[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DCMGZF4ST09BW07ZFHDZ1R":3,"skill-same:01M6DCMGZF4ST09BW07ZFHDZ1R":64},{"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":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":44,"commitSha":45,"skillDirectory":46,"forksCount":14,"repositoryHtmlUrl":47,"repositoryHomepageUrl":6,"ownerHtmlUrl":48,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":49,"install":50,"resources":63},"01M6DCMGZF4ST09BW07ZFHDZ1R","gem-hunt",null,"Use when the user wants to DISCOVER high-value improvements to their OWN agentic workspace\u002Ftoolkit — new hooks, behaviors, gems, skills, MCPs, cross-domain techniques, or frontier-harness patterns — via a wide multi-lens agent fan-out, then a consolidated adopt\u002Fprune decision. This is the named \"agentic-perfection sweep\" \u002F \"extensive gem search\" process. Triggers: \"find more gems\", \"search extensive(ly) for improvements\", \"agentic perfection\", \"fan out to explore improvements\u002Fhooks\", \"what are we missing vs other tools\", \"self-improve the harness\". NOT for interrogating ONE existing plan (use grill-me-extensive), NOT for ordinary topic research (use deep-research).","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\u002Fplatform\u002Frouting\u002Ffixtures\u002Fhome\u002F.agents\u002Fskills\u002Fgem-hunt\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"gem hunt","gem","hunt","grill-me","triggers","adopt","discover","deep","self","domain","agentic","hooks","use","decision","sweep","improve","explore","search","harness","toolkit","2026-11-10 10:12:30",false,"---\nname: gem-hunt\ndescription: >-\n  Use when the user wants to DISCOVER high-value improvements to their OWN agentic\n  workspace\u002Ftoolkit — new hooks, behaviors, gems, skills, MCPs, cross-domain techniques,\n  or frontier-harness patterns — via a wide multi-lens agent fan-out, then a consolidated\n  adopt\u002Fprune decision. This is the named \"agentic-perfection sweep\" \u002F \"extensive gem\n  search\" process. Triggers: \"find more gems\", \"search extensive(ly) for improvements\",\n  \"agentic perfection\", \"fan out to explore improvements\u002Fhooks\", \"what are we missing\n  vs other tools\", \"self-improve the harness\". NOT for interrogating ONE existing plan\n  (use grill-me-extensive), NOT for ordinary topic research (use deep-research).\n---\n\n# Gem-Hunt — extensive multi-lens workspace self-improvement sweep\n\nThe repeatable form of the process that produced the agentic-perfection gems (open-loops,\ncontraindication-registry, iatrogenics-gate, the closed self-improvement loop, ACE, …).\nRe-run it whenever the landscape moves (new papers, new tools, new domains) — the lenses\nand discipline below are the winning formula; only the findings change.\n\n**Core philosophy (the user's standing intent):** fan out **LARGE** and wide — *\"there's no\nreason to limit the search; a gold gem unfound is a waste.\"* Breadth-first across diverse,\nindependent lenses beats one deep pass, because the best finds come from angles you wouldn't\nhave prompted for. Be adversarially honest, cite, grade confidence, and converge to a\ndecision the user steers — never silently adopt.\n\n## The method (7 steps)\n\n1. **GROUND — build the dedup-set first.** Read the live workspace state (hooks in\n   `~\u002F.claude\u002Fhooks` + `settings.json`, skills, `~\u002F.mcp.json`, `MEMORY.md`, the\n   `AGENTIC-PERFECTION-PLAN.md` \u002F `OPEN-THREADS.md` \u002F `CONSOLIDATED-GEM-DECISIONS.md` docs)\n   and recall memory. Assemble the explicit lists: **BUILT · PLANNED-unbuilt · ABSORBED ·\n   ALREADY-FOUND-this-hunt**. Every lens agent gets this set so it dedups instead of\n   re-proposing what exists. Without it, 80% of finds are duplicates.\n\n2. **FAN OUT — one agent per DISTINCT lens** (the menu that works; pick\u002Fscale to the ask,\n   default 6-9, go to 15-20+ for \"be exhaustive\"):\n   - **cross-domain borrows** — mechanisms from unmined fields (clinical medicine, intel\n\n### The anti-overfit meta-anchor (gate every adopt decision)\n### Hard-won lessons (do these, they cost real reruns to learn)\n### Deliverable\n","# Gem-Hunt — extensive multi-lens workspace self-improvement sweep\n\nThe repeatable form of the process that produced the agentic-perfection gems (open-loops,\ncontraindication-registry, iatrogenics-gate, the closed self-improvement loop, ACE, …).\nRe-run it whenever the landscape moves (new papers, new tools, new domains) — the lenses\nand discipline below are the winning formula; only the findings change.\n\n**Core philosophy (the user's standing intent):** fan out **LARGE** and wide — *\"there's no\nreason to limit the search; a gold gem unfound is a waste.\"* Breadth-first across diverse,\nindependent lenses beats one deep pass, because the best finds come from angles you wouldn't\nhave prompted for. Be adversarially honest, cite, grade confidence, and converge to a\ndecision the user steers — never silently adopt.\n\n## The method (7 steps)\n\n1. **GROUND — build the dedup-set first.** Read the live workspace state (hooks in\n   `~\u002F.claude\u002Fhooks` + `settings.json`, skills, `~\u002F.mcp.json`, `MEMORY.md`, the\n   `AGENTIC-PERFECTION-PLAN.md` \u002F `OPEN-THREADS.md` \u002F `CONSOLIDATED-GEM-DECISIONS.md` docs)\n   and recall memory. Assemble the explicit lists: **BUILT · PLANNED-unbuilt · ABSORBED ·\n   ALREADY-FOUND-this-hunt**. Every lens agent gets this set so it dedups instead of\n   re-proposing what exists. Without it, 80% of finds are duplicates.\n\n2. **FAN OUT — one agent per DISTINCT lens** (the menu that works; pick\u002Fscale to the ask,\n   default 6-9, go to 15-20+ for \"be exhaustive\"):\n   - **cross-domain borrows** — mechanisms from unmined fields (clinical medicine, intel\n\n### The anti-overfit meta-anchor (gate every adopt decision)\n### Hard-won lessons (do these, they cost real reruns to learn)\n### Deliverable\n",{"name":5,"description":7},"main","a298c929b6cbd662e1fce54302ce520d5ceea1a5","platform\u002Frouting\u002Ffixtures\u002Fhome\u002F.agents\u002Fskills\u002Fgem-hunt","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain","https:\u002F\u002Fgithub.com\u002FPrekzursil","2026-11-02 14:30:57",{"source":8,"skillName":5,"commands":51,"prompt":61,"zipAvailable":62},[52,55,58],{"tool":53,"command":54},"npx","npx skills add Prekzursil\u002Fagent-skills-toolchain --skill gem-hunt",{"tool":56,"command":57},"bunx","bunx skills add Prekzursil\u002Fagent-skills-toolchain --skill gem-hunt",{"tool":59,"command":60},"pnpm","pnpm dlx skills add Prekzursil\u002Fagent-skills-toolchain --skill gem-hunt","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Fplatform\u002Frouting\u002Ffixtures\u002Fhome\u002F.agents\u002Fskills\u002Fgem-hunt\u002FSKILL.md",true,[],[65,86,116,143,157,173],{"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":15,"licenseFileUrl":6,"sourceHtmlUrl":69,"categories":70,"keywords":71,"publishedAt":39},"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",[],[72,73,74,75,76,77,78,79,80,31,81,82,83,84,85],"clarify requirements","clarify","requirements","risk","options","task","prompts","goal","scanning","context","repo","injection","execution","file",{"skillNo":87,"name":88,"nameZh":6,"description":89,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":90,"categories":91,"keywords":97,"publishedAt":39},"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",[92],{"categoryNo":93,"categoryName":94,"taxonomyType":95,"taxonomyTypeDesc":96},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[98,99,32,100,101,102,103,104,105,106,107,108,109,110,31,111,112,113,114,115],"openmm md","how","pick","linux","analyze","tool","stack","open","NVIDIA","gpu","license","workflow","windows","free","molecular dynamics","local","do","MCP",{"skillNo":117,"name":118,"nameZh":6,"description":119,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":120,"categories":121,"keywords":128,"publishedAt":39},"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",[122,125],{"categoryNo":123,"categoryName":124,"taxonomyType":95,"taxonomyTypeDesc":96},"01JBSEEDCAT000000000000003","演示文稿",{"categoryNo":126,"categoryName":127,"taxonomyType":95,"taxonomyTypeDesc":96},"01JBSEEDCAT000000000000008","测试与质量",[129,130,131,132,133,134,135,136,137,138,99,139,140,141,142],"review","visual","visual review","pages","web","false","iteration","take","check","slides","ui","screenshot","playwright","screenshots",{"skillNo":144,"name":145,"nameZh":6,"description":146,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":147,"categories":148,"keywords":149,"publishedAt":39},"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",[],[145,150,151,152,153,154,155,156],"setup","report","project","installation","project setup","issues","state",{"skillNo":158,"name":159,"nameZh":6,"description":160,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":161,"categories":162,"keywords":164,"publishedAt":39},"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",[163],{"categoryNo":93,"categoryName":94,"taxonomyType":95,"taxonomyTypeDesc":96},[159,165,77,166,167,168,31,169,170,171,172],"start issue","issue","ready","work on issue","user","work","work on","development",{"skillNo":174,"name":150,"nameZh":6,"description":175,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":176,"categories":177,"keywords":178,"publishedAt":39},"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",[],[150,152,113,179,154,180],"files","interactive"]