[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6D82SP1WG5CHRBY7VV1DAYY":3,"skill-same:01M6D82SP1WG5CHRBY7VV1DAYY":60},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":31,"linkOnly":32,"markdownContent":33,"markdownBody":34,"frontMatter":35,"refName":37,"commitSha":38,"skillDirectory":39,"forksCount":40,"repositoryHtmlUrl":41,"repositoryHomepageUrl":6,"ownerHtmlUrl":42,"ownerBlogUrl":43,"ownerDescription":44,"updatedAt":45,"install":46,"resources":59},"01M6D82SP1WG5CHRBY7VV1DAYY","agentic-engineering",null,"Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.","oabdelmaksoud\u002FSuperClaw","oabdelmaksoud","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F50699149?v=4","01M6D5CVVN778ZCDP1WHS816SP","Omar Abdelmaksoud","01M6D5CW1RHNSKCJR85GJACBFT",2,"MIT","https:\u002F\u002Fgithub.com\u002Foabdelmaksoud\u002FSuperClaw\u002Fblob\u002Fmain\u002Fupstream-sync\u002Fwork\u002Fecc\u002Fskills\u002Fagentic-engineering\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30],"agentic","agentic engineering","engineering","routing","execution","first","model","eval","cost","engineer","decomposition","as","2026-11-10 10:12:30",false,"---\nname: agentic-engineering\ndescription: Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.\norigin: ECC\n---\n\n# Agentic Engineering\n\nUse this skill for engineering workflows where AI agents perform most implementation work and humans enforce quality and risk controls.\n\n## Operating Principles\n\n1. Define completion criteria before execution.\n2. Decompose work into agent-sized units.\n3. Route model tiers by task complexity.\n4. Measure with evals and regression checks.\n\n## Eval-First Loop\n\n1. Define capability eval and regression eval.\n2. Run baseline and capture failure signatures.\n3. Execute implementation.\n4. Re-run evals and compare deltas.\n\n## Task Decomposition\n\nApply the 15-minute unit rule:\n- each unit should be independently verifiable\n- each unit should have a single dominant risk\n- each unit should expose a clear done condition\n\n## Model Routing\n\n- Haiku: classification, boilerplate transforms, narrow edits\n- Sonnet: implementation and refactors\n- Opus: architecture, root-cause analysis, multi-file invariants\n\n## Session Strategy\n\n- Continue session for closely-coupled units.\n- Start fresh session after major phase transitions.\n- Compact after milestone completion, not during active debugging.\n\n## Review Focus for AI-Generated Code\n\nPrioritize:\n- invariants and edge cases\n- error boundaries\n- security and auth assumptions\n- hidden coupling and rollout risk\n\nDo not waste review cycles on style-only disagreements when automated format\u002Flint already enforce style.\n\n## Cost Discipline\n\nTrack per task:\n- model\n- token estimate\n- retries\n- wall-clock time\n- success\u002Ffailure\n\nEscalate model tier only when lower tier fails with a clear reasoning gap.\n","# Agentic Engineering\n\nUse this skill for engineering workflows where AI agents perform most implementation work and humans enforce quality and risk controls.\n\n## Operating Principles\n\n1. Define completion criteria before execution.\n2. Decompose work into agent-sized units.\n3. Route model tiers by task complexity.\n4. Measure with evals and regression checks.\n\n## Eval-First Loop\n\n1. Define capability eval and regression eval.\n2. Run baseline and capture failure signatures.\n3. Execute implementation.\n4. Re-run evals and compare deltas.\n\n## Task Decomposition\n\nApply the 15-minute unit rule:\n- each unit should be independently verifiable\n- each unit should have a single dominant risk\n- each unit should expose a clear done condition\n\n## Model Routing\n\n- Haiku: classification, boilerplate transforms, narrow edits\n- Sonnet: implementation and refactors\n- Opus: architecture, root-cause analysis, multi-file invariants\n\n## Session Strategy\n\n- Continue session for closely-coupled units.\n- Start fresh session after major phase transitions.\n- Compact after milestone completion, not during active debugging.\n\n## Review Focus for AI-Generated Code\n\nPrioritize:\n- invariants and edge cases\n- error boundaries\n- security and auth assumptions\n- hidden coupling and rollout risk\n\nDo not waste review cycles on style-only disagreements when automated format\u002Flint already enforce style.\n\n## Cost Discipline\n\nTrack per task:\n- model\n- token estimate\n- retries\n- wall-clock time\n- success\u002Ffailure\n\nEscalate model tier only when lower tier fails with a clear reasoning gap.\n",{"name":5,"origin":36,"description":7},"ECC","main","7b610356e36623652299fa2acb477ff821b1d920","upstream-sync\u002Fwork\u002Fecc\u002Fskills\u002Fagentic-engineering",0,"https:\u002F\u002Fgithub.com\u002Foabdelmaksoud\u002FSuperClaw","https:\u002F\u002Fgithub.com\u002Foabdelmaksoud","https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fo-abdelmaksoud\u002F","Full-Stack Engineer | AI Systems Architect | Building autonomous multi-agent systems","2026-03-08 21:12:53",{"source":8,"skillName":5,"commands":47,"prompt":57,"zipAvailable":58},[48,51,54],{"tool":49,"command":50},"npx","npx skills add oabdelmaksoud\u002FSuperClaw --skill agentic-engineering",{"tool":52,"command":53},"bunx","bunx skills add oabdelmaksoud\u002FSuperClaw --skill agentic-engineering",{"tool":55,"command":56},"pnpm","pnpm dlx skills add oabdelmaksoud\u002FSuperClaw --skill agentic-engineering","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Foabdelmaksoud\u002FSuperClaw\u002Fblob\u002Fmain\u002Fupstream-sync\u002Fwork\u002Fecc\u002Fskills\u002Fagentic-engineering\u002FSKILL.md",true,[],[61,82,96,127,153,172],{"skillNo":62,"name":63,"nameZh":6,"description":64,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":65,"categories":66,"keywords":72,"publishedAt":31},"01M6D88QCPTBZVCRED0NZ1Y8K8","visa-doc-translate","Translate visa application documents (images) to English and create a bilingual PDF with original and translation","https:\u002F\u002Fgithub.com\u002Foabdelmaksoud\u002FSuperClaw\u002Fblob\u002Fmain\u002Fupstream-sync\u002Fwork\u002Fecc\u002Fskills\u002Fvisa-doc-translate\u002FSKILL.md",[67],{"categoryNo":68,"categoryName":69,"taxonomyType":70,"taxonomyTypeDesc":71},"01JBSEEDCAT000000000000002","文档处理","SCENARIO","使用场景",[73,74,75,76,77,78,79,80,81],"translate","doc","visa doc translate","translation","application","create","images","PDF","documents",{"skillNo":83,"name":84,"nameZh":6,"description":85,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":86,"categories":87,"keywords":88,"publishedAt":31},"01M6D88NBM95T3TFM50CYYAP65","verification-loop","A comprehensive verification system for Claude Code sessions.","https:\u002F\u002Fgithub.com\u002Foabdelmaksoud\u002FSuperClaw\u002Fblob\u002Fmain\u002Fupstream-sync\u002Fwork\u002Fecc\u002Fskills\u002Fverification-loop\u002FSKILL.md",[],[89,90,91,92,93,94,95],"verification","loop","verification loop","sessions","code","claude code sessions","system",{"skillNo":97,"name":98,"nameZh":6,"description":99,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":100,"categories":101,"keywords":113,"publishedAt":31},"01M6D88JFZ2P996GVRHJNSZSTM","tdd-workflow","Use this skill when writing new features, fixing bugs, or refactoring code. 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