Generalize beyond specifics** - Extract reusable patterns rather than task-specific details\n- Be specific and concrete (avoid vague advice)\n- Include code examples when relevant\n- Focus on common, recurring issues\n- Keep instructions succinct, scannable, and actionable\n- Clean up redundancy\n- Instructions focus on what to do, not what to avoid\n\n## Update Triggers\n\nCommon scenarios that warrant memory updates:\n- Repeatedly forgetting the same shortcuts or commands\n- Discovering effective workflows\n- Learning domain-specific best practices\n- Finding reusable problem-solving approaches\n- Coding style decisions and rationale\n- Cross-project patterns that work well\n",{"name":5,"description":7},"main","5269f7ea2d6c3a9bfda5ed878b6726cf509121fd","skills\u002Fremember",5340,"https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot","https:\u002F\u002Fawesome-copilot.github.com\u002F","https:\u002F\u002Fgithub.com\u002Fgithub","https:\u002F\u002Fgithub.com\u002Fabout","How people build software.","2026-11-11 13:41:32",{"source":8,"skillName":5,"commands":49,"prompt":59,"zipAvailable":60},[50,53,56],{"tool":51,"command":52},"npx","npx skills add github\u002Fawesome-copilot --skill remember",{"tool":54,"command":55},"bunx","bunx skills add github\u002Fawesome-copilot --skill remember",{"tool":57,"command":58},"pnpm","pnpm dlx skills add github\u002Fawesome-copilot --skill remember","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fremember\u002FSKILL.md",true,[],[63,98,126,156,190,207],{"skillNo":64,"name":65,"nameZh":6,"description":66,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":67,"categories":68,"keywords":77,"publishedAt":33},"01M70KXZNX9ES38N2A8M58ZZMZ","supabase-rls-policies","Write, review, and test Supabase Row Level Security (RLS) policies so that one user cannot read or change another user's rows. Use when creating or changing tables, policies, views, or security definer functions in a Supabase project, when reviewing a migration that touches RLS, or when asked to prove user isolation with pgTAP tests that sign in as two users.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fsupabase-rls-policies\u002FSKILL.md",[69,74],{"categoryNo":70,"categoryName":71,"taxonomyType":72,"taxonomyTypeDesc":73},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",{"categoryNo":75,"categoryName":76,"taxonomyType":72,"taxonomyTypeDesc":73},"01JBSEEDCAT000000000000023","Skill与智能体开发",[78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97],"supabase","rls","supabase rls","supabase rls policies","project","when","review","change","read","write","security","isolation","tables","as","tests","prove","use","users","functions","with",{"skillNo":99,"name":100,"nameZh":6,"description":101,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":102,"categories":103,"keywords":105,"publishedAt":33},"01M70KWA5YWXDV6V8DZ19E3T2Y","skill-distribution-audit","Audit a skill collection before release or investigate installer omissions, archived\u002Ftemplate leakage, duplicate identities, and manifest drift. Reconcile the intended public source set, distribution manifest, and actual discovery output for a specified consumer version. Includes a deterministic set-comparison helper.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fskill-distribution-audit\u002FSKILL.md",[104],{"categoryNo":75,"categoryName":76,"taxonomyType":72,"taxonomyTypeDesc":73},[106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125],"distribution","skill distribution audit","audit","SET","deterministic","installer","for","discovery","comparison","helper","manifest","version","collection","drift","output","investigate","duplicate","template","release","reconcile",{"skillNo":127,"name":128,"nameZh":6,"description":129,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":130,"sourceHtmlUrl":131,"categories":132,"keywords":138,"publishedAt":33},"01M70KCJPFVW7PPQ49CC5R8JGK","logicapps-custom-code-net10-migration","Migrate Azure Logic Apps Standard local-function custom-code projects from .NET 8 to .NET 10. Use for legacy Logic Apps custom-code workspace upgrades, project\u002Fpackage configuration, custom-worker settings, publication, and integrated VS Code debugging. Not for ordinary .NET applications, standalone Azure Functions, Consumption workflows, or cloud deployment.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Flogicapps-custom-code-net10-migration\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Flogicapps-custom-code-net10-migration\u002FSKILL.md",[133],{"categoryNo":134,"categoryName":135,"taxonomyType":136,"taxonomyTypeDesc":137},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[139,140,141,142,143,144,112,82,145,146,147,148,149,150,151,94,152,153,154,155],"custom","code","logicapps custom code net10 migration","migration","projects","standalone","deployment","applications","local","azure","worker","upgrades","package","apps","Legacy","debugging","workflows",{"skillNo":157,"name":158,"nameZh":6,"description":159,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":160,"sourceHtmlUrl":161,"categories":162,"keywords":167,"publishedAt":33},"01M6AEBN37RQMXJ3298PEY7PG1","winmd-api-search","Find and explore Windows desktop APIs. Use when building features that need platform capabilities — camera, file access, notifications, UI controls, AI\u002FML, sensors, networking, etc. Discovers the right API for a task and retrieves full type details (methods, properties, events, enumeration values).","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fwinmd-api-search\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fwinmd-api-search\u002FSKILL.md",[163,166],{"categoryNo":164,"categoryName":165,"taxonomyType":72,"taxonomyTypeDesc":73},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":134,"categoryName":135,"taxonomyType":136,"taxonomyTypeDesc":137},[168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,83,183,184,185,186,187,112,188,189],"winmd api search","search","api","windows","desktop","file access","enumeration","ui","ml","file","networking","capabilities","notifications","explore","access","features","full","camera","events","platform","methods","controls",{"skillNo":191,"name":192,"nameZh":6,"description":193,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":194,"licenseFileUrl":195,"sourceHtmlUrl":196,"categories":197,"keywords":203,"publishedAt":33},"01M6AE571R3SC1ZGE202B3NB5S","resemble-detect","Deepfake detection and media safety — detect AI-generated audio, images, video, and text, trace synthesis sources, apply watermarks, verify speaker identity, and analyze media intelligence using Resemble AI","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fresemble-detect\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fresemble-detect\u002FSKILL.md",[198,199,202],{"categoryNo":164,"categoryName":165,"taxonomyType":72,"taxonomyTypeDesc":73},{"categoryNo":200,"categoryName":201,"taxonomyType":72,"taxonomyTypeDesc":73},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":75,"categoryName":76,"taxonomyType":72,"taxonomyTypeDesc":73},[204,109,177,205,206],"resemble detect","https","identity",{"skillNo":208,"name":209,"nameZh":6,"description":210,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":194,"licenseFileUrl":211,"sourceHtmlUrl":212,"categories":213,"keywords":218,"publishedAt":33},"01M6AE30BSK2HCY4TQQ22Z8JRD","quality-playbook","Run a complete quality engineering audit on any codebase. Derives behavioral requirements from the code, generates spec-traced functional tests, runs a three-pass code review with regression tests, executes a multi-model spec audit (Council of Three), and produces a consolidated bug report with TDD-verified patches. Finds the 35% of real defects that structural code review alone cannot catch. Works with any language. Trigger on 'quality playbook', 'spec audit', 'Council of Three', 'fitness-to-purpose', or 'coverage theater'.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fquality-playbook\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fquality-playbook\u002FSKILL.md",[214,217],{"categoryNo":215,"categoryName":216,"taxonomyType":72,"taxonomyTypeDesc":73},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":75,"categoryName":76,"taxonomyType":72,"taxonomyTypeDesc":73},[219,220,221,222,140,84,9,108,223,224,205,225,226,227,228,229,230,231,232,233,234,235,92,236,237,238,239],"playbook","quality playbook","quality","code review","tdd","run","report","spec","bug report","council","engineering","functional","spec audit","bug","verified","multi-model","three","coverage","model","regression","structural"]