[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6C2MJ305VB9XJA616QVJDB1":3,"skill-same:01M6C2MJ305VB9XJA616QVJDB1":134},{"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":38,"publishedAt":68,"linkOnly":69,"markdownContent":70,"markdownBody":71,"frontMatter":72,"refName":79,"commitSha":80,"skillDirectory":81,"forksCount":14,"repositoryHtmlUrl":82,"repositoryHomepageUrl":6,"ownerHtmlUrl":83,"ownerBlogUrl":6,"ownerDescription":84,"updatedAt":85,"install":86,"resources":98},"01M6C2MJ305VB9XJA616QVJDB1","seo-image-gen",null,"AI image generation for SEO assets: OG\u002Fsocial preview images, blog hero images, schema images, product photography, infographics. Powered by Gemini via nanobanana-mcp. Requires banana extension installed. Use when user says \"generate image\", \"OG image\", \"social preview\", \"hero image\", \"blog image\", \"product photo\", \"infographic\", \"seo image\", \"create visual\", \"image-gen\", \"favicon\", \"schema image\", \"pinterest pin\", \"generate visual\", \"banner\", or \"thumbnail\".","noirelab\u002Flinux-setup","noirelab","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F142925921?v=4","01M6C29R3FEDGFAXAT0KXY28QX","Kaíque M. 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Powered by Gemini via nanobanana-mcp. Requires banana extension installed. Use when user says \\\"generate image\\\", \\\"OG image\\\", \\\"social preview\\\", \\\"hero image\\\", \\\"blog image\\\", \\\"product photo\\\", \\\"infographic\\\", \\\"seo image\\\", \\\"create visual\\\", \\\"image-gen\\\", \\\"favicon\\\", \\\"schema image\\\", \\\"pinterest pin\\\", \\\"generate visual\\\", \\\"banner\\\", or \\\"thumbnail\\\".\"\nargument-hint: \"[og|hero|product|infographic|custom|batch] \u003Cdescription>\"\nuser-invocable: true\nlicense: MIT\ncompatibility: \"Requires nanobanana MCP server\"\nmetadata:\n  author: AgriciDaniel\n  version: \"2.2.4\"\n  category: seo\n---\n\n# SEO Image Gen: AI Image Generation for SEO Assets (Extension)\n\nGenerate production-ready images for SEO use cases using Gemini's image generation\nvia the banana Creative Director pipeline. Maps SEO needs to optimized domain modes,\naspect ratios, and resolution defaults.\n\n## Architecture Note\n\nThis extension is built on [Claude Banana](https:\u002F\u002Fgithub.com\u002FAgriciDaniel\u002Fbanana-claude),\nthe standalone AI image generation skill for Claude Code.\n\nThis skill has two components with distinct roles:\n- **SKILL.md** (this file): Handles interactive `\u002Fseo image-gen` commands for generating images\n- **Agent** (`agents\u002Fseo-image-gen.md`): Audit-only analyst spawned during `\u002Fseo audit` to assess existing OG\u002Fsocial images and produce a generation plan (never auto-generates)\n\n## Prerequisites\n\nThis skill requires the banana extension to be installed:\n```bash\n.\u002Fextensions\u002Fbanana\u002Finstall.sh\n```\n\n**Check availability:** Before using any image generation tool, verify the MCP server\nis connected by checking if `gemini_generate_image` or `set_aspect_ratio` tools are\navailable. If tools are not available, inform the user the extension is not installed\nand provide install instructions.\n\n## Quick Reference\n\n| Command | What it does |\n|---------|-------------|\n| `\u002Fseo image-gen og \u003Cdescription>` | Generate OG\u002Fsocial preview image (1200x630 feel) |\n| `\u002Fseo image-gen hero \u003Cdescription>` | Blog hero image (widescreen, dramatic) |\n| `\u002Fseo image-gen product \u003Cdescription>` | Product photography (clean, white BG) |\n| `\u002Fseo image-gen infographic \u003Cdescription>` | Infographic visual (vertical, data-heavy) |\n| `\u002Fseo image-gen custom \u003Cdescription>` | Custom image with full Creative Director pipeline |\n| `\u002Fseo image-gen batch \u003Cdescription> [N]` | Generate N variations (default: 3) |\n\n## SEO Image Use Cases\n\nEach use case maps to pre-configured banana parameters:\n\n| Use Case | Aspect Ratio | Resolution | Domain Mode | Notes |\n|----------|-------------|------------|-------------|-------|\n| **OG\u002FSocial Preview** | `16:9` | `1K` | Product or UI\u002FWeb | Clean, professional, text-friendly |\n| **Blog Hero** | `16:9` | `2K` | Cinema or Editorial | Dramatic, atmospheric, editorial quality |\n| **Schema Image** | `4:3` | `1K` | Product | Clean, descriptive, schema ImageObject |\n| **Social Square** | `1:1` | `1K` | UI\u002FWeb | Platform-optimized square |\n| **Product Photo** | `4:3` | `2K` | Product | White background, studio lighting |\n| **Infographic** | `2:3` | `4K` | Infographic | Data-heavy, vertical layout |\n| **Favicon\u002FIcon** | `1:1` | `512` | Logo | Minimal, scalable, recognizable |\n| **Pinterest Pin** | `2:3` | `2K` | Editorial | Tall vertical card |\n\n## Generation Pipeline\n\nFor every generation request:\n\n1. **Identify use case** from command or context (og, hero, product, etc.)\n2. **Apply SEO defaults** from the use cases table above\n3. **Set aspect ratio** via `set_aspect_ratio` MCP tool\n4. **Construct Reasoning Brief** using the banana Creative Director pipeline:\n   - Load `references\u002Fprompt-engineering.md` for the 6-component system\n   - Apply domain mode emphasis (Subject 30%, Style 25%, Context 15%, etc.)\n   - Be SPECIFIC and VISCERAL: describe what the camera sees\n5. **Generate** via `gemini_generate_image` MCP tool\n6. **Post-generation SEO checklist** (see below)\n\n### Check for Presets\n\nIf the user mentions a brand or has SEO presets configured:\n```bash\n# Use the installed Banana MCP\u002Ftool configuration to list presets.\n```\nLoad matching preset and apply as defaults. Also check `references\u002Fseo-image-presets.md`\nfor SEO-specific preset templates.\n\n## Post-Generation SEO Checklist\n\nAfter every successful generation, guide the user on:\n\n1. **Alt text**:Write descriptive, keyword-rich alt text for the generated image\n2. **File naming**:Rename to SEO-friendly format: `keyword-description-widthxheight.webp`\n3. **WebP conversion**:Convert to WebP for optimal page speed:\n   ```bash\n   magick output.png -quality 85 output.webp\n   ```\n4. **File size**:Target under 200KB for hero images, under 100KB for thumbnails\n5. **Schema markup**:Suggest `ImageObject` schema for the generated image:\n   ```json\n   {\n     \"@type\": \"ImageObject\",\n     \"url\": \"https:\u002F\u002Fexample.com\u002Fimages\u002Fkeyword-description.webp\",\n     \"width\": 1200,\n     \"height\": 630,\n     \"caption\": \"Descriptive caption with target keyword\"\n   }\n   ```\n6. **OG meta tags**:For social preview images, remind about:\n   ```html\n   \u003Cmeta property=\"og:image\" content=\"https:\u002F\u002Fexample.com\u002Fimages\u002Fog-image.webp\" \u002F>\n   \u003Cmeta property=\"og:image:width\" content=\"1200\" \u002F>\n   \u003Cmeta property=\"og:image:height\" content=\"630\" \u002F>\n   \u003Cmeta property=\"og:image:alt\" content=\"Descriptive alt text\" \u002F>\n   ```\n\n## Cost Awareness\n\nImage generation costs money. Be transparent:\n- Show estimated cost before generating (especially for batch)\n- Log every generation in the installed Banana MCP\u002Ftool ledger when available\n- Use the installed Banana MCP\u002Ftool usage summary if user asks about usage\n\nApproximate costs:\n- Verify current pricing in the installed MCP\u002Ftool configuration before quoting\n\n## Model Routing\n\n| Scenario | Model | Why |\n|----------|-------|-----|\n| OG images, social previews | Installed MCP\u002Ftool default @ 1K | Fast, cost-effective |\n| Hero images, product photos | Installed MCP\u002Ftool quality model @ 2K | Quality + detail |\n| Infographics with text | Installed MCP\u002Ftool text-capable model @ 2K, thinking: high if supported | Better text rendering |\n| Quick drafts | Installed MCP\u002Ftool draft model @ 512 | Rapid iteration |\n\n## Error Handling\n\n| Error | Resolution |\n|-------|-----------|\n| MCP not configured | Run `.\u002Fextensions\u002Fbanana\u002Finstall.sh` |\n| API key invalid | New key at https:\u002F\u002Faistudio.google.com\u002Fapikey |\n| Rate limited (429) | Wait 60s, retry. Free tier: ~10 RPM \u002F ~500 RPD |\n| `IMAGE_SAFETY` | Rephrase prompt - see `references\u002Fprompt-engineering.md` Safety section |\n| MCP unavailable | Configure MCP with `.\u002Fextensions\u002Fbanana\u002Finstall.sh`; claude-seo does not vendor a local generation fallback script |\n| Extension not installed | Show install instructions: `.\u002Fextensions\u002Fbanana\u002Finstall.sh` |\n\n## Cross-Skill Integration\n\n- **seo-images** (analysis) feeds into **seo-image-gen** (generation): audit results from `\u002Fseo images` identify missing or low-quality images; use those findings to drive `\u002Fseo image-gen` commands\n- **seo-audit** spawns the seo-image-gen **agent** (not this skill) to analyze OG\u002Fsocial images across the site and produce a prioritized generation plan\n- **seo-schema** can consume generated images: after generation, suggest `ImageObject` schema markup pointing to the new assets\n\n## Reference Documentation\n\nLoad on-demand. Do NOT load all at startup:\n- `references\u002Fprompt-engineering.md`:6-component system, domain modes, templates\n- `references\u002Fgemini-models.md`:Model specs, rate limits, capabilities\n- `references\u002Fmcp-tools.md`:MCP tool parameters and responses\n- `references\u002Fpost-processing.md`:ImageMagick\u002FFFmpeg pipeline recipes\n- `references\u002Fcost-tracking.md`:Pricing, usage tracking\n- `references\u002Fpresets.md`:Brand preset management\n- `references\u002Fseo-image-presets.md`:SEO-specific preset templates\n\n## Response Format\n\nAfter generating, always provide:\n1. **Image path**:where it was saved\n2. **Crafted prompt**:show what was sent to the API (educational)\n3. **Settings**:model, aspect ratio, resolution\n4. **SEO checklist**:alt text suggestion, file naming, WebP conversion\n5. **Schema snippet**:ImageObject or og:image markup if applicable\n","# SEO Image Gen: AI Image Generation for SEO Assets (Extension)\n\nGenerate production-ready images for SEO use cases using Gemini's image generation\nvia the banana Creative Director pipeline. Maps SEO needs to optimized domain modes,\naspect ratios, and resolution defaults.\n\n## Architecture Note\n\nThis extension is built on [Claude Banana](https:\u002F\u002Fgithub.com\u002FAgriciDaniel\u002Fbanana-claude),\nthe standalone AI image generation skill for Claude Code.\n\nThis skill has two components with distinct roles:\n- **SKILL.md** (this file): Handles interactive `\u002Fseo image-gen` commands for generating images\n- **Agent** (`agents\u002Fseo-image-gen.md`): Audit-only analyst spawned during `\u002Fseo audit` to assess existing OG\u002Fsocial images and produce a generation plan (never auto-generates)\n\n## Prerequisites\n\nThis skill requires the banana extension to be installed:\n```bash\n.\u002Fextensions\u002Fbanana\u002Finstall.sh\n```\n\n**Check availability:** Before using any image generation tool, verify the MCP server\nis connected by checking if `gemini_generate_image` or `set_aspect_ratio` tools are\navailable. If tools are not available, inform the user the extension is not installed\nand provide install instructions.\n\n## Quick Reference\n\n| Command | What it does |\n|---------|-------------|\n| `\u002Fseo image-gen og \u003Cdescription>` | Generate OG\u002Fsocial preview image (1200x630 feel) |\n| `\u002Fseo image-gen hero \u003Cdescription>` | Blog hero image (widescreen, dramatic) |\n| `\u002Fseo image-gen product \u003Cdescription>` | Product photography (clean, white BG) |\n| `\u002Fseo image-gen infographic \u003Cdescription>` | Infographic visual (vertical, data-heavy) |\n| `\u002Fseo image-gen custom \u003Cdescription>` | Custom image with full Creative Director pipeline |\n| `\u002Fseo image-gen batch \u003Cdescription> [N]` | Generate N variations (default: 3) |\n\n## SEO Image Use Cases\n\nEach use case maps to pre-configured banana parameters:\n\n| Use Case | Aspect Ratio | Resolution | Domain Mode | Notes |\n|----------|-------------|------------|-------------|-------|\n| **OG\u002FSocial Preview** | `16:9` | `1K` | Product or UI\u002FWeb | Clean, professional, text-friendly |\n| **Blog Hero** | `16:9` | `2K` | Cinema or Editorial | Dramatic, atmospheric, editorial quality |\n| **Schema Image** | `4:3` | `1K` | Product | Clean, descriptive, schema ImageObject |\n| **Social Square** | `1:1` | `1K` | UI\u002FWeb | Platform-optimized square |\n| **Product Photo** | `4:3` | `2K` | Product | White background, studio lighting |\n| **Infographic** | `2:3` | `4K` | Infographic | Data-heavy, vertical layout |\n| **Favicon\u002FIcon** | `1:1` | `512` | Logo | Minimal, scalable, recognizable |\n| **Pinterest Pin** | `2:3` | `2K` | Editorial | Tall vertical card |\n\n## Generation Pipeline\n\nFor every generation request:\n\n1. **Identify use case** from command or context (og, hero, product, etc.)\n2. **Apply SEO defaults** from the use cases table above\n3. **Set aspect ratio** via `set_aspect_ratio` MCP tool\n4. **Construct Reasoning Brief** using the banana Creative Director pipeline:\n   - Load `references\u002Fprompt-engineering.md` for the 6-component system\n   - Apply domain mode emphasis (Subject 30%, Style 25%, Context 15%, etc.)\n   - Be SPECIFIC and VISCERAL: describe what the camera sees\n5. **Generate** via `gemini_generate_image` MCP tool\n6. **Post-generation SEO checklist** (see below)\n\n### Check for Presets\n\nIf the user mentions a brand or has SEO presets configured:\n```bash\n# Use the installed Banana MCP\u002Ftool configuration to list presets.\n```\nLoad matching preset and apply as defaults. Also check `references\u002Fseo-image-presets.md`\nfor SEO-specific preset templates.\n\n## Post-Generation SEO Checklist\n\nAfter every successful generation, guide the user on:\n\n1. **Alt text**:Write descriptive, keyword-rich alt text for the generated image\n2. **File naming**:Rename to SEO-friendly format: `keyword-description-widthxheight.webp`\n3. **WebP conversion**:Convert to WebP for optimal page speed:\n   ```bash\n   magick output.png -quality 85 output.webp\n   ```\n4. **File size**:Target under 200KB for hero images, under 100KB for thumbnails\n5. **Schema markup**:Suggest `ImageObject` schema for the generated image:\n   ```json\n   {\n     \"@type\": \"ImageObject\",\n     \"url\": \"https:\u002F\u002Fexample.com\u002Fimages\u002Fkeyword-description.webp\",\n     \"width\": 1200,\n     \"height\": 630,\n     \"caption\": \"Descriptive caption with target keyword\"\n   }\n   ```\n6. **OG meta tags**:For social preview images, remind about:\n   ```html\n   \u003Cmeta property=\"og:image\" content=\"https:\u002F\u002Fexample.com\u002Fimages\u002Fog-image.webp\" \u002F>\n   \u003Cmeta property=\"og:image:width\" content=\"1200\" \u002F>\n   \u003Cmeta property=\"og:image:height\" content=\"630\" \u002F>\n   \u003Cmeta property=\"og:image:alt\" content=\"Descriptive alt text\" \u002F>\n   ```\n\n## Cost Awareness\n\nImage generation costs money. Be transparent:\n- Show estimated cost before generating (especially for batch)\n- Log every generation in the installed Banana MCP\u002Ftool ledger when available\n- Use the installed Banana MCP\u002Ftool usage summary if user asks about usage\n\nApproximate costs:\n- Verify current pricing in the installed MCP\u002Ftool configuration before quoting\n\n## Model Routing\n\n| Scenario | Model | Why |\n|----------|-------|-----|\n| OG images, social previews | Installed MCP\u002Ftool default @ 1K | Fast, cost-effective |\n| Hero images, product photos | Installed MCP\u002Ftool quality model @ 2K | Quality + detail |\n| Infographics with text | Installed MCP\u002Ftool text-capable model @ 2K, thinking: high if supported | Better text rendering |\n| Quick drafts | Installed MCP\u002Ftool draft model @ 512 | Rapid iteration |\n\n## Error Handling\n\n| Error | Resolution |\n|-------|-----------|\n| MCP not configured | Run `.\u002Fextensions\u002Fbanana\u002Finstall.sh` |\n| API key invalid | New key at https:\u002F\u002Faistudio.google.com\u002Fapikey |\n| Rate limited (429) | Wait 60s, retry. Free tier: ~10 RPM \u002F ~500 RPD |\n| `IMAGE_SAFETY` | Rephrase prompt - see `references\u002Fprompt-engineering.md` Safety section |\n| MCP unavailable | Configure MCP with `.\u002Fextensions\u002Fbanana\u002Finstall.sh`; claude-seo does not vendor a local generation fallback script |\n| Extension not installed | Show install instructions: `.\u002Fextensions\u002Fbanana\u002Finstall.sh` |\n\n## Cross-Skill Integration\n\n- **seo-images** (analysis) feeds into **seo-image-gen** (generation): audit results from `\u002Fseo images` identify missing or low-quality images; use those findings to drive `\u002Fseo image-gen` commands\n- **seo-audit** spawns the seo-image-gen **agent** (not this skill) to analyze OG\u002Fsocial images across the site and produce a prioritized generation plan\n- **seo-schema** can consume generated images: after generation, suggest `ImageObject` schema markup pointing to the new assets\n\n## Reference Documentation\n\nLoad on-demand. 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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",[143],{"categoryNo":28,"categoryName":29,"taxonomyType":22,"taxonomyTypeDesc":23},[145,146,147,148,149,150,65,151,152,153,154,155,54,156,157,158,159,160,161,43,162],"skill creator","creator","performance","run evals","test","variance analysis","run","benchmark","analysis","improve","edit","evals","optimize","existing skill","for","accuracy","scratch","new",{"skillNo":164,"name":165,"nameZh":6,"description":166,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":139,"licenseFileUrl":6,"sourceHtmlUrl":167,"categories":168,"keywords":169,"publishedAt":68},"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",[],[170,171,172,173,174,175,63,176,177,178,179,180,181,182,183,184,54,185,186,187,188,189,190,191,192,193,159,194,195,43,196],"returns","returns reverse logistics","reverse logistics","reverse","github","code","https","authorization","detection","fraud","recovery","decisions","management","operations","vendor","claims management","frameworks","fraud detection","pattern","grading","processing","economics","managers","claims","expertise","refund","inspection",{"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":139,"licenseFileUrl":6,"sourceHtmlUrl":201,"categories":202,"keywords":203,"publishedAt":68},"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",[],[204,205,174,206,207,175,208,176,209,210,211,212,153,213,182,54,214,215,216,217,218,219,220,221,159,194,222,43],"quality","quality nonconformance","root cause analysis","interpretation","issues","audit","data","methodology","lifecycle","investigation","fda","across","manufacturing","environments","corrective action","supplier quality management","action","conformance","root cause",{"skillNo":224,"name":225,"nameZh":6,"description":226,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":139,"licenseFileUrl":6,"sourceHtmlUrl":227,"categories":228,"keywords":229,"publishedAt":68},"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",[],[230,231,232,174,175,62,176,233,153,234,235,54,236,237,186,238,239,240,216,241,159,194,43],"Production","production scheduling","scheduling","Optimization","erp","bottleneck","toc","patterns","line","interaction","sequencing","buffer",{"skillNo":243,"name":244,"nameZh":6,"description":245,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":139,"licenseFileUrl":6,"sourceHtmlUrl":246,"categories":247,"keywords":248,"publishedAt":68},"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",[],[182,249,174,175,250,208,251,176,252,54,186,253,254,255,256,193,159,194,257,43],"logistics exception management","shipping","protocols","escalation","delivery","claude-code","judgment","with","freight",{"skillNo":259,"name":260,"nameZh":6,"description":261,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":139,"licenseFileUrl":6,"sourceHtmlUrl":262,"categories":263,"keywords":264,"publishedAt":68},"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",[],[265,266,267,268,174,175,176,269,233,270,153,182,184,271,54,272,186,273,274,275,276,277,159,194,278,43],"planning","inventory","inventory demand planning","demand planning","negotiation","Safety","forecasting","selection","estimation","stock","seasonal","lift","at","transition"]