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03:05:39",{"accountNo":154,"login":155,"displayName":156,"avatarUrl":157,"accountType":107,"accountTypeDesc":108,"profileDescription":158,"skillCount":159,"repoCount":160,"professionCount":5,"scenarioCount":6,"totalStars":161,"updatedAt":162},"01M6AC83DS133TPXFSP1DHNCC6","github","GitHub","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F9919?v=4","How people build software.",936,27,238434,"2026-11-13 03:17:57",{"accountNo":164,"login":165,"displayName":166,"avatarUrl":167,"accountType":107,"accountTypeDesc":108,"profileDescription":18,"skillCount":168,"repoCount":169,"professionCount":5,"scenarioCount":6,"totalStars":170,"updatedAt":171},"01M697XGDPXJAVQ8391V2BCYTE","anthropics","Anthropic","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F76263028?v=4",674,17,231455,"2026-11-12 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Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.","endman100\u002Fskill-router-nexus","endman100","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F31997019?v=4","01M6KPDX17BYDWW4RRB0TNGGMX","01M6KPDX64Y2QBEWVFG5W5PWPF",0,"MIT","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FImage-Recognition\u002Fsegment-anything\u002FSKILL.md",[210],{"categoryNo":211,"categoryName":212,"taxonomyType":11,"taxonomyTypeDesc":12},"01JBSEEDCAT000000000000016","图像与多媒体",[214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234],"model","segment anything model","segment","segment anything","image","generate","multimodal","ZeRO","Transformers","segmentation","computer","use","vision","images","as","boxes","Zero-Shot","you","orchestra","for","when","2026-11-10 10:12:30",{"skillNo":237,"name":238,"nameZh":18,"description":239,"descriptionZh":18,"repositoryFullName":240,"ownerLogin":241,"ownerAvatarUrl":242,"ownerAccountNo":243,"ownerDisplayName":18,"repositoryNo":244,"starsCount":206,"licenseSpdxId":245,"licenseFileUrl":18,"sourceHtmlUrl":246,"categories":247,"keywords":248,"publishedAt":235},"01M6RTK6P0Y76ENS21K9R0PA3P","blender-motion-state-inspection","Use this skill when inspecting Blender characters, rigs, poses, animation retargeting, ground contact, facing direction, or model-vs-motion alignment where screenshots alone are not enough.","sakamoto-family-smile\u002Fagent_monorepo","sakamoto-family-smile","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F132812403?v=4","01M6RTAT3H8PMWX5SJ65KP3VYF","01M6RTAV321WB5RAHCWTZMX5CV","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Fblender-motion-state-inspection\u002FSKILL.md",[],[249,250,251,252,253,254,255,256,214,257,258,259,260,225,261,262,263,264,234],"state","motion","blender","blender motion state inspection","inspection","screenshots","Animation","Bash","grep","read","write","edit","alignment","direction","retargeting","characters",{"skillNo":266,"name":267,"nameZh":18,"description":268,"descriptionZh":18,"repositoryFullName":240,"ownerLogin":241,"ownerAvatarUrl":242,"ownerAccountNo":243,"ownerDisplayName":18,"repositoryNo":244,"starsCount":206,"licenseSpdxId":245,"licenseFileUrl":18,"sourceHtmlUrl":269,"categories":270,"keywords":271,"publishedAt":235},"01M6RTK1PYYAAGNZXNSFRJQ58N","benchmark-optimization-loop","Use when the user asks to make something faster, try many variants, run recursive optimization, benchmark latency\u002Fthroughput\u002Fcost, or choose the best implementation by repeated measured tests.","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Fbenchmark-optimization-loop\u002FSKILL.md",[],[272,273,274,275,276,256,277,257,258,259,260,225,278,279,280,281,282,283,284,234],"benchmark","Optimization","loop","benchmark optimization loop","run","choose","cost","implementation","latency","tests","throughput","recursive","variants",{"skillNo":286,"name":287,"nameZh":18,"description":288,"descriptionZh":18,"repositoryFullName":240,"ownerLogin":241,"ownerAvatarUrl":242,"ownerAccountNo":243,"ownerDisplayName":18,"repositoryNo":244,"starsCount":206,"licenseSpdxId":245,"licenseFileUrl":18,"sourceHtmlUrl":289,"categories":290,"keywords":297,"publishedAt":235},"01M6RTJXKN1TRKVMWMBAA40VD8","backend-patterns","Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Fbackend-patterns\u002FSKILL.md",[291,294],{"categoryNo":292,"categoryName":293,"taxonomyType":11,"taxonomyTypeDesc":12},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":295,"categoryName":296,"taxonomyType":11,"taxonomyTypeDesc":12},"01JBSEEDCAT000000000000015","视觉设计",[298,299,300,301,302,303,304,305,306,273,307,308,309,310,311,312,313,314,315,233],"backend patterns","backend","patterns","design","architecture","api design","best practices","database","server","architecture patterns","api","Next.js","js","node","database optimization","next","express","server-side",{"skillNo":317,"name":318,"nameZh":18,"description":319,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":18,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":18,"sourceHtmlUrl":320,"categories":321,"keywords":323,"publishedAt":235},"01M6KWAWXVX4QDT9CVYCPQ66CX","llava","Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna\u002FLLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FImage-Recognition\u002Fllava\u002Fllava\u002FSKILL.md",[322],{"categoryNo":211,"categoryName":212,"taxonomyType":11,"taxonomyTypeDesc":12},[318,218,324,325,220,222,326,327,328,329,226,330,331,332,333,334,335,336,232,233],"assistant","tasks","tuning","analysis","question","clip","Vision-Language","Visual Question Answering","Image Chat","Vicuna","image understanding","conversations","pillow",{"skillNo":338,"name":339,"nameZh":18,"description":340,"descriptionZh":18,"repositoryFullName":240,"ownerLogin":241,"ownerAvatarUrl":242,"ownerAccountNo":243,"ownerDisplayName":18,"repositoryNo":244,"starsCount":206,"licenseSpdxId":245,"licenseFileUrl":18,"sourceHtmlUrl":341,"categories":342,"keywords":346,"publishedAt":235},"01M6RTJ658EER99Q27GCF19SGK","autonomous-loops","Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Fautonomous-loops\u002FSKILL.md",[343],{"categoryNo":344,"categoryName":345,"taxonomyType":11,"taxonomyTypeDesc":12},"01JBSEEDCAT000000000000023","Skill与智能体开发",[347,348,349,350,351,352,353,354,355,300,356,357,358,359,233],"autonomous","autonomous loops","loops","dag","code","RFC","multi-agent","pipelines","simple","systems","driven","architectures","multi",{"skillNo":361,"name":318,"nameZh":18,"description":319,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":18,"repositoryNo":205,"starsCount":206,"licenseSpdxId":207,"licenseFileUrl":18,"sourceHtmlUrl":362,"categories":363,"keywords":365,"publishedAt":235},"01M6KWANBCBP12C8F3FBNG1DJM","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FImage-Recognition\u002Fllava\u002FSKILL.md",[364],{"categoryNo":211,"categoryName":212,"taxonomyType":11,"taxonomyTypeDesc":12},[318,218,324,325,220,222,326,327,328,329,226,330,331,332,333,334,335,336,232,233],{"skillNo":367,"name":368,"nameZh":18,"description":369,"descriptionZh":18,"repositoryFullName":240,"ownerLogin":241,"ownerAvatarUrl":242,"ownerAccountNo":243,"ownerDisplayName":18,"repositoryNo":244,"starsCount":206,"licenseSpdxId":245,"licenseFileUrl":18,"sourceHtmlUrl":370,"categories":371,"keywords":373,"publishedAt":235},"01M6RTJ0Z6EFA7P0X8AH8HTSQQ","automation-audit-ops","Evidence-first automation inventory and overlap audit workflow for ECC. Use when the user wants to know which jobs, hooks, connectors, MCP servers, or wrappers are live, broken, redundant, or missing before fixing anything.","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Fautomation-audit-ops\u002FSKILL.md",[372],{"categoryNo":344,"categoryName":345,"taxonomyType":11,"taxonomyTypeDesc":12},[374,375,376,377,378,379,380,381,382,383,384,385,225,386,387,388,389,390,233,391,234],"automation","audit","ops","automation audit","automation audit ops","audit ops","MCP","workflow","connectors","first","inventory","broken","evidence","hooks","missing","audit workflow","which","servers",{"skillNo":393,"name":394,"nameZh":18,"description":395,"descriptionZh":18,"repositoryFullName":240,"ownerLogin":241,"ownerAvatarUrl":242,"ownerAccountNo":243,"ownerDisplayName":18,"repositoryNo":244,"starsCount":206,"licenseSpdxId":245,"licenseFileUrl":18,"sourceHtmlUrl":396,"categories":397,"keywords":402,"publishedAt":235},"01M6RTHGY75KXAXHWJ7BR8RX31","article-writing","Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Farticle-writing\u002FSKILL.md",[398,401],{"categoryNo":399,"categoryName":400,"taxonomyType":11,"taxonomyTypeDesc":12},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":80,"categoryName":81,"taxonomyType":58,"taxonomyTypeDesc":59},[403,404,405,406,407,408,409,259,225,410,411,412,413,414,415,416,417,418,419,234],"writing","article writing","article","issues","examples","blog","brand","guidance","newsletter","structure","long","guides","form","posts","consistency","long-form","credibility",{"skillNo":421,"name":422,"nameZh":18,"description":423,"descriptionZh":18,"repositoryFullName":240,"ownerLogin":241,"ownerAvatarUrl":242,"ownerAccountNo":243,"ownerDisplayName":18,"repositoryNo":244,"starsCount":206,"licenseSpdxId":245,"licenseFileUrl":18,"sourceHtmlUrl":424,"categories":425,"keywords":430,"publishedAt":235},"01M6RTH9932TAJTQW97J8FT35X","api-design","REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs.","https:\u002F\u002Fgithub.com\u002Fsakamoto-family-smile\u002Fagent_monorepo\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fecc\u002Fapi-design\u002FSKILL.md",[426,427,428,429],{"categoryNo":292,"categoryName":293,"taxonomyType":11,"taxonomyTypeDesc":12},{"categoryNo":295,"categoryName":296,"taxonomyType":11,"taxonomyTypeDesc":12},{"categoryNo":57,"categoryName":60,"taxonomyType":58,"taxonomyTypeDesc":59},{"categoryNo":66,"categoryName":67,"taxonomyType":58,"taxonomyTypeDesc":59},[301,303,308,431,432,433,434,435,436,437,300,438,439,440,441,442,443,444,233,445],"status","Production","REST","versioning","filtering","design patterns","pagination","rate limiting","rest api","error","codes","api design patterns","naming","rest api design","rate",{"skillNo":447,"name":448,"nameZh":18,"description":449,"descriptionZh":18,"repositoryFullName":240,"ownerLogin":241,"ownerAvatarUrl":242,"ownerAccountNo":243,"ownerDisplayName":18,"repositoryNo":244,"starsCount":206,"licenseSpdxId":245,"licenseFileUrl":18,"sourceHtmlUrl":450,"categories":451,"keywords":454,"publishedAt":235},"01M6RTH1G229TR1B7T52CR2F2J","api-connector-builder","Build a new API connector or provider by matching the target repo's existing integration pattern exactly. 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