[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DBRQBWTKSA2512K70J7RVQ":3,"skill-same:01M6DBRQBWTKSA2512K70J7RVQ":62},{"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":35,"linkOnly":36,"markdownContent":37,"markdownBody":38,"frontMatter":39,"refName":42,"commitSha":43,"skillDirectory":44,"forksCount":14,"repositoryHtmlUrl":45,"repositoryHomepageUrl":6,"ownerHtmlUrl":46,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":47,"install":48,"resources":61},"01M6DBRQBWTKSA2512K70J7RVQ","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.","Prekzursil\u002Fagent-skills-toolchain","Prekzursil","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F54636077?v=4","01M6DACZ1PCQHD99SCR1YXG28B","Andrei Mihai Visalon","01M6DACZ670WZF535V3WYYSS4Z",0,"MIT","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Frecursive-decision-ledger\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34],"decision","recursive decision ledger","reasoning","search","Optimization","Bash","grep","read","write","edit","user","use","evidence","rollouts","exploration","local","2026-11-10 10:12:30",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.\norigin: 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":40,"origin":41,"description":7},"Read, Write, Edit, Bash, Grep, Glob","ECC","main","a298c929b6cbd662e1fce54302ce520d5ceea1a5",".agents\u002Fskills\u002Frecursive-decision-ledger","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain","https:\u002F\u002Fgithub.com\u002FPrekzursil","2026-11-02 14:30:57",{"source":8,"skillName":5,"commands":49,"prompt":59,"zipAvailable":60},[50,53,56],{"tool":51,"command":52},"npx","npx skills add Prekzursil\u002Fagent-skills-toolchain --skill recursive-decision-ledger",{"tool":54,"command":55},"bunx","bunx skills add Prekzursil\u002Fagent-skills-toolchain --skill recursive-decision-ledger",{"tool":57,"command":58},"pnpm","pnpm dlx skills add Prekzursil\u002Fagent-skills-toolchain --skill recursive-decision-ledger","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Frecursive-decision-ledger\u002FSKILL.md",true,[],[63,84,113,140,154,169],{"skillNo":64,"name":65,"nameZh":6,"description":66,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":67,"categories":68,"keywords":69,"publishedAt":35},"01M6DF7D7478R55P46REYH4QAC","clarify-requirements","Resolve genuine pre-execution ambiguity by scanning repo context, generating 1-6 grounded options, and asking 1-3 focused questions via AskUserQuestion. NOT for mid-task use (injection risk); NOT when the goal is already unambiguous; use to disambiguate vague prompts before any file edits.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Fworkspace-hooks\u002Fskills\u002Fclarify-requirements\u002FSKILL.md",[],[70,71,72,73,74,75,76,77,78,30,79,80,81,82,83],"clarify requirements","clarify","requirements","risk","options","task","prompts","goal","scanning","context","repo","injection","execution","file",{"skillNo":85,"name":86,"nameZh":6,"description":87,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":88,"categories":89,"keywords":95,"publishedAt":35},"01M6DF79CA4BHJS66J8EZDBPWJ","openmm-md","Run FREE, open-source, Windows-native GPU molecular dynamics via the openmm-md MCP (OpenMM + CUDA on the local NVIDIA GPU). Use for protein \u002F protein-ligand MD when you want a free stack or are on Windows without a Schrodinger license. Covers the full workflow (prepare, solvate, minimize, equilibrate, production, analyze, mmgbsa) AND an honest decision guide vs Schrodinger Desmond, including how to run Desmond legitimately on Linux or a cloud GPU with a real license. This is a deliberately LESSER free alternative and does NOT replace the schrodinger MCP tools. Do NOT use it to pick a free tool when a validated FEP+, WaterMap, IFD-MD, or Prime MM-GBSA result is actually required.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Fmcp\u002Fopenmm-md-mcp\u002Fskill\u002Fopenmm-md\u002FSKILL.md",[90],{"categoryNo":91,"categoryName":92,"taxonomyType":93,"taxonomyTypeDesc":94},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[96,97,19,98,99,100,101,102,103,104,105,106,107,108,30,109,110,34,111,112],"openmm md","how","pick","linux","analyze","tool","stack","open","NVIDIA","gpu","license","workflow","windows","free","molecular dynamics","do","MCP",{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":117,"categories":118,"keywords":125,"publishedAt":35},"01M6DF76C1MG85VEWP8VZCBNMN","visual-review","Take screenshots of web pages and UI using Playwright for visual review and iteration","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fvisual-review\u002FSKILL.md",[119,122],{"categoryNo":120,"categoryName":121,"taxonomyType":93,"taxonomyTypeDesc":94},"01JBSEEDCAT000000000000003","演示文稿",{"categoryNo":123,"categoryName":124,"taxonomyType":93,"taxonomyTypeDesc":94},"01JBSEEDCAT000000000000008","测试与质量",[126,127,128,129,130,131,132,133,134,135,97,136,137,138,139],"review","visual","visual review","pages","web","false","iteration","take","check","slides","ui","screenshot","playwright","screenshots",{"skillNo":141,"name":142,"nameZh":6,"description":143,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":144,"categories":145,"keywords":146,"publishedAt":35},"01M6DF73AQVCBZKEN0YXEX9FXP","status","Diagnostic status report — shows metaswarm installation state, project setup, and potential issues","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fstatus\u002FSKILL.md",[],[142,147,148,149,150,151,152,153],"setup","report","project","installation","project setup","issues","state",{"skillNo":155,"name":156,"nameZh":6,"description":157,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":158,"categories":159,"keywords":161,"publishedAt":35},"01M6DF6X6C2XB0P6GX76P7TTYV","start","Use when starting work on any task, when the user mentions metaswarm, or when the user wants to begin tracked development work","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fstart\u002FSKILL.md",[160],{"categoryNo":91,"categoryName":92,"taxonomyType":93,"taxonomyTypeDesc":94},[156,162,75,163,164,165,30,29,166,167,168],"start issue","issue","ready","work on issue","work","work on","development",{"skillNo":170,"name":147,"nameZh":6,"description":171,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":172,"categories":173,"keywords":174,"publishedAt":35},"01M6DF6QMJ9AJKFKHHKRT005PQ","Interactive project setup — detects your project, configures metaswarm, writes project-local files","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fsetup\u002FSKILL.md",[],[147,149,34,175,151,176],"files","interactive"]