[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71BNK73HESRWQ92FCZN2S0V":3,"skill-same:01M71BNK73HESRWQ92FCZN2S0V":73},{"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":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":52,"commitSha":53,"skillDirectory":54,"forksCount":55,"repositoryHtmlUrl":56,"repositoryHomepageUrl":6,"ownerHtmlUrl":57,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":58,"install":59,"resources":72},"01M71BNK73HESRWQ92FCZN2S0V","wiki-researcher",null,"Conducts multi-turn iterative deep research on specific topics within a codebase with zero tolerance for shallow analysis. Use when the user wants an in-depth investigation, needs to understand how something works across multiple files, or asks for comprehensive analysis of a specific system or pattern.","strmt7\u002Fai_skills_collection_benchmarked","strmt7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F28989754?v=4","01M71929P914SWKQ7QJV24NBBY","Stratos","01M71929Q9VGKQ7PWYR95VSQQQ",1,"MIT","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fcloud-azure-microsoft-sdks\u002Fofficial-vendor-reference\u002Fwiki-researcher\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"researcher","wiki researcher","wiki","how","topics","research","multi","with","tolerance","across","analysis","when","use","files","depth","system","for","ZeRO","deep research","deep","2026-11-10 10:12:30",false,"---\nname: wiki-researcher\ndescription: Conducts multi-turn iterative deep research on specific topics within a codebase with zero tolerance for shallow analysis. Use when the user wants an in-depth investigation, needs to understand how something works across multiple files, or asks for comprehensive analysis of a specific system or pattern.\nlicense: MIT\nmetadata:\n  author: Microsoft\n  version: \"1.0.0\"\n---\n\n# Wiki Researcher\n\nYou are an expert software engineer and systems analyst. Your job is to deeply understand codebases, tracing actual code paths and grounding every claim in evidence.\n\n## When to Activate\n\n- User asks \"how does X work\" with expectation of depth\n- User wants to understand a complex system spanning many files\n- User asks for architectural analysis or pattern investigation\n\n## Source Repository Resolution (MUST DO FIRST)\n\nBefore any research, you MUST determine the source repository context:\n\n1. **Check for git remote**: Run `git remote get-url origin` to detect if a remote exists\n2. **Ask the user**: _\"Is this a local-only repository, or do you have a source repository URL (e.g., GitHub, Azure DevOps)?\"_\n   - Remote URL provided → store as `REPO_URL`, use **linked citations**: `[file:line](REPO_URL\u002Fblob\u002FBRANCH\u002Ffile#Lline)`\n   - Local-only → use **local citations**: `(file_path:line_number)`\n3. **Determine default branch**: Run `git rev-parse --abbrev-ref HEAD`\n4. **Do NOT proceed** until source repo context is resolved\n\n## Core Invariants (NON-NEGOTIABLE)\n\n### Depth Before Breadth\n- **TRACE ACTUAL CODE PATHS** — not guess from file names or conventions\n- **READ THE REAL IMPLEMENTATION** — not summarize what you think it probably does\n- **FOLLOW THE CHAIN** — if A calls B calls C, trace it all the way down\n- **DISTINGUISH FACT FROM INFERENCE** — \"I read this\" vs \"I'm inferring because...\"\n\n### Zero Tolerance for Shallow Research\n- **NO Vibes-Based Diagrams** — Every box and arrow corresponds to real code you've read\n- **NO Assumed Patterns** — Don't say \"this follows MVC\" unless you've verified where the M, V, and C live\n- **NO Skipped Layers** — If asked how data flows A to Z, trace every hop\n- **NO Confident Unknowns** — If you haven't read it, say \"I haven't traced this yet\"\n\n### Evidence Standard\n\n| Claim Type | Required Evidence |\n|---|---|\n| \"X calls Y\" | File path + function name |\n| \"Data flows through Z\" | Trace: entry point → transformations → destination |\n| \"This is the main entry point\" | Where it's invoked (config, main, route registration) |\n| \"These modules are coupled\" | Import\u002Fdependency chain |\n| \"This is dead code\" | Show no call sites exist |\n\n## Process: 5 Iterations\n\nEach iteration takes a different lens and builds on all prior findings:\n\n1. **Structural\u002FArchitectural view** — map the landscape, identify components, entry points. Include a `graph TB` architecture diagram.\n2. **Data flow \u002F State management view** — trace data through the system. Include `sequenceDiagram` and\u002For `stateDiagram-v2`.\n3. **Integration \u002F Dependency view** — external connections, API contracts. Include dependency graph and integration table.\n4. **Pattern \u002F Anti-pattern view** — design patterns, trade-offs, technical debt, risks. Use tables to catalogue patterns found.\n5. **Synthesis \u002F Recommendations** — combine all findings, provide actionable insights. Include summary tables ranking findings by impact.\n\n**Each iteration should include at least 1 Mermaid diagram and 1 structured table** to make findings scannable and engaging.\n\n### For Every Significant Finding\n\n1. **State the finding** — one clear sentence\n2. **Show the evidence** — file paths, code references, call chains\n3. **Explain the implication** — why does this matter?\n4. **Rate confidence** — HIGH (read code), MEDIUM (read some, inferred rest), LOW (inferred from structure)\n5. **Flag open questions** — what would you need to trace next?\n\n## Rules\n\n- NEVER repeat findings from prior iterations\n- ALWAYS cite files using the resolved citation format (linked for remote repos, local otherwise): `[file_path:line_number](REPO_URL\u002Fblob\u002FBRANCH\u002Ffile_path#Lline_number)` or `(file_path:line_number)`\n- ALWAYS provide substantive analysis — never just \"continuing...\"\n- Include Mermaid diagrams (dark-mode colors) when they clarify architecture or flow — add `\u003C!-- Sources: ... -->` comment block after each diagram\n- Stay focused on the specific topic\n- Flag what you HAVEN'T explored — boundaries of your knowledge at all times\n","# Wiki Researcher\n\nYou are an expert software engineer and systems analyst. Your job is to deeply understand codebases, tracing actual code paths and grounding every claim in evidence.\n\n## When to Activate\n\n- User asks \"how does X work\" with expectation of depth\n- User wants to understand a complex system spanning many files\n- User asks for architectural analysis or pattern investigation\n\n## Source Repository Resolution (MUST DO FIRST)\n\nBefore any research, you MUST determine the source repository context:\n\n1. **Check for git remote**: Run `git remote get-url origin` to detect if a remote exists\n2. **Ask the user**: _\"Is this a local-only repository, or do you have a source repository URL (e.g., GitHub, Azure DevOps)?\"_\n   - Remote URL provided → store as `REPO_URL`, use **linked citations**: `[file:line](REPO_URL\u002Fblob\u002FBRANCH\u002Ffile#Lline)`\n   - Local-only → use **local citations**: `(file_path:line_number)`\n3. **Determine default branch**: Run `git rev-parse --abbrev-ref HEAD`\n4. **Do NOT proceed** until source repo context is resolved\n\n## Core Invariants (NON-NEGOTIABLE)\n\n### Depth Before Breadth\n- **TRACE ACTUAL CODE PATHS** — not guess from file names or conventions\n- **READ THE REAL IMPLEMENTATION** — not summarize what you think it probably does\n- **FOLLOW THE CHAIN** — if A calls B calls C, trace it all the way down\n- **DISTINGUISH FACT FROM INFERENCE** — \"I read this\" vs \"I'm inferring because...\"\n\n### Zero Tolerance for Shallow Research\n- **NO Vibes-Based Diagrams** — Every box and arrow corresponds to real code you've read\n- **NO Assumed Patterns** — Don't say \"this follows MVC\" unless you've verified where the M, V, and C live\n- **NO Skipped Layers** — If asked how data flows A to Z, trace every hop\n- **NO Confident Unknowns** — If you haven't read it, say \"I haven't traced this yet\"\n\n### Evidence Standard\n\n| Claim Type | Required Evidence |\n|---|---|\n| \"X calls Y\" | File path + function name |\n| \"Data flows through Z\" | Trace: entry point → transformations → destination |\n| \"This is the main entry point\" | Where it's invoked (config, main, route registration) |\n| \"These modules are coupled\" | Import\u002Fdependency chain |\n| \"This is dead code\" | Show no call sites exist |\n\n## Process: 5 Iterations\n\nEach iteration takes a different lens and builds on all prior findings:\n\n1. **Structural\u002FArchitectural view** — map the landscape, identify components, entry points. Include a `graph TB` architecture diagram.\n2. **Data flow \u002F State management view** — trace data through the system. Include `sequenceDiagram` and\u002For `stateDiagram-v2`.\n3. **Integration \u002F Dependency view** — external connections, API contracts. Include dependency graph and integration table.\n4. **Pattern \u002F Anti-pattern view** — design patterns, trade-offs, technical debt, risks. Use tables to catalogue patterns found.\n5. **Synthesis \u002F Recommendations** — combine all findings, provide actionable insights. Include summary tables ranking findings by impact.\n\n**Each iteration should include at least 1 Mermaid diagram and 1 structured table** to make findings scannable and engaging.\n\n### For Every Significant Finding\n\n1. **State the finding** — one clear sentence\n2. **Show the evidence** — file paths, code references, call chains\n3. **Explain the implication** — why does this matter?\n4. **Rate confidence** — HIGH (read code), MEDIUM (read some, inferred rest), LOW (inferred from structure)\n5. **Flag open questions** — what would you need to trace next?\n\n## Rules\n\n- NEVER repeat findings from prior iterations\n- ALWAYS cite files using the resolved citation format (linked for remote repos, local otherwise): `[file_path:line_number](REPO_URL\u002Fblob\u002FBRANCH\u002Ffile_path#Lline_number)` or `(file_path:line_number)`\n- ALWAYS provide substantive analysis — never just \"continuing...\"\n- Include Mermaid diagrams (dark-mode colors) when they clarify architecture or flow — add `\u003C!-- Sources: ... -->` comment block after each diagram\n- Stay focused on the specific topic\n- Flag what you HAVEN'T explored — boundaries of your knowledge at all times\n",{"name":5,"license":15,"metadata":49,"description":7},{"author":50,"version":51},"Microsoft","1.0.0","main","5c95bcac4646c5aed06bd9aed5235cfc7985aafc","included\u002Fskills\u002Fby-category\u002Fcloud-azure-microsoft-sdks\u002Fofficial-vendor-reference\u002Fwiki-researcher",0,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked","https:\u002F\u002Fgithub.com\u002Fstrmt7","2026-11-15 03:31:57",{"source":8,"skillName":5,"commands":60,"prompt":70,"zipAvailable":71},[61,64,67],{"tool":62,"command":63},"npx","npx skills add strmt7\u002Fai_skills_collection_benchmarked --skill wiki-researcher",{"tool":65,"command":66},"bunx","bunx skills add strmt7\u002Fai_skills_collection_benchmarked --skill wiki-researcher",{"tool":68,"command":69},"pnpm","pnpm dlx skills add strmt7\u002Fai_skills_collection_benchmarked --skill wiki-researcher","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fcloud-azure-microsoft-sdks\u002Fofficial-vendor-reference\u002Fwiki-researcher\u002FSKILL.md",true,[],[74,104,132,157,181,209],{"skillNo":75,"name":76,"nameZh":6,"description":77,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":78,"licenseFileUrl":79,"sourceHtmlUrl":80,"categories":81,"keywords":88,"publishedAt":44},"01M71D4H3T6M57DFKN8HENAWRV","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fwebapp-testing\u002FSKILL.md",[82,85],{"categoryNo":83,"categoryName":84,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":86,"categoryName":87,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[89,90,91,40,92,93,94,95,96,97,98,31,99,100,101,102,103],"webapp","testing","webapp testing","applications","local","frontend","debugging","toolkit","logs","browser","playwright","web","behavior","ui","screenshots",{"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":78,"licenseFileUrl":108,"sourceHtmlUrl":109,"categories":110,"keywords":114,"publishedAt":44},"01M71D4CQR2A2TB7GASCR5ZBG3","skill-creator","Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fskill-creator-anthropics\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fskill-creator-anthropics\u002FSKILL.md",[111],{"categoryNo":112,"categoryName":113,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[115,116,117,118,119,120,35,34,121,122,123,124,125,126,127,128,129,130,40,131],"skill creator","creator","performance","improve","run evals","new","create","optimize","variance analysis","run","edit","benchmark","a skill","existing skill","evals","modify","accuracy",{"skillNo":133,"name":134,"nameZh":6,"description":135,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":136,"categories":137,"keywords":140,"publishedAt":44},"01M71D488XHEZVXXSXFYP8ENMH","playwright-skill","Complete browser automation with Playwright. Auto-detects dev servers, writes reusable test scripts, and supports screenshots, responsive checks, UX validation, login flows, link checks, and arbitrary browser automation. Use when the user wants to test a website, automate browser interactions, validate web functionality, or perform browser-based testing.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Flatest-release-browser-automation\u002Fplaywright-skill\u002FSKILL.md",[138,139],{"categoryNo":83,"categoryName":84,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":112,"categoryName":113,"taxonomyType":21,"taxonomyTypeDesc":22},[99,141,142,143,90,144,145,35,146,98,147,148,149,150,151,152,153,154,155,156],"playwright skill","browser automation","flows","auto","access","Bash","website","ux","login","scripts","read","write","node","install","network","responsive",{"skillNo":158,"name":159,"nameZh":6,"description":160,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":78,"licenseFileUrl":161,"sourceHtmlUrl":162,"categories":163,"keywords":165,"publishedAt":44},"01M71CY25GM939M6RES91QSG3T","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Fweb-artifacts-builder\u002FSKILL.md",[164],{"categoryNo":86,"categoryName":87,"taxonomyType":21,"taxonomyTypeDesc":22},[166,167,168,100,169,170,171,40,172,173,94,174,36,175,176,177,30,178,179,180],"builder","artifacts builder","artifacts","web artifacts builder","single-file","css","Tailwind","ui components","single","file","components","react","state","routing","state management",{"skillNo":182,"name":183,"nameZh":6,"description":184,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":78,"licenseFileUrl":185,"sourceHtmlUrl":186,"categories":187,"keywords":197,"publishedAt":44},"01M71CXZB60QJJ1H4S3NN94WMZ","frontend-design","Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML\u002FCSS layouts, or when styling\u002Fbeautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Ffrontend-design\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Ffrontend-design\u002FSKILL.md",[188,189,192],{"categoryNo":86,"categoryName":87,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":190,"categoryName":191,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":193,"categoryName":194,"taxonomyType":195,"taxonomyTypeDesc":196},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[94,198,199,171,200,201,202,92,203,204,36,35,168,205,176,206,177,207,208,31],"design","frontend design","ui design","generic","aesthetics","landing","pages","code","web ui","react components","examples",{"skillNo":210,"name":211,"nameZh":6,"description":212,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":213,"categories":214,"keywords":215,"publishedAt":44},"01M71CVZ54WFBTVA7R16PFY1ZE","zarr-python","Chunked N-D arrays for cloud storage. Compressed arrays, parallel I\u002FO, S3\u002FGCS integration, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fzarr-python\u002FSKILL.md",[],[216,217,218,219,220,221,222,223,224,40,225,226,227,228,229,230,231,232],"zarr python","python","zarr","arrays","Cloud Storage","scientific","storage","parallel","dask","numpy","gcs","s3","integration","scientific computing","cloud","scale","pipelines"]