[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7EEV3KB7C7W7JMDPBFNEFSX":3,"skill-same:01M7EEV3KB7C7W7JMDPBFNEFSX":49},{"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":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":27,"commitSha":28,"skillDirectory":29,"forksCount":30,"repositoryHtmlUrl":31,"repositoryHomepageUrl":6,"ownerHtmlUrl":32,"ownerBlogUrl":6,"ownerDescription":33,"updatedAt":34,"install":35,"resources":48},"01M7EEV3KB7C7W7JMDPBFNEFSX","recursive-decision-ledger",null,"Use when the user asks for repeated rollouts, marked decision processes, high-dimensional search, stochastic optimization, local-optima exploration, ensemble comparison, or recursive reasoning with a visible evidence trail.","sanjeevafk\u002Fagent-skills","sanjeevafk","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F230678117?v=4","01M7C540EFY46ETG1NNWKS5X3Q","Sanjeev","01M7C540F366J5C1D587BMKH9Q",0,"MIT","https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Frecursive-decision-ledger\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: recursive-decision-ledger\ndescription: Use when the user asks for repeated rollouts, marked decision processes, high-dimensional search, stochastic optimization, local-optima exploration, ensemble comparison, or recursive reasoning with a visible evidence trail.\nlicense: MIT\nmetadata:\n  origin: ECC\ntools: Read, Write, Edit, Bash, Grep, Glob\n---\n\n# Recursive Decision Ledger\n\nUse this skill when the user is trying to force deeper computation through\nrepeated rollouts or \"Prime Gauss\" style recursive prompting. Preserve the useful\npart: repeated trials, prior memory, fresh information, and explicit marks.\nRemove the unsafe part: pretending the loop proves certainty.\n\n## Ledger Contract\n\nEvery rollout should record:\n\n- rollout id and timestamp;\n- prior accepted winner and prior watchlist;\n- fresh information ingested;\n- search space size;\n- model families or heuristics used;\n- trial count and effective trial count;\n- top candidates;\n- decision marks;\n- coherence marks against the prior ledger;\n- promotion gate result.\n\nPrefer JSONL for append-only ledgers and Markdown for human summaries.\n\n## Rollout Loop\n\n1. Load the prior ledger.\n2. Capture new information at time-step zero.\n3. Run the bounded search.\n4. Mark each candidate: accept, watch, reject, decay watch, or needs replay.\n5. Compare winners against prior winners and latest marked rollout.\n6. Downgrade candidates when drift, tail risk, stale data, or failed replay\n   invalidates the previous mark.\n7. Append artifacts before summarizing.\n\n## Coherence Mark\n\nInclude a compact coherence mark:\n\n```text\nEnsemble matches prior winner: true\nRecursive matches prior winner: false\nLatest rollout match: true\nLive promotion allowed: false\nReason: replay and freshness gates not satisfied\n```\n\n## Promotion Rules\n\nFor trading, capital allocation, production deploys, migrations, or destructive\nops, recursive confidence is not approval.\n\nDefault to paper, dry-run, read-only, preview, or staged mode unless the user\nexplicitly approves the live action and the repo\u002Fservice gate supports it.\n\nPromote only when:\n\n- the candidate beats the prior accepted winner on the chosen metric;\n- correctness and replay checks pass;\n- risk limits are explicit;\n- the evidence is durable;\n- the user has approved the live step when needed.\n\n## Summary Shape\n\nLead with the decision, not the drama:\n\n```text\nRollout 15 complete. The prior winner still holds, but edge deteriorated 17%.\nStatus: watch, not live. Next gate: 20 replay fills with fresh orderbook age\nbelow threshold.\n```\n","# Recursive Decision Ledger\n\nUse this skill when the user is trying to force deeper computation through\nrepeated rollouts or \"Prime Gauss\" style recursive prompting. Preserve the useful\npart: repeated trials, prior memory, fresh information, and explicit marks.\nRemove the unsafe part: pretending the loop proves certainty.\n\n## Ledger Contract\n\nEvery rollout should record:\n\n- rollout id and timestamp;\n- prior accepted winner and prior watchlist;\n- fresh information ingested;\n- search space size;\n- model families or heuristics used;\n- trial count and effective trial count;\n- top candidates;\n- decision marks;\n- coherence marks against the prior ledger;\n- promotion gate result.\n\nPrefer JSONL for append-only ledgers and Markdown for human summaries.\n\n## Rollout Loop\n\n1. Load the prior ledger.\n2. Capture new information at time-step zero.\n3. Run the bounded search.\n4. Mark each candidate: accept, watch, reject, decay watch, or needs replay.\n5. Compare winners against prior winners and latest marked rollout.\n6. Downgrade candidates when drift, tail risk, stale data, or failed replay\n   invalidates the previous mark.\n7. Append artifacts before summarizing.\n\n## Coherence Mark\n\nInclude a compact coherence mark:\n\n```text\nEnsemble matches prior winner: true\nRecursive matches prior winner: false\nLatest rollout match: true\nLive promotion allowed: false\nReason: replay and freshness gates not satisfied\n```\n\n## Promotion Rules\n\nFor trading, capital allocation, production deploys, migrations, or destructive\nops, recursive confidence is not approval.\n\nDefault to paper, dry-run, read-only, preview, or staged mode unless the user\nexplicitly approves the live action and the repo\u002Fservice gate supports it.\n\nPromote only when:\n\n- the candidate beats the prior accepted winner on the chosen metric;\n- correctness and replay checks pass;\n- risk limits are explicit;\n- the evidence is durable;\n- the user has approved the live step when needed.\n\n## Summary Shape\n\nLead with the decision, not the drama:\n\n```text\nRollout 15 complete. The prior winner still holds, but edge deteriorated 17%.\nStatus: watch, not live. Next gate: 20 replay fills with fresh orderbook age\nbelow threshold.\n```\n",{"name":5,"tools":24,"license":15,"metadata":25,"description":7},"Read, Write, Edit, Bash, Grep, Glob",{"origin":26},"ECC","main","4e084e84eb42fc53e144c89c0f7f48b39c8a4b0f","skills\u002Frecursive-decision-ledger",1,"https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills","https:\u002F\u002Fgithub.com\u002Fsanjeevafk","First make it work. Then make it right. Then make it fast.","2026-11-14 13:36:16",{"source":8,"skillName":5,"commands":36,"prompt":46,"zipAvailable":47},[37,40,43],{"tool":38,"command":39},"npx","npx skills add sanjeevafk\u002Fagent-skills --skill recursive-decision-ledger",{"tool":41,"command":42},"bunx","bunx skills add sanjeevafk\u002Fagent-skills --skill recursive-decision-ledger",{"tool":44,"command":45},"pnpm","pnpm dlx skills add sanjeevafk\u002Fagent-skills --skill recursive-decision-ledger","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Frecursive-decision-ledger\u002FSKILL.md",true,[],[50,57,65,74,82,89],{"skillNo":51,"name":52,"nameZh":6,"description":53,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":54,"categories":55,"keywords":56,"publishedAt":19},"01M7EFHX67M3KKXT1BXVPA5ADT","zarr-python","Chunked N-D arrays for cloud storage (Zarr-Python 3). Compressed arrays, parallel I\u002FO, S3\u002FGCS via fsspec, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzarr-python\u002FSKILL.md",[],[],{"skillNo":58,"name":59,"nameZh":6,"description":60,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":61,"sourceHtmlUrl":62,"categories":63,"keywords":64,"publishedAt":19},"01M7EFFQGM51TZBGRENXY50ZYM","whiteboard-diagrams","Create accurate, simple, hand-drawn whiteboard diagrams from a user's process, system, architecture, learning workflow, comparison, or causal explanation. Use when the user asks for a scribbly whiteboard visual, educational workflow graphic, hand-drawn explainer, or diagram like the bundled reference; ask one focused clarification question when the subject or relationships are missing, then generate and visually verify the final image.","https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Fwhiteboard-diagrams\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Fwhiteboard-diagrams\u002FSKILL.md",[],[],{"skillNo":66,"name":67,"nameZh":6,"description":68,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":69,"licenseFileUrl":70,"sourceHtmlUrl":71,"categories":72,"keywords":73,"publishedAt":19},"01M7EFF1CSQNTDMHFK4ZGY6NYK","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Fwebapp-testing\u002FSKILL.md",[],[],{"skillNo":75,"name":76,"nameZh":6,"description":77,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":69,"licenseFileUrl":78,"sourceHtmlUrl":79,"categories":80,"keywords":81,"publishedAt":19},"01M7EFE8106X6C28FT8PA74427","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Fweb-artifacts-builder\u002FSKILL.md",[],[],{"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":19},"01M7EFCSNZM9G7ZHS6F127Q71X","verification-loop","A comprehensive verification system for Claude Code sessions.","https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Fverification-loop\u002FSKILL.md",[],[],{"skillNo":90,"name":91,"nameZh":6,"description":92,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":93,"sourceHtmlUrl":94,"categories":95,"keywords":96,"publishedAt":19},"01M7EFCE7EZMKPRYDDNKBQ9EEH","vercel-deploy","Deploy applications and websites to Vercel. Use when the user requests deployment actions like \"deploy my app\", \"deploy and give me the link\", \"push this live\", or \"create a preview deployment\".","https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Fvercel-deploy\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fsanjeevafk\u002Fagent-skills\u002Fblob\u002Fmain\u002Fskills\u002Fvercel-deploy\u002FSKILL.md",[],[]]