[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6C2N4A2CK1CPH4BJAHZHSN7":3,"skill-same:01M6C2N4A2CK1CPH4BJAHZHSN7":106},{"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":56,"linkOnly":57,"markdownContent":58,"markdownBody":59,"frontMatter":60,"refName":67,"commitSha":68,"skillDirectory":69,"forksCount":14,"repositoryHtmlUrl":70,"repositoryHomepageUrl":6,"ownerHtmlUrl":71,"ownerBlogUrl":6,"ownerDescription":72,"updatedAt":73,"install":74,"resources":86},"01M6C2N4A2CK1CPH4BJAHZHSN7","seo-programmatic",null,"Programmatic SEO planning and analysis for pages generated at scale from data sources. Covers template engines, URL patterns, internal linking automation, thin content safeguards, and index bloat prevention. Use when user says \"programmatic SEO\", \"pages at scale\", \"dynamic pages\", \"template pages\", \"generated pages\", or \"data-driven SEO\".","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\u002Fclaude\u002Fskills\u002Fseo-programmatic\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fclaude\u002Fskills\u002Fseo-programmatic\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",[30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55],"seo","programmatic","seo programmatic","use","when","data sources","data-driven","linking","bloat","at","URL","sources","seo planning","patterns","automation","generated","user","template","plan","analysis","prevention","programmatic seo","data","content","index","planning","2026-11-10 10:12:30",false,"---\nname: seo-programmatic\ndescription: >\n  Programmatic SEO planning and analysis for pages generated at scale from data\n  sources. Covers template engines, URL patterns, internal linking automation,\n  thin content safeguards, and index bloat prevention. Use when user says\n  \"programmatic SEO\", \"pages at scale\", \"dynamic pages\", \"template pages\",\n  \"generated pages\", or \"data-driven SEO\".\nuser-invocable: true\nargument-hint: \"[url or plan]\"\nlicense: MIT\nmetadata:\n  author: AgriciDaniel\n  version: \"2.2.4\"\n  category: seo\n---\n\n# Programmatic SEO Analysis & Planning\n\nBuild and audit SEO pages generated at scale from structured data sources.\nEnforces quality gates to prevent thin content penalties and index bloat.\n\n## Data Source Assessment\n\nEvaluate the data powering programmatic pages:\n- **CSV\u002FJSON files**: Row count, column uniqueness, missing values\n- **API endpoints**: Response structure, data freshness, rate limits\n- **Database queries**: Record count, field completeness, update frequency\n- Data quality checks:\n  - Each record must have enough unique attributes to generate distinct content\n  - Flag duplicate or near-duplicate records (>80% field overlap)\n  - Verify data freshness; stale data produces stale pages\n\n## Template Engine Planning\n\nDesign templates that produce unique, valuable pages:\n- **Variable injection points**: Title, H1, body sections, meta description, schema\n- **Content blocks**: Static (shared across pages) vs dynamic (unique per page)\n- **Conditional logic**: Show\u002Fhide sections based on data availability\n- **Supplementary content**: Related items, contextual tips, user-generated content\n- Template review checklist:\n  - Each page must read as a standalone, valuable resource\n  - No \"mad-libs\" patterns (just swapping city\u002Fproduct names in identical text)\n  - Dynamic sections must add genuine information, not just keyword variations\n\n## URL Pattern Strategy\n\n### Common Patterns\n- `\u002Ftools\u002F[tool-name]`: Tool\u002Fproduct directory pages\n- `\u002F[city]\u002F[service]`: Location + service pages\n- `\u002Fintegrations\u002F[platform]`: Integration landing pages\n- `\u002Fglossary\u002F[term]`: Definition\u002Freference pages\n- `\u002Ftemplates\u002F[template-name]`: Downloadable template pages\n\n### URL Rules\n- Lowercase, hyphenated slugs derived from data\n- Logical hierarchy reflecting site architecture\n- No duplicate slugs; enforce uniqueness at generation time\n- Keep URLs under 100 characters\n- No query parameters for primary content URLs\n- Consistent trailing slash usage (match existing site pattern)\n\n## Internal Linking Automation\n\n- **Hub\u002Fspoke model**: Category hub pages linking to individual programmatic pages\n- **Related items**: Auto-link to 3-5 related pages based on data attributes\n- **Breadcrumbs**: Generate BreadcrumbList schema from URL hierarchy\n- **Cross-linking**: Link between programmatic pages sharing attributes (same category, same city, same feature)\n- **Anchor text**: Use descriptive, varied anchor text. Avoid exact-match keyword repetition\n- Link density: 3-5 internal links per 1000 words (match seo-content guidelines)\n\n## Thin Content Safeguards\n\n### Quality Gates\n\n| Metric | Threshold | Action |\n|--------|-----------|--------|\n| Pages without content review | 100+ | ⚠️ WARNING: require content audit before publishing |\n| Pages without justification | 500+ | ? HARD STOP: require explicit user approval and thin content audit |\n| Unique content per page | \u003C40% | ❌ Flag as thin content (likely penalty risk) |\n| Word count per page | \u003C300 | ⚠️ Flag for review (may lack sufficient value) |\n\n### Scaled Content Abuse: Enforcement Context (2025-2026)\n\nGoogle's Scaled Content Abuse policy (introduced March 2024) saw major enforcement escalation in 2025:\n\n- **June 2025:** Wave of manual actions targeting websites with AI-generated content at scale\n- **August 2025:** Third-party\u002FSEO-community reporting described stronger SpamBrain detection for AI-generated link schemes and content farms\n- **Result:** Google reported 45% reduction in low-quality, unoriginal content in search results post-March 2024 enforcement\n\n**Enhanced quality gates for programmatic pages:**\n- **Content differentiation:** ≥30-40% of content must be genuinely unique between any two programmatic pages (not just city\u002Fkeyword string replacement)\n- **Human review:** Minimum 5-10% sample review of generated pages before publishing\n- **Progressive rollout:** Publish in batches of 50-100 pages. Monitor indexing and rankings for 2-4 weeks before expanding. Never publish 500+ programmatic pages simultaneously without explicit quality review.\n- **Standalone value test:** Each page should pass: \"Would this page be worth publishing even if no other similar pages existed?\"\n- **Site reputation abuse:** Google clarified site reputation abuse language on 2024-11-19; treat third-party\u002Fhosted programmatic content as a policy risk.\n\n> **Recommendation:** The WARNING gate at `\u003C40% unique content` remains appropriate. Consider a HARD STOP at `\u003C30%` unique content to prevent scaled content abuse risk.\n\n### Safe Programmatic Pages (OK at scale)\n✅ Integration pages (with real setup docs, API details, screenshots)\n✅ Template\u002Ftool pages (with downloadable content, usage instructions)\n✅ Glossary pages (200+ word definitions with examples, related terms)\n✅ Product pages (unique specs, reviews, comparison data)\n✅ Data-driven pages (unique statistics, charts, analysis per record)\n\n### Penalty Risk (avoid at scale)\n❌ Location pages with only city name swapped in identical text\n❌ \"Best [tool] for [industry]\" without industry-specific value\n❌ \"[Competitor] alternative\" without real comparison data\n❌ AI-generated pages without human review and unique value-add\n❌ Pages where >60% of content is shared template boilerplate\n\n### Uniqueness Calculation\nUnique content % = (words unique to this page) \u002F (total words on page) × 100\n\nMeasure against all other pages in the programmatic set. Shared headers, footers, and navigation are excluded from the calculation. Template boilerplate text IS included.\n\n## Canonical Strategy\n\n- Every programmatic page must have a self-referencing canonical tag\n- Parameter variations (sort, filter) canonical to the base URL when duplicate or low-value\n- Paginated series: use self-canonical paginated pages when content differs; keep crawlable links\n- If programmatic pages overlap with manual pages, the manual page is canonical\n- No canonical to a different domain unless intentional cross-domain setup\n\n## Sitemap Integration\n\n- Auto-generate sitemap entries for all programmatic pages\n- Split at 50,000 URLs or 50MB uncompressed per sitemap file, whichever comes first (protocol limit)\n- Use sitemap index if multiple sitemap files needed\n- `\u003Clastmod>` reflects actual data update timestamp (not generation time)\n- Exclude noindexed programmatic pages from sitemap\n- Register sitemap in robots.txt\n- Update sitemap dynamically as new records are added to data source\n\n## Index Bloat Prevention\n\n- **Noindex low-value pages**: Pages that don't meet quality gates\n- **Pagination**: Reserve noindex\u002Fcanonical consolidation for true duplicates or low-value filtered views\n- **Faceted navigation**: Reserve noindex\u002Fcanonical to base category for true duplicates or low-value filtered views\n- **Crawl budget**: For sites with >10k programmatic pages, monitor crawl stats in Search Console\n- **Thin page consolidation**: Merge records with insufficient data into aggregated pages\n- **Regular audits**: Monthly review of indexed page count vs intended count\n\n## Output\n\n### Programmatic SEO Score: XX\u002F100\n\n### Assessment Summary\n| Category | Status | Score |\n|----------|--------|-------|\n| Data Quality | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n| Template Uniqueness | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n| URL Structure | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n| Internal Linking | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n| Thin Content Risk | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n| Index Management | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n\n### Critical Issues (fix immediately)\n### High Priority (fix within 1 week)\n### Medium Priority (fix within 1 month)\n### Low Priority (backlog)\n\n### Recommendations\n- Data source improvements\n- Template modifications\n- URL pattern adjustments\n- Quality gate compliance actions\n\n## Error Handling\n\n| Scenario | Action |\n|----------|--------|\n| URL unreachable | Report connection error with status code. Suggest verifying URL accessibility and checking for authentication requirements. |\n| No programmatic pages detected | Inform user that no template-generated or data-driven page patterns were found. Suggest checking if pages use client-side rendering or if the URL points to the correct section. |\n| Thin content threshold exceeded | Trigger quality gate warning. Report the unique content percentage and flag pages below 40% uniqueness. Require user acknowledgment before proceeding. |\n| Quality gate violation | Halt analysis at the HARD STOP threshold (500+ pages without justification or \u003C30% unique content). Present findings and require explicit user approval to continue. |\n","# Programmatic SEO Analysis & Planning\n\nBuild and audit SEO pages generated at scale from structured data sources.\nEnforces quality gates to prevent thin content penalties and index bloat.\n\n## Data Source Assessment\n\nEvaluate the data powering programmatic pages:\n- **CSV\u002FJSON files**: Row count, column uniqueness, missing values\n- **API endpoints**: Response structure, data freshness, rate limits\n- **Database queries**: Record count, field completeness, update frequency\n- Data quality checks:\n  - Each record must have enough unique attributes to generate distinct content\n  - Flag duplicate or near-duplicate records (>80% field overlap)\n  - Verify data freshness; stale data produces stale pages\n\n## Template Engine Planning\n\nDesign templates that produce unique, valuable pages:\n- **Variable injection points**: Title, H1, body sections, meta description, schema\n- **Content blocks**: Static (shared across pages) vs dynamic (unique per page)\n- **Conditional logic**: Show\u002Fhide sections based on data availability\n- **Supplementary content**: Related items, contextual tips, user-generated content\n- Template review checklist:\n  - Each page must read as a standalone, valuable resource\n  - No \"mad-libs\" patterns (just swapping city\u002Fproduct names in identical text)\n  - Dynamic sections must add genuine information, not just keyword variations\n\n## URL Pattern Strategy\n\n### Common Patterns\n- `\u002Ftools\u002F[tool-name]`: Tool\u002Fproduct directory pages\n- `\u002F[city]\u002F[service]`: Location + service pages\n- `\u002Fintegrations\u002F[platform]`: Integration landing pages\n- `\u002Fglossary\u002F[term]`: Definition\u002Freference pages\n- `\u002Ftemplates\u002F[template-name]`: Downloadable template pages\n\n### URL Rules\n- Lowercase, hyphenated slugs derived from data\n- Logical hierarchy reflecting site architecture\n- No duplicate slugs; enforce uniqueness at generation time\n- Keep URLs under 100 characters\n- No query parameters for primary content URLs\n- Consistent trailing slash usage (match existing site pattern)\n\n## Internal Linking Automation\n\n- **Hub\u002Fspoke model**: Category hub pages linking to individual programmatic pages\n- **Related items**: Auto-link to 3-5 related pages based on data attributes\n- **Breadcrumbs**: Generate BreadcrumbList schema from URL hierarchy\n- **Cross-linking**: Link between programmatic pages sharing attributes (same category, same city, same feature)\n- **Anchor text**: Use descriptive, varied anchor text. Avoid exact-match keyword repetition\n- Link density: 3-5 internal links per 1000 words (match seo-content guidelines)\n\n## Thin Content Safeguards\n\n### Quality Gates\n\n| Metric | Threshold | Action |\n|--------|-----------|--------|\n| Pages without content review | 100+ | ⚠️ WARNING: require content audit before publishing |\n| Pages without justification | 500+ | ? HARD STOP: require explicit user approval and thin content audit |\n| Unique content per page | \u003C40% | ❌ Flag as thin content (likely penalty risk) |\n| Word count per page | \u003C300 | ⚠️ Flag for review (may lack sufficient value) |\n\n### Scaled Content Abuse: Enforcement Context (2025-2026)\n\nGoogle's Scaled Content Abuse policy (introduced March 2024) saw major enforcement escalation in 2025:\n\n- **June 2025:** Wave of manual actions targeting websites with AI-generated content at scale\n- **August 2025:** Third-party\u002FSEO-community reporting described stronger SpamBrain detection for AI-generated link schemes and content farms\n- **Result:** Google reported 45% reduction in low-quality, unoriginal content in search results post-March 2024 enforcement\n\n**Enhanced quality gates for programmatic pages:**\n- **Content differentiation:** ≥30-40% of content must be genuinely unique between any two programmatic pages (not just city\u002Fkeyword string replacement)\n- **Human review:** Minimum 5-10% sample review of generated pages before publishing\n- **Progressive rollout:** Publish in batches of 50-100 pages. Monitor indexing and rankings for 2-4 weeks before expanding. Never publish 500+ programmatic pages simultaneously without explicit quality review.\n- **Standalone value test:** Each page should pass: \"Would this page be worth publishing even if no other similar pages existed?\"\n- **Site reputation abuse:** Google clarified site reputation abuse language on 2024-11-19; treat third-party\u002Fhosted programmatic content as a policy risk.\n\n> **Recommendation:** The WARNING gate at `\u003C40% unique content` remains appropriate. Consider a HARD STOP at `\u003C30%` unique content to prevent scaled content abuse risk.\n\n### Safe Programmatic Pages (OK at scale)\n✅ Integration pages (with real setup docs, API details, screenshots)\n✅ Template\u002Ftool pages (with downloadable content, usage instructions)\n✅ Glossary pages (200+ word definitions with examples, related terms)\n✅ Product pages (unique specs, reviews, comparison data)\n✅ Data-driven pages (unique statistics, charts, analysis per record)\n\n### Penalty Risk (avoid at scale)\n❌ Location pages with only city name swapped in identical text\n❌ \"Best [tool] for [industry]\" without industry-specific value\n❌ \"[Competitor] alternative\" without real comparison data\n❌ AI-generated pages without human review and unique value-add\n❌ Pages where >60% of content is shared template boilerplate\n\n### Uniqueness Calculation\nUnique content % = (words unique to this page) \u002F (total words on page) × 100\n\nMeasure against all other pages in the programmatic set. Shared headers, footers, and navigation are excluded from the calculation. Template boilerplate text IS included.\n\n## Canonical Strategy\n\n- Every programmatic page must have a self-referencing canonical tag\n- Parameter variations (sort, filter) canonical to the base URL when duplicate or low-value\n- Paginated series: use self-canonical paginated pages when content differs; keep crawlable links\n- If programmatic pages overlap with manual pages, the manual page is canonical\n- No canonical to a different domain unless intentional cross-domain setup\n\n## Sitemap Integration\n\n- Auto-generate sitemap entries for all programmatic pages\n- Split at 50,000 URLs or 50MB uncompressed per sitemap file, whichever comes first (protocol limit)\n- Use sitemap index if multiple sitemap files needed\n- `\u003Clastmod>` reflects actual data update timestamp (not generation time)\n- Exclude noindexed programmatic pages from sitemap\n- Register sitemap in robots.txt\n- Update sitemap dynamically as new records are added to data source\n\n## Index Bloat Prevention\n\n- **Noindex low-value pages**: Pages that don't meet quality gates\n- **Pagination**: Reserve noindex\u002Fcanonical consolidation for true duplicates or low-value filtered views\n- **Faceted navigation**: Reserve noindex\u002Fcanonical to base category for true duplicates or low-value filtered views\n- **Crawl budget**: For sites with >10k programmatic pages, monitor crawl stats in Search Console\n- **Thin page consolidation**: Merge records with insufficient data into aggregated pages\n- **Regular audits**: Monthly review of indexed page count vs intended count\n\n## Output\n\n### Programmatic SEO Score: XX\u002F100\n\n### Assessment Summary\n| Category | Status | Score |\n|----------|--------|-------|\n| Data Quality | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n| Template Uniqueness | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n| URL Structure | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n| Internal Linking | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n| Thin Content Risk | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n| Index Management | ✅\u002F⚠️\u002F❌ | XX\u002F100 |\n\n### Critical Issues (fix immediately)\n### High Priority (fix within 1 week)\n### Medium Priority (fix within 1 month)\n### Low Priority (backlog)\n\n### Recommendations\n- Data source improvements\n- Template modifications\n- URL pattern adjustments\n- Quality gate compliance actions\n\n## Error Handling\n\n| Scenario | Action |\n|----------|--------|\n| URL unreachable | Report connection error with status code. Suggest verifying URL accessibility and checking for authentication requirements. |\n| No programmatic pages detected | Inform user that no template-generated or data-driven page patterns were found. Suggest checking if pages use client-side rendering or if the URL points to the correct section. |\n| Thin content threshold exceeded | Trigger quality gate warning. Report the unique content percentage and flag pages below 40% uniqueness. Require user acknowledgment before proceeding. |\n| Quality gate violation | Halt analysis at the HARD STOP threshold (500+ pages without justification or \u003C30% unique content). Present findings and require explicit user approval to continue. |\n",{"name":5,"license":15,"metadata":61,"description":64,"argument-hint":65,"user-invocable":66},{"author":62,"version":63,"category":30},"AgriciDaniel","2.2.4","Programmatic SEO planning and analysis for pages generated at scale from data sources. Covers template engines, URL patterns, internal linking automation, thin content safeguards, and index bloat prevention. Use when user says \"programmatic SEO\", \"pages at scale\", \"dynamic pages\", \"template pages\", \"generated pages\", or \"data-driven SEO\".\n","[url or plan]",true,"main","d8378e461d60315bd1ca8a6e71716df39b6abe4a","configs\u002Fcommon\u002Fclaude\u002Fskills\u002Fseo-programmatic","https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup","https:\u002F\u002Fgithub.com\u002Fnoirelab","Artificial Intelligence Researcher |\r\nComputer Science majoring at UTFPR","2026-11-14 00:24:00",{"source":8,"skillName":5,"commands":75,"prompt":85,"zipAvailable":66},[76,79,82],{"tool":77,"command":78},"npx","npx skills add noirelab\u002Flinux-setup --skill seo-programmatic",{"tool":80,"command":81},"bunx","bunx skills add noirelab\u002Flinux-setup --skill seo-programmatic",{"tool":83,"command":84},"pnpm","pnpm dlx skills add noirelab\u002Flinux-setup --skill seo-programmatic","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fnoirelab\u002Flinux-setup\u002Fblob\u002Fmain\u002Fconfigs\u002Fcommon\u002Fclaude\u002Fskills\u002Fseo-programmatic\u002FSKILL.md",[87,92,98,102],{"path":88,"resourceType":89,"resourceTypeDesc":90,"sizeBytes":91,"sourceHtmlUrl":16},"LICENSE.txt","LICENSE","许可证",143,{"path":93,"resourceType":94,"resourceTypeDesc":95,"sizeBytes":96,"sourceHtmlUrl":97},"manifest.json","REFERENCE","参考文档",101,"https:\u002F\u002Fgithub.com\u002Fmanagedcode\u002Fdotnet-skills\u002Fblob\u002Fmain\u002Fcatalog\u002FFrameworks\u002FBlazor\u002Fskills\u002Fblazor\u002Fmanifest.json",{"path":99,"resourceType":94,"resourceTypeDesc":95,"sizeBytes":100,"sourceHtmlUrl":101},"references\u002Fanti-patterns.md",13859,"https:\u002F\u002Fgithub.com\u002Fmanagedcode\u002Fdotnet-skills\u002Fblob\u002Fmain\u002Fcatalog\u002FFrameworks\u002FBlazor\u002Fskills\u002Fblazor\u002Freferences\u002Fanti-patterns.md",{"path":103,"resourceType":94,"resourceTypeDesc":95,"sizeBytes":104,"sourceHtmlUrl":105},"references\u002Fpatterns.md",15972,"https:\u002F\u002Fgithub.com\u002Fmanagedcode\u002Fdotnet-skills\u002Fblob\u002Fmain\u002Fcatalog\u002FFrameworks\u002FBlazor\u002Fskills\u002Fblazor\u002Freferences\u002Fpatterns.md",[107,137,172,197,216,232],{"skillNo":108,"name":109,"nameZh":6,"description":110,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":111,"licenseFileUrl":112,"sourceHtmlUrl":113,"categories":114,"keywords":118,"publishedAt":56},"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",[115],{"categoryNo":116,"categoryName":117,"taxonomyType":22,"taxonomyTypeDesc":23},"01JBSEEDCAT000000000000023","Skill与智能体开发",[119,120,121,122,123,124,125,126,127,49,128,129,33,130,131,132,133,134,135,34,136],"skill creator","creator","performance","run evals","test","variance analysis","create","run","benchmark","improve","edit","evals","optimize","existing skill","for","accuracy","scratch","new",{"skillNo":138,"name":139,"nameZh":6,"description":140,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":111,"licenseFileUrl":6,"sourceHtmlUrl":141,"categories":142,"keywords":143,"publishedAt":56},"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",[],[144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,33,160,161,162,163,164,165,166,167,168,133,169,170,34,171],"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":173,"name":174,"nameZh":6,"description":175,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":111,"licenseFileUrl":6,"sourceHtmlUrl":176,"categories":177,"keywords":178,"publishedAt":56},"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",[],[179,180,148,181,182,149,183,151,184,52,185,186,49,187,157,33,188,189,190,191,192,193,194,195,133,169,196,34],"quality","quality nonconformance","root cause analysis","interpretation","issues","audit","methodology","lifecycle","investigation","fda","across","manufacturing","environments","corrective action","supplier quality management","action","conformance","root cause",{"skillNo":198,"name":199,"nameZh":6,"description":200,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":111,"licenseFileUrl":6,"sourceHtmlUrl":201,"categories":202,"keywords":203,"publishedAt":56},"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",[],[204,205,206,148,149,207,151,208,49,209,210,33,211,43,161,212,213,214,190,215,133,169,34],"Production","production scheduling","scheduling","batch","Optimization","erp","bottleneck","toc","line","interaction","sequencing","buffer",{"skillNo":217,"name":218,"nameZh":6,"description":219,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":111,"licenseFileUrl":6,"sourceHtmlUrl":220,"categories":221,"keywords":222,"publishedAt":56},"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",[],[157,223,148,149,224,183,225,151,226,33,161,227,228,229,230,168,133,169,231,34],"logistics exception management","shipping","protocols","escalation","delivery","claude-code","judgment","with","freight",{"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":111,"licenseFileUrl":6,"sourceHtmlUrl":236,"categories":237,"keywords":238,"publishedAt":56},"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",[],[55,239,240,241,148,149,151,242,208,243,49,157,159,244,33,245,161,246,247,248,249,39,133,169,250,34],"inventory","inventory demand planning","demand planning","negotiation","Safety","forecasting","selection","estimation","stock","seasonal","lift","transition"]