[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6C2S2SKEZPFWXG1XHDEFSFA":3,"skill-same:01M6C2S2SKEZPFWXG1XHDEFSFA":120},{"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":16,"sourceHtmlUrl":17,"categories":18,"keywords":29,"publishedAt":55,"linkOnly":56,"markdownContent":57,"markdownBody":58,"frontMatter":59,"refName":65,"commitSha":66,"skillDirectory":67,"forksCount":14,"repositoryHtmlUrl":68,"repositoryHomepageUrl":6,"ownerHtmlUrl":69,"ownerBlogUrl":6,"ownerDescription":70,"updatedAt":71,"install":72,"resources":84},"01M6C2S2SKEZPFWXG1XHDEFSFA","seo-audit",null,"Full website SEO audit with parallel subagent delegation. Crawls up to 500 pages, detects business type, delegates to up to 15 specialists (8 always + 7 conditional), generates health score. Use when user says audit, full SEO check, analyze my site, or website health check.","noirelab\u002Flinux-setup","noirelab","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F142925921?v=4","01M6C29R3FEDGFAXAT0KXY28QX","Kaíque M. Lima","01M6C29R811WX04B0GYHTH1XV6",0,"MIT","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fopencode\u002Fskills\u002Fseo-audit\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fopencode\u002Fskills\u002Fseo-audit\u002FSKILL.md",[19,24],{"categoryNo":20,"categoryName":21,"taxonomyType":22,"taxonomyTypeDesc":23},"01JBSEEDCAT000000000000019","营销推广","SCENARIO","使用场景",{"categoryNo":25,"categoryName":26,"taxonomyType":27,"taxonomyTypeDesc":28},"01JBSEEDCAT000000000000035","市场营销","PROFESSION","适用职业",[30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54],"audit","seo audit","seo","user","when","conditional","my","true","URL","type","pages","full","up","health check","use","business","delegation","check","parallel","analyze","site","subagent","health","website seo audit","website","2026-11-10 10:12:30",false,"---\nname: seo-audit\ndescription: \"Full website SEO audit with parallel subagent delegation. Crawls up to 500 pages, detects business type, delegates to up to 15 specialists (8 always + 7 conditional), generates health score. Use when user says audit, full SEO check, analyze my site, or website health check.\"\nuser-invocable: true\nargument-hint: \"[url]\"\nlicense: MIT\nmetadata:\n  author: AgriciDaniel\n  version: \"2.2.4\"\n  category: seo\n---\n\n# Full Website SEO Audit\n\n## Process\n\n1. **Render homepage**: use `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run render_page.py \u003Curl> --mode auto --json` to capture raw HTML, rendered HTML, extracted text, SPA status, and accessibility data when needed\n2. **Detect business type**: analyze homepage signals per seo orchestrator\n3. **Crawl site**: follow internal links up to 500 pages, respect robots.txt\n4. **Delegate to subagents** (if available, otherwise run inline sequentially):\n   - `seo-technical` -- robots.txt, sitemaps, canonicals, Core Web Vitals, security headers\n   - `seo-content` -- E-E-A-T, readability, thin content, AI citation readiness\n   - `seo-schema` -- detection, validation, generation recommendations\n   - `seo-sitemap` -- structure analysis, quality gates, missing pages\n   - `seo-performance` -- LCP, INP, CLS measurements\n   - `seo-visual` -- screenshots, mobile testing, above-fold analysis\n   - `seo-geo` -- AI crawler access, llms.txt, citability, brand mention signals\n   - `seo-local` -- GBP signals, NAP consistency, reviews, local schema, industry-specific local factors (spawn when Local Service industry detected: brick-and-mortar, SAB, or hybrid business type)\n   - `seo-maps` -- Geo-grid rank tracking, GBP audit, review intelligence, competitor radius mapping (spawn when Local Service detected AND DataForSEO MCP available)\n   - `seo-google` -- CWV field data (CrUX), URL indexation (GSC), organic traffic (GA4) (spawn when Google API credentials detected via `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run google_auth.py --check`)\n   - `seo-backlinks` -- Backlink profile data: DA\u002FPA, referring domains, anchor text, toxic links (spawn when Moz or Bing API credentials detected via `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run backlinks_auth.py --check`, or always include Common Crawl domain-level metrics)\n   - `seo-cluster` -- Semantic clustering analysis (spawn when content strategy signals detected: blog, pillar pages, topic clusters)\n   - `seo-sxo` -- Search experience analysis: page-type mismatch, user stories, persona scoring (always include in full audits)\n   - `seo-drift` -- Drift analysis: compare against stored baseline (spawn when drift baseline exists for the URL via `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run drift_history.py \u003Curl>`)\n   - `seo-ecommerce` -- Product schema, marketplace intelligence (spawn when E-commerce industry detected)\n5. **Score** -- aggregate into SEO Health Score (0-100)\n6. **Persist audit artifacts** -- write all outputs under `{domain}-audit\u002F`\n7. **Report** -- generate prioritized action plan and optional PDF\u002FHTML report\n\n## Crawl Configuration\n\n```\nMax pages: 500\nRespect robots.txt: Yes\nFollow redirects: Yes (max 3 hops)\nTimeout per page: 30 seconds\nConcurrent requests: 5\nDelay between requests: 1 second\n```\n\n## Output Files\n\n- `{domain}-audit\u002FFULL-AUDIT-REPORT.md`: Comprehensive findings\n- `{domain}-audit\u002FACTION-PLAN.md`: Prioritized recommendations (Critical > High > Medium > Low)\n- `{domain}-audit\u002Faudit-data.json`: Structured audit envelope for report generation\n- `{domain}-audit\u002Ffindings\u002F*.md`: Per-category specialist findings (`technical.md`, `content.md`, `schema.md`, `performance.md`, `visual.md`, etc.)\n- `{domain}-audit\u002Fscreenshots\u002F`: Desktop + mobile captures (if Playwright available)\n- **PDF Report** (recommended): Generate a professional A4 PDF using `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run google_report.py --type full --data {domain}-audit\u002Faudit-data.json --domain \u003Cdomain> --output-dir {domain}-audit\u002F`. This produces a white-cover enterprise report with TOC, executive summary, charts (Lighthouse gauges, query bars, index donut), metric cards, threshold tables, prioritized recommendations with effort estimates, and implementation roadmap. Always offer PDF generation after completing an audit.\n\n## Structured Audit Data Envelope\n\nWrite `{domain}-audit\u002Faudit-data.json` with this shape so `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run google_report.py --type full --data {domain}-audit\u002Faudit-data.json --domain \u003Cdomain> --output-dir {domain}-audit\u002F` can generate a report even when Google API data is unavailable:\n\n```json\n{\n  \"summary\": {\n    \"health_score\": 0,\n    \"business_type\": \"detected type\",\n    \"top_findings\": [],\n    \"quick_wins\": []\n  },\n  \"categories\": [\n    {\n      \"name\": \"Technical SEO\",\n      \"score\": 0,\n      \"what_works\": [],\n      \"findings\": [\n        {\n          \"title\": \"Finding title\",\n          \"severity\": \"Critical|High|Medium|Low|Info\",\n          \"description\": \"Evidence-backed detail\",\n          \"recommendation\": \"Specific fix\"\n        }\n      ]\n    }\n  ],\n  \"action_plan\": {\n    \"phases\": [\n      {\"name\": \"Phase 1: Critical Fixes\", \"timeframe\": \"Week 1\", \"items\": []},\n      {\"name\": \"Phase 2: High-Impact Improvements\", \"timeframe\": \"Weeks 2-3\", \"items\": []},\n      {\"name\": \"Phase 3: Content & Authority\", \"timeframe\": \"Month 2\", \"items\": []},\n      {\"name\": \"Phase 4: Monitoring & Iteration\", \"timeframe\": \"Ongoing\", \"items\": []}\n    ]\n  },\n  \"artifacts\": {\n    \"findings_dir\": \"findings\u002F\",\n    \"screenshots_dir\": \"screenshots\u002F\"\n  }\n}\n```\n\n## Scoring Weights\n\n| Category | Weight |\n|----------|--------|\n| Technical SEO | 22% |\n| Content Quality | 23% |\n| On-Page SEO | 20% |\n| Schema \u002F Structured Data | 10% |\n| Performance (CWV) | 10% |\n| AI Search Readiness | 10% |\n| Images | 5% |\n\n## Report Structure\n\n### Executive Summary\n- Overall SEO Health Score (0-100)\n- Business type detected\n- Top 5 critical issues\n- Top 5 quick wins\n\n### Technical SEO\n- Crawlability issues\n- Indexability problems\n- Security concerns\n- Core Web Vitals status\n\n### Content Quality\n- E-E-A-T assessment\n- Thin content pages\n- Duplicate content issues\n- Readability scores\n\n### On-Page SEO\n- Title tag issues\n- Meta description problems\n- Heading structure\n- Internal linking gaps\n\n### Schema & Structured Data\n- Current implementation\n- Validation errors\n- Missing opportunities\n\n### Performance\n- LCP, INP, CLS scores\n- Resource optimization needs\n- Third-party script impact\n\n### Images\n- Missing alt text\n- Oversized images\n- Format recommendations\n\n### AI Search Readiness\n- Citability score\n- Structural improvements\n- Authority signals\n\n## Priority Definitions\n\n- **Critical**: Blocks indexing or causes penalties (fix immediately)\n- **High**: Significantly impacts rankings (fix within 1 week)\n- **Medium**: Optimization opportunity (fix within 1 month)\n- **Low**: Nice to have (backlog)\n\n## DataForSEO Integration (Optional)\n\nIf DataForSEO MCP tools are available, spawn the `seo-dataforseo` agent alongside existing subagents to enrich the audit with live data: real SERP positions, backlink profiles with spam scores, on-page analysis (Lighthouse), business listings, and AI visibility checks (ChatGPT scraper, LLM mentions).\n\n## Google API Integration (Optional)\n\nIf Google API credentials are configured (`\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run google_auth.py --check`), spawn the `seo-google` agent to enrich the audit with real Google field data: CrUX Core Web Vitals (replaces lab-only estimates), GSC URL indexation status, search performance (clicks, impressions, CTR), and GA4 organic traffic trends. The Performance (CWV) category score benefits most from field data.\n\n## Error Handling\n\n| Scenario | Action |\n|----------|--------|\n| URL unreachable (DNS failure, connection refused) | Report the error clearly. Do not guess site content. Suggest the user verify the URL and try again. |\n| robots.txt blocks crawling | Report which paths are blocked. Analyze only accessible pages and note the limitation in the report. |\n| Rate limiting (429 responses) | Back off and reduce concurrent requests. Report partial results with a note on which sections could not be completed. |\n| Timeout on large sites (500+ pages) | Cap the crawl at the timeout limit. Report findings for pages crawled and estimate total site scope. |\n","# Full Website SEO Audit\n\n## Process\n\n1. **Render homepage**: use `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run render_page.py \u003Curl> --mode auto --json` to capture raw HTML, rendered HTML, extracted text, SPA status, and accessibility data when needed\n2. **Detect business type**: analyze homepage signals per seo orchestrator\n3. **Crawl site**: follow internal links up to 500 pages, respect robots.txt\n4. **Delegate to subagents** (if available, otherwise run inline sequentially):\n   - `seo-technical` -- robots.txt, sitemaps, canonicals, Core Web Vitals, security headers\n   - `seo-content` -- E-E-A-T, readability, thin content, AI citation readiness\n   - `seo-schema` -- detection, validation, generation recommendations\n   - `seo-sitemap` -- structure analysis, quality gates, missing pages\n   - `seo-performance` -- LCP, INP, CLS measurements\n   - `seo-visual` -- screenshots, mobile testing, above-fold analysis\n   - `seo-geo` -- AI crawler access, llms.txt, citability, brand mention signals\n   - `seo-local` -- GBP signals, NAP consistency, reviews, local schema, industry-specific local factors (spawn when Local Service industry detected: brick-and-mortar, SAB, or hybrid business type)\n   - `seo-maps` -- Geo-grid rank tracking, GBP audit, review intelligence, competitor radius mapping (spawn when Local Service detected AND DataForSEO MCP available)\n   - `seo-google` -- CWV field data (CrUX), URL indexation (GSC), organic traffic (GA4) (spawn when Google API credentials detected via `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run google_auth.py --check`)\n   - `seo-backlinks` -- Backlink profile data: DA\u002FPA, referring domains, anchor text, toxic links (spawn when Moz or Bing API credentials detected via `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run backlinks_auth.py --check`, or always include Common Crawl domain-level metrics)\n   - `seo-cluster` -- Semantic clustering analysis (spawn when content strategy signals detected: blog, pillar pages, topic clusters)\n   - `seo-sxo` -- Search experience analysis: page-type mismatch, user stories, persona scoring (always include in full audits)\n   - `seo-drift` -- Drift analysis: compare against stored baseline (spawn when drift baseline exists for the URL via `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run drift_history.py \u003Curl>`)\n   - `seo-ecommerce` -- Product schema, marketplace intelligence (spawn when E-commerce industry detected)\n5. **Score** -- aggregate into SEO Health Score (0-100)\n6. **Persist audit artifacts** -- write all outputs under `{domain}-audit\u002F`\n7. **Report** -- generate prioritized action plan and optional PDF\u002FHTML report\n\n## Crawl Configuration\n\n```\nMax pages: 500\nRespect robots.txt: Yes\nFollow redirects: Yes (max 3 hops)\nTimeout per page: 30 seconds\nConcurrent requests: 5\nDelay between requests: 1 second\n```\n\n## Output Files\n\n- `{domain}-audit\u002FFULL-AUDIT-REPORT.md`: Comprehensive findings\n- `{domain}-audit\u002FACTION-PLAN.md`: Prioritized recommendations (Critical > High > Medium > Low)\n- `{domain}-audit\u002Faudit-data.json`: Structured audit envelope for report generation\n- `{domain}-audit\u002Ffindings\u002F*.md`: Per-category specialist findings (`technical.md`, `content.md`, `schema.md`, `performance.md`, `visual.md`, etc.)\n- `{domain}-audit\u002Fscreenshots\u002F`: Desktop + mobile captures (if Playwright available)\n- **PDF Report** (recommended): Generate a professional A4 PDF using `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run google_report.py --type full --data {domain}-audit\u002Faudit-data.json --domain \u003Cdomain> --output-dir {domain}-audit\u002F`. This produces a white-cover enterprise report with TOC, executive summary, charts (Lighthouse gauges, query bars, index donut), metric cards, threshold tables, prioritized recommendations with effort estimates, and implementation roadmap. Always offer PDF generation after completing an audit.\n\n## Structured Audit Data Envelope\n\nWrite `{domain}-audit\u002Faudit-data.json` with this shape so `\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run google_report.py --type full --data {domain}-audit\u002Faudit-data.json --domain \u003Cdomain> --output-dir {domain}-audit\u002F` can generate a report even when Google API data is unavailable:\n\n```json\n{\n  \"summary\": {\n    \"health_score\": 0,\n    \"business_type\": \"detected type\",\n    \"top_findings\": [],\n    \"quick_wins\": []\n  },\n  \"categories\": [\n    {\n      \"name\": \"Technical SEO\",\n      \"score\": 0,\n      \"what_works\": [],\n      \"findings\": [\n        {\n          \"title\": \"Finding title\",\n          \"severity\": \"Critical|High|Medium|Low|Info\",\n          \"description\": \"Evidence-backed detail\",\n          \"recommendation\": \"Specific fix\"\n        }\n      ]\n    }\n  ],\n  \"action_plan\": {\n    \"phases\": [\n      {\"name\": \"Phase 1: Critical Fixes\", \"timeframe\": \"Week 1\", \"items\": []},\n      {\"name\": \"Phase 2: High-Impact Improvements\", \"timeframe\": \"Weeks 2-3\", \"items\": []},\n      {\"name\": \"Phase 3: Content & Authority\", \"timeframe\": \"Month 2\", \"items\": []},\n      {\"name\": \"Phase 4: Monitoring & Iteration\", \"timeframe\": \"Ongoing\", \"items\": []}\n    ]\n  },\n  \"artifacts\": {\n    \"findings_dir\": \"findings\u002F\",\n    \"screenshots_dir\": \"screenshots\u002F\"\n  }\n}\n```\n\n## Scoring Weights\n\n| Category | Weight |\n|----------|--------|\n| Technical SEO | 22% |\n| Content Quality | 23% |\n| On-Page SEO | 20% |\n| Schema \u002F Structured Data | 10% |\n| Performance (CWV) | 10% |\n| AI Search Readiness | 10% |\n| Images | 5% |\n\n## Report Structure\n\n### Executive Summary\n- Overall SEO Health Score (0-100)\n- Business type detected\n- Top 5 critical issues\n- Top 5 quick wins\n\n### Technical SEO\n- Crawlability issues\n- Indexability problems\n- Security concerns\n- Core Web Vitals status\n\n### Content Quality\n- E-E-A-T assessment\n- Thin content pages\n- Duplicate content issues\n- Readability scores\n\n### On-Page SEO\n- Title tag issues\n- Meta description problems\n- Heading structure\n- Internal linking gaps\n\n### Schema & Structured Data\n- Current implementation\n- Validation errors\n- Missing opportunities\n\n### Performance\n- LCP, INP, CLS scores\n- Resource optimization needs\n- Third-party script impact\n\n### Images\n- Missing alt text\n- Oversized images\n- Format recommendations\n\n### AI Search Readiness\n- Citability score\n- Structural improvements\n- Authority signals\n\n## Priority Definitions\n\n- **Critical**: Blocks indexing or causes penalties (fix immediately)\n- **High**: Significantly impacts rankings (fix within 1 week)\n- **Medium**: Optimization opportunity (fix within 1 month)\n- **Low**: Nice to have (backlog)\n\n## DataForSEO Integration (Optional)\n\nIf DataForSEO MCP tools are available, spawn the `seo-dataforseo` agent alongside existing subagents to enrich the audit with live data: real SERP positions, backlink profiles with spam scores, on-page analysis (Lighthouse), business listings, and AI visibility checks (ChatGPT scraper, LLM mentions).\n\n## Google API Integration (Optional)\n\nIf Google API credentials are configured (`\u002Fhome\u002Fnoirelab\u002F.config\u002Fopencode\u002Fskills\u002Fseo\u002Fbin\u002Fclaude-seo run google_auth.py --check`), spawn the `seo-google` agent to enrich the audit with real Google field data: CrUX Core Web Vitals (replaces lab-only estimates), GSC URL indexation status, search performance (clicks, impressions, CTR), and GA4 organic traffic trends. The Performance (CWV) category score benefits most from field data.\n\n## Error Handling\n\n| Scenario | Action |\n|----------|--------|\n| URL unreachable (DNS failure, connection refused) | Report the error clearly. Do not guess site content. Suggest the user verify the URL and try again. |\n| robots.txt blocks crawling | Report which paths are blocked. Analyze only accessible pages and note the limitation in the report. |\n| Rate limiting (429 responses) | Back off and reduce concurrent requests. Report partial results with a note on which sections could not be completed. |\n| Timeout on large sites (500+ pages) | Cap the crawl at the timeout limit. Report findings for pages crawled and estimate total site scope. |\n",{"name":5,"license":15,"metadata":60,"description":7,"argument-hint":63,"user-invocable":64},{"author":61,"version":62,"category":32},"AgriciDaniel","2.2.4","[url]",true,"main","d8378e461d60315bd1ca8a6e71716df39b6abe4a","configs\u002Fcommon\u002Fopencode\u002Fskills\u002Fseo-audit","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup","https:\u002F\u002Fgithub.com\u002Fnoirelab","Artificial Intelligence Researcher |\r\nComputer Science majoring at UTFPR","2026-11-11 09:12:51",{"source":8,"skillName":5,"commands":73,"prompt":83,"zipAvailable":64},[74,77,80],{"tool":75,"command":76},"npx","npx skills add noirelab\u002Flinux-setup --skill seo-audit",{"tool":78,"command":79},"bunx","bunx skills add noirelab\u002Flinux-setup --skill seo-audit",{"tool":81,"command":82},"pnpm","pnpm dlx skills add noirelab\u002Flinux-setup --skill seo-audit","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fopencode\u002Fskills\u002Fseo-audit\u002FSKILL.md",[85,91,95,99,103,107,111,115],{"path":86,"resourceType":87,"resourceTypeDesc":88,"sizeBytes":89,"sourceHtmlUrl":90},"evals\u002Fbenchmark.json","REFERENCE","参考文档",20175,"https:\u002F\u002Fgithub.com\u002Fatomicinnovation\u002Faccelerator\u002Fblob\u002Fmain\u002Fskills\u002Fwork\u002Fextract-work-items\u002Fevals\u002Fbenchmark.json",{"path":92,"resourceType":87,"resourceTypeDesc":88,"sizeBytes":93,"sourceHtmlUrl":94},"evals\u002Fevals.json",27011,"https:\u002F\u002Fgithub.com\u002Fatomicinnovation\u002Faccelerator\u002Fblob\u002Fmain\u002Fskills\u002Fwork\u002Fextract-work-items\u002Fevals\u002Fevals.json",{"path":96,"resourceType":87,"resourceTypeDesc":88,"sizeBytes":97,"sourceHtmlUrl":98},"evals\u002Ffixtures\u002Fmixed-project-batch.md",879,"https:\u002F\u002Fgithub.com\u002Fatomicinnovation\u002Faccelerator\u002Fblob\u002Fmain\u002Fskills\u002Fwork\u002Fextract-work-items\u002Fevals\u002Ffixtures\u002Fmixed-project-batch.md",{"path":100,"resourceType":87,"resourceTypeDesc":88,"sizeBytes":101,"sourceHtmlUrl":102},"evals\u002Ffixtures\u002Fmixed-requirements.md",2448,"https:\u002F\u002Fgithub.com\u002Fatomicinnovation\u002Faccelerator\u002Fblob\u002Fmain\u002Fskills\u002Fwork\u002Fextract-work-items\u002Fevals\u002Ffixtures\u002Fmixed-requirements.md",{"path":104,"resourceType":87,"resourceTypeDesc":88,"sizeBytes":105,"sourceHtmlUrl":106},"evals\u002Ffixtures\u002Fsimple-story.md",440,"https:\u002F\u002Fgithub.com\u002Fatomicinnovation\u002Faccelerator\u002Fblob\u002Fmain\u002Fskills\u002Fwork\u002Fextract-work-items\u002Fevals\u002Ffixtures\u002Fsimple-story.md",{"path":108,"resourceType":87,"resourceTypeDesc":88,"sizeBytes":109,"sourceHtmlUrl":110},"evals\u002Ffixtures\u002Fsparse-feature.md",146,"https:\u002F\u002Fgithub.com\u002Fatomicinnovation\u002Faccelerator\u002Fblob\u002Fmain\u002Fskills\u002Fwork\u002Fextract-work-items\u002Fevals\u002Ffixtures\u002Fsparse-feature.md",{"path":112,"resourceType":87,"resourceTypeDesc":88,"sizeBytes":113,"sourceHtmlUrl":114},"evals\u002Ffixtures\u002Fstructural-content.md",906,"https:\u002F\u002Fgithub.com\u002Fatomicinnovation\u002Faccelerator\u002Fblob\u002Fmain\u002Fskills\u002Fwork\u002Fextract-work-items\u002Fevals\u002Ffixtures\u002Fstructural-content.md",{"path":116,"resourceType":117,"resourceTypeDesc":118,"sizeBytes":119,"sourceHtmlUrl":16},"LICENSE.txt","LICENSE","许可证",143,[121,152,187,212,232,248],{"skillNo":122,"name":123,"nameZh":6,"description":124,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":125,"licenseFileUrl":126,"sourceHtmlUrl":127,"categories":128,"keywords":132,"publishedAt":55},"01M6C2Q1S6HCS7Y9TBQ2PJ2NAM","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.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fclaude\u002Fskills\u002Fsynced\u002Ffcfa9261-0073-49cb-8312-19eea68f0c58_391f3767-a35d-4280-81a1-363cd861a8e6\u002Fskill-creator\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fclaude\u002Fskills\u002Fsynced\u002Ffcfa9261-0073-49cb-8312-19eea68f0c58_391f3767-a35d-4280-81a1-363cd861a8e6\u002Fskill-creator\u002FSKILL.md",[129],{"categoryNo":130,"categoryName":131,"taxonomyType":22,"taxonomyTypeDesc":23},"01JBSEEDCAT000000000000023","Skill与智能体开发",[133,134,135,136,137,138,139,140,141,142,143,144,44,145,146,147,148,149,150,34,151],"skill creator","creator","performance","run evals","test","variance analysis","create","run","benchmark","analysis","improve","edit","evals","optimize","existing skill","for","accuracy","scratch","new",{"skillNo":153,"name":154,"nameZh":6,"description":155,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":125,"licenseFileUrl":6,"sourceHtmlUrl":156,"categories":157,"keywords":158,"publishedAt":55},"01M6C2ZRGJ9HN4N9BP24DPNCR4","returns-reverse-logistics","Codified expertise for returns authorization, receipt and inspection, disposition decisions, refund processing, fraud detection, and warranty claims management. Informed by returns operations managers with 15+ years experience. Includes grading frameworks, disposition economics, fraud pattern recognition, and vendor recovery processes. Use when handling product returns, reverse logistics, refund decisions, return fraud detection, or warranty claims.","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fopencode_home\u002Fskills\u002Freturns-reverse-logistics\u002FSKILL.md",[],[159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,44,175,176,177,178,179,180,181,182,183,148,184,185,34,186],"returns","returns reverse logistics","reverse logistics","reverse","github","code","product","https","authorization","detection","fraud","recovery","decisions","management","operations","vendor","claims management","frameworks","fraud detection","pattern","grading","processing","economics","managers","claims","expertise","refund","inspection",{"skillNo":188,"name":189,"nameZh":6,"description":190,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":125,"licenseFileUrl":6,"sourceHtmlUrl":191,"categories":192,"keywords":193,"publishedAt":55},"01M6C2ZGWSNZGZZQ5VCFWHD2QT","quality-nonconformance","Codified expertise for quality control, non-conformance investigation, root cause analysis, corrective action, and supplier quality management in regulated manufacturing. Informed by quality engineers with 15+ years experience across FDA, IATF 16949, and AS9100 environments. Includes NCR lifecycle management, CAPA systems, SPC interpretation, and audit methodology. Use when investigating non-conformances, performing root cause analysis, managing CAPAs, interpreting SPC data, or handling supplier quality issues.","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fopencode_home\u002Fskills\u002Fquality-nonconformance\u002FSKILL.md",[],[194,195,163,196,197,164,198,166,30,199,200,201,142,202,172,44,203,204,205,206,207,208,209,210,148,184,211,34],"quality","quality nonconformance","root cause analysis","interpretation","issues","data","methodology","lifecycle","investigation","fda","across","manufacturing","environments","corrective action","supplier quality management","action","conformance","root cause",{"skillNo":213,"name":214,"nameZh":6,"description":215,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":125,"licenseFileUrl":6,"sourceHtmlUrl":216,"categories":217,"keywords":218,"publishedAt":55},"01M6C2Z8VQ9AYZYKPZW1KD9DX5","production-scheduling","Codified expertise for production scheduling, job sequencing, line balancing, changeover optimization, and bottleneck resolution in discrete and batch manufacturing. Informed by production schedulers with 15+ years experience. Includes TOC\u002Fdrum-buffer-rope, SMED, OEE analysis, disruption response frameworks, and ERP\u002FMES interaction patterns. Use when scheduling production, resolving bottlenecks, optimizing changeovers, responding to disruptions, or balancing manufacturing lines.","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fopencode_home\u002Fskills\u002Fproduction-scheduling\u002FSKILL.md",[],[219,220,221,163,164,222,166,223,142,224,225,44,226,227,176,228,229,230,205,231,148,184,34],"Production","production scheduling","scheduling","batch","Optimization","erp","bottleneck","toc","patterns","line","interaction","sequencing","buffer",{"skillNo":233,"name":234,"nameZh":6,"description":235,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":125,"licenseFileUrl":6,"sourceHtmlUrl":236,"categories":237,"keywords":238,"publishedAt":55},"01M6C2YR01NNN2Z1G18RN7F9MP","logistics-exception-management","Codified expertise for handling freight exceptions, shipment delays, damages, losses, and carrier disputes. Informed by logistics professionals with 15+ years operational experience. Includes escalation protocols, carrier-specific behaviors, claims procedures, and judgment frameworks. Use when handling shipping exceptions, freight claims, delivery issues, or carrier disputes.","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fopencode_home\u002Fskills\u002Flogistics-exception-management\u002FSKILL.md",[],[172,239,163,164,240,198,241,166,242,44,176,243,244,245,246,183,148,184,247,34],"logistics exception management","shipping","protocols","escalation","delivery","claude-code","judgment","with","freight",{"skillNo":249,"name":250,"nameZh":6,"description":251,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":125,"licenseFileUrl":6,"sourceHtmlUrl":252,"categories":253,"keywords":254,"publishedAt":55},"01M6C2YC5PXTEJYBJJQZVXPQS0","inventory-demand-planning","Codified expertise for demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation at multi-location retailers. Informed by demand planners with 15+ years experience managing hundreds of SKUs. Includes forecasting method selection, ABC\u002FXYZ analysis, seasonal transition management, and vendor negotiation frameworks. Use when forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory levels.","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fopencode_home\u002Fskills\u002Finventory-demand-planning\u002FSKILL.md",[],[255,256,257,258,163,164,166,259,223,260,142,172,174,261,44,262,176,263,264,265,266,267,148,184,268,34],"planning","inventory","inventory demand planning","demand planning","negotiation","Safety","forecasting","selection","estimation","stock","seasonal","lift","at","transition"]