[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ADHYTP3AWBAFGWKDYSG9A6":3,"skill-same:01M6ADHYTP3AWBAFGWKDYSG9A6":84},{"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":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":53,"ownerHtmlUrl":54,"ownerBlogUrl":55,"ownerDescription":56,"updatedAt":57,"install":58,"resources":71},"01M6ADHYTP3AWBAFGWKDYSG9A6","eyeball",null,"Document analysis with inline source screenshots. When you ask Copilot to analyze a document, Eyeball generates a Word doc where every factual claim includes a highlighted screenshot from the source material so you can verify it with your own eyes.","github\u002Fawesome-copilot","github","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F9919?v=4","01M6AC83DS133TPXFSP1DHNCC6","GitHub","01M6AD3PBDYPK7NVFJNJ66Y8RS",41081,"MIT","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Feyeball\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000002","文档处理","SCENARIO","使用场景",[5,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"document","when","inline","source","can","ask copilot","you","with","material","claim","screenshots","eyes","ask","analyze","Word","analysis","doc","screenshot","copilot","2026-11-10 10:12:30",false,"---\nname: eyeball\ndescription: 'Document analysis with inline source screenshots. When you ask Copilot to analyze a document, Eyeball generates a Word doc where every factual claim includes a highlighted screenshot from the source material so you can verify it with your own eyes.'\n---\n\n# Eyeball\n\nAnalyze documents with visual proof. When activated, Eyeball produces a Word document on the user's Desktop where every factual assertion includes an inline screenshot from the source material with the cited text highlighted in yellow.\n\n## Activation\n\nWhen the user invokes this skill (e.g., \"use eyeball\", \"run eyeball on this\", \"eyeball this document\"), respond with:\n\n> **Eyeball is active.** I'll analyze the document and produce a Word doc with inline source screenshots so you can verify every claim with your own eyes.\n\nThen follow the workflow below.\n\n## Supported Sources\n\n- **Local files:** Word documents (.docx, .doc), PDFs (.pdf), RTF files\n- **Web URLs:** Any publicly accessible web page\n\n## Tool Location\n\nThe Eyeball Python utility is located at:\n```\n\u003Cplugin_dir>\u002Fskills\u002Feyeball\u002Ftools\u002Feyeball.py\n```\n\nTo find the actual path, run:\n```bash\nfind ~\u002F.copilot\u002Finstalled-plugins -name \"eyeball.py\" -path \"*\u002Feyeball\u002F*\" 2>\u002Fdev\u002Fnull\n```\n\nIf not found there, check the project directory or the user's home directory for the eyeball repo.\n\n## First-Run Setup\n\nBefore first use, check that dependencies are installed:\n\n```bash\npython3 \u003Cpath-to>\u002Feyeball.py setup-check\n```\n\nIf anything is missing, install the required dependencies:\n```bash\npip3 install pymupdf pillow python-docx playwright\npython3 -m playwright install chromium\n```\n\nOn Windows, also install pywin32 for Word automation:\n```bash\npip install pywin32\n```\n\n## Workflow\n\nFollow these steps exactly. The order matters.\n\n### Step 1: Read the source text\n\nBefore writing any analysis, extract and read the full text of the source document:\n\n```bash\npython3 \u003Cpath-to>\u002Feyeball.py extract-text --source \"\u003Cpath-or-url>\"\n```\n\nRead the output carefully. Identify actual section numbers, headings, page numbers, and key language.\n\n**CRITICAL:** Do not skip this step. Do not write analysis based on assumptions about how the document is structured. Read the actual text.\n\n### Step 2: Write analysis with exact citations\n\nFor each point in your analysis, you must:\n\n1. **Reference the correct section number as it appears in the document** (e.g., \"Section 9\" not \"Section 8\" because you assumed the numbering).\n2. **Reference the correct page number** where the section appears in the extracted text.\n3. **Select anchors that are verbatim phrases from the source** that directly support your claim.\n\n### Step 3: Select anchors correctly\n\nThis is the most important step. Anchors determine what gets highlighted in the screenshots.\n\n**DO:**\n- Use verbatim phrases from the source text that directly support your assertion\n- Use multiple anchors to span the full range of text the reader should see\n- Use specific, uncommon phrases that appear only where you intend\n\n**DO NOT:**\n- Use generic topic labels (e.g., \"Confidentiality\") that appear throughout the document\n- Use section titles alone when they appear as cross-references elsewhere\n- Use single common words that match in many places\n\n**Examples:**\n\nWRONG -- uses a generic topic label that matches everywhere:\n```json\n{\"anchors\": [\"User-Generated Content\"], \"target_page\": 8}\n```\n\nRIGHT -- uses the specific language that supports the claim:\n```json\n{\"anchors\": [\"retain ownership\", \"Ownership of Content, Right to Post\"], \"target_page\": 8}\n```\n\nWRONG -- section title appears as a cross-reference on earlier pages:\n```json\n{\"anchors\": [\"LIMITATION OF LIABILITY\"]}\n```\n\nRIGHT -- includes the section number for precision, targets the correct page:\n```json\n{\"anchors\": [\"12. LIMITATION OF LIABILITY\", \"INDIRECT\", \"CONSEQUENTIAL\"], \"target_page\": 13}\n```\n\n### Step 4: Build the analysis document\n\nConstruct a JSON array of sections and call the build command:\n\n```bash\npython3 \u003Cpath-to>\u002Feyeball.py build \\\n  --source \"\u003Cpath-or-url>\" \\\n  --output ~\u002FDesktop\u002F\u003Ctitle>.docx \\\n  --title \"Analysis Title\" \\\n  --subtitle \"Source description\" \\\n  --sections '[\n    {\n      \"heading\": \"1. Section Title\",\n      \"analysis\": \"Your analysis text here. Reference Section X on page Y...\",\n      \"anchors\": [\"verbatim phrase 1\", \"verbatim phrase 2\"],\n      \"target_page\": 5,\n      \"context_padding\": 40\n    },\n    {\n      \"heading\": \"2. Another Section\",\n      \"analysis\": \"More analysis...\",\n      \"anchors\": [\"exact quote from source\"],\n      \"target_pages\": [10, 11],\n      \"context_padding\": 50\n    }\n  ]'\n```\n\nSection object fields:\n- `heading` (required): Section heading in the output document\n- `analysis` (required): Your analysis text\n- `anchors` (required): List of verbatim phrases from the source to search for and highlight\n- `target_page` (optional): Single page number (1-indexed) to search on\n- `target_pages` (optional): List of page numbers to search across (screenshots stitched vertically)\n- `context_padding` (optional): Padding in PDF points above\u002Fbelow the anchor region (default: 40). Increase for more context.\n\n### Step 5: Deliver the output\n\nSave the output to the user's Desktop. Tell the user the filename and that they can open it to verify each claim against the highlighted source screenshots.\n\n## Self-Check Before Delivery\n\nBefore saving the final document, mentally verify:\n\n1. Does each section's analysis text reference the correct section number from the source?\n2. Are the anchors verbatim phrases that appear on the target page?\n3. Does each anchor directly support the claim in the analysis, not just relate to the same topic?\n4. If the screenshot doesn't match the analysis, is the analysis wrong or is the anchor wrong? Fix whichever is incorrect.\n\n## Notes\n\n- The output document includes highlighted screenshots that are dynamically sized. If you provide multiple anchors, the screenshot expands to cover all of them.\n- When a search term is not found, the output document will note this. If this happens, the anchor was likely not verbatim enough. Adjust and rebuild.\n- For web pages, Playwright renders the page to PDF first. The resulting page numbers may differ from what you see in a browser. Use the extracted text output (step 1) to determine correct page numbers.\n- If the user has already provided the source text or you have already read it in the current conversation, you can skip step 1. But always verify section numbers and page references against the actual text before writing analysis.\n","# Eyeball\n\nAnalyze documents with visual proof. When activated, Eyeball produces a Word document on the user's Desktop where every factual assertion includes an inline screenshot from the source material with the cited text highlighted in yellow.\n\n## Activation\n\nWhen the user invokes this skill (e.g., \"use eyeball\", \"run eyeball on this\", \"eyeball this document\"), respond with:\n\n> **Eyeball is active.** I'll analyze the document and produce a Word doc with inline source screenshots so you can verify every claim with your own eyes.\n\nThen follow the workflow below.\n\n## Supported Sources\n\n- **Local files:** Word documents (.docx, .doc), PDFs (.pdf), RTF files\n- **Web URLs:** Any publicly accessible web page\n\n## Tool Location\n\nThe Eyeball Python utility is located at:\n```\n\u003Cplugin_dir>\u002Fskills\u002Feyeball\u002Ftools\u002Feyeball.py\n```\n\nTo find the actual path, run:\n```bash\nfind ~\u002F.copilot\u002Finstalled-plugins -name \"eyeball.py\" -path \"*\u002Feyeball\u002F*\" 2>\u002Fdev\u002Fnull\n```\n\nIf not found there, check the project directory or the user's home directory for the eyeball repo.\n\n## First-Run Setup\n\nBefore first use, check that dependencies are installed:\n\n```bash\npython3 \u003Cpath-to>\u002Feyeball.py setup-check\n```\n\nIf anything is missing, install the required dependencies:\n```bash\npip3 install pymupdf pillow python-docx playwright\npython3 -m playwright install chromium\n```\n\nOn Windows, also install pywin32 for Word automation:\n```bash\npip install pywin32\n```\n\n## Workflow\n\nFollow these steps exactly. The order matters.\n\n### Step 1: Read the source text\n\nBefore writing any analysis, extract and read the full text of the source document:\n\n```bash\npython3 \u003Cpath-to>\u002Feyeball.py extract-text --source \"\u003Cpath-or-url>\"\n```\n\nRead the output carefully. Identify actual section numbers, headings, page numbers, and key language.\n\n**CRITICAL:** Do not skip this step. Do not write analysis based on assumptions about how the document is structured. Read the actual text.\n\n### Step 2: Write analysis with exact citations\n\nFor each point in your analysis, you must:\n\n1. **Reference the correct section number as it appears in the document** (e.g., \"Section 9\" not \"Section 8\" because you assumed the numbering).\n2. **Reference the correct page number** where the section appears in the extracted text.\n3. **Select anchors that are verbatim phrases from the source** that directly support your claim.\n\n### Step 3: Select anchors correctly\n\nThis is the most important step. Anchors determine what gets highlighted in the screenshots.\n\n**DO:**\n- Use verbatim phrases from the source text that directly support your assertion\n- Use multiple anchors to span the full range of text the reader should see\n- Use specific, uncommon phrases that appear only where you intend\n\n**DO NOT:**\n- Use generic topic labels (e.g., \"Confidentiality\") that appear throughout the document\n- Use section titles alone when they appear as cross-references elsewhere\n- Use single common words that match in many places\n\n**Examples:**\n\nWRONG -- uses a generic topic label that matches everywhere:\n```json\n{\"anchors\": [\"User-Generated Content\"], \"target_page\": 8}\n```\n\nRIGHT -- uses the specific language that supports the claim:\n```json\n{\"anchors\": [\"retain ownership\", \"Ownership of Content, Right to Post\"], \"target_page\": 8}\n```\n\nWRONG -- section title appears as a cross-reference on earlier pages:\n```json\n{\"anchors\": [\"LIMITATION OF LIABILITY\"]}\n```\n\nRIGHT -- includes the section number for precision, targets the correct page:\n```json\n{\"anchors\": [\"12. LIMITATION OF LIABILITY\", \"INDIRECT\", \"CONSEQUENTIAL\"], \"target_page\": 13}\n```\n\n### Step 4: Build the analysis document\n\nConstruct a JSON array of sections and call the build command:\n\n```bash\npython3 \u003Cpath-to>\u002Feyeball.py build \\\n  --source \"\u003Cpath-or-url>\" \\\n  --output ~\u002FDesktop\u002F\u003Ctitle>.docx \\\n  --title \"Analysis Title\" \\\n  --subtitle \"Source description\" \\\n  --sections '[\n    {\n      \"heading\": \"1. Section Title\",\n      \"analysis\": \"Your analysis text here. Reference Section X on page Y...\",\n      \"anchors\": [\"verbatim phrase 1\", \"verbatim phrase 2\"],\n      \"target_page\": 5,\n      \"context_padding\": 40\n    },\n    {\n      \"heading\": \"2. Another Section\",\n      \"analysis\": \"More analysis...\",\n      \"anchors\": [\"exact quote from source\"],\n      \"target_pages\": [10, 11],\n      \"context_padding\": 50\n    }\n  ]'\n```\n\nSection object fields:\n- `heading` (required): Section heading in the output document\n- `analysis` (required): Your analysis text\n- `anchors` (required): List of verbatim phrases from the source to search for and highlight\n- `target_page` (optional): Single page number (1-indexed) to search on\n- `target_pages` (optional): List of page numbers to search across (screenshots stitched vertically)\n- `context_padding` (optional): Padding in PDF points above\u002Fbelow the anchor region (default: 40). Increase for more context.\n\n### Step 5: Deliver the output\n\nSave the output to the user's Desktop. Tell the user the filename and that they can open it to verify each claim against the highlighted source screenshots.\n\n## Self-Check Before Delivery\n\nBefore saving the final document, mentally verify:\n\n1. Does each section's analysis text reference the correct section number from the source?\n2. Are the anchors verbatim phrases that appear on the target page?\n3. Does each anchor directly support the claim in the analysis, not just relate to the same topic?\n4. If the screenshot doesn't match the analysis, is the analysis wrong or is the anchor wrong? Fix whichever is incorrect.\n\n## Notes\n\n- The output document includes highlighted screenshots that are dynamically sized. If you provide multiple anchors, the screenshot expands to cover all of them.\n- When a search term is not found, the output document will note this. If this happens, the anchor was likely not verbatim enough. Adjust and rebuild.\n- For web pages, Playwright renders the page to PDF first. The resulting page numbers may differ from what you see in a browser. Use the extracted text output (step 1) to determine correct page numbers.\n- If the user has already provided the source text or you have already read it in the current conversation, you can skip step 1. But always verify section numbers and page references against the actual text before writing analysis.\n",{"name":5,"description":7},"main","5269f7ea2d6c3a9bfda5ed878b6726cf509121fd","skills\u002Feyeball",5344,"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.","2026-11-13 02:05:36",{"source":8,"skillName":5,"commands":59,"prompt":69,"zipAvailable":70},[60,63,66],{"tool":61,"command":62},"npx","npx skills add github\u002Fawesome-copilot --skill eyeball",{"tool":64,"command":65},"bunx","bunx skills add github\u002Fawesome-copilot --skill eyeball",{"tool":67,"command":68},"pnpm","pnpm dlx skills add github\u002Fawesome-copilot --skill eyeball","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Feyeball\u002FSKILL.md",true,[72,78],{"path":73,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":76,"sourceHtmlUrl":77},"CREDITS.md","REFERENCE","参考文档",1195,"https:\u002F\u002Fgithub.com\u002Fderseitenschneider\u002Fdotfiles\u002Fblob\u002Fmain\u002Fclaude-config\u002F.claude\u002Fskills\u002Freview-loop\u002FCREDITS.md",{"path":79,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":82,"sourceHtmlUrl":83},"tools\u002Feyeball.py","SCRIPT","脚本",28494,"https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Feyeball\u002Ftools\u002Feyeball.py",[85,116,144,174,208,225],{"skillNo":86,"name":87,"nameZh":6,"description":88,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":89,"categories":90,"keywords":97,"publishedAt":43},"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",[91,94],{"categoryNo":92,"categoryName":93,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":95,"categoryName":96,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[98,99,100,101,102,25,103,104,105,106,107,108,109,110,111,112,113,114,115,31],"supabase","rls","supabase rls","supabase rls policies","project","review","change","read","write","security","isolation","tables","as","tests","prove","use","users","functions",{"skillNo":117,"name":118,"nameZh":6,"description":119,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":120,"categories":121,"keywords":123,"publishedAt":43},"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",[122],{"categoryNo":95,"categoryName":96,"taxonomyType":21,"taxonomyTypeDesc":22},[124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143],"distribution","skill distribution audit","audit","SET","deterministic","installer","for","discovery","comparison","helper","manifest","version","collection","drift","output","investigate","duplicate","template","release","reconcile",{"skillNo":145,"name":146,"nameZh":6,"description":147,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":148,"sourceHtmlUrl":149,"categories":150,"keywords":156,"publishedAt":43},"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",[151],{"categoryNo":152,"categoryName":153,"taxonomyType":154,"taxonomyTypeDesc":155},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[157,158,159,160,161,162,130,102,163,164,165,166,167,168,169,113,170,171,172,173],"custom","code","logicapps custom code net10 migration","migration","projects","standalone","deployment","applications","local","azure","worker","upgrades","package","apps","Legacy","debugging","workflows",{"skillNo":175,"name":176,"nameZh":6,"description":177,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":178,"sourceHtmlUrl":179,"categories":180,"keywords":185,"publishedAt":43},"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",[181,184],{"categoryNo":182,"categoryName":183,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":152,"categoryName":153,"taxonomyType":154,"taxonomyTypeDesc":155},[186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,25,201,202,203,204,205,130,206,207],"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":209,"name":210,"nameZh":6,"description":211,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":212,"licenseFileUrl":213,"sourceHtmlUrl":214,"categories":215,"keywords":221,"publishedAt":43},"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",[216,217,220],{"categoryNo":182,"categoryName":183,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":218,"categoryName":219,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":95,"categoryName":96,"taxonomyType":21,"taxonomyTypeDesc":22},[222,127,195,223,224],"resemble detect","https","identity",{"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":212,"licenseFileUrl":229,"sourceHtmlUrl":230,"categories":231,"keywords":236,"publishedAt":43},"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",[232,235],{"categoryNo":233,"categoryName":234,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":95,"categoryName":96,"taxonomyType":21,"taxonomyTypeDesc":22},[237,238,239,240,158,103,9,126,241,242,223,243,244,245,246,247,248,249,250,251,252,253,111,254,255,256,257],"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"]