[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DCWE9G1XD7KMH9DCTFT9CJ":3,"skill-same:01M6DCWE9G1XD7KMH9DCTFT9CJ":58},{"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":23,"publishedAt":33,"linkOnly":34,"markdownContent":35,"markdownBody":36,"frontMatter":37,"refName":38,"commitSha":39,"skillDirectory":40,"forksCount":14,"repositoryHtmlUrl":41,"repositoryHomepageUrl":6,"ownerHtmlUrl":42,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":43,"install":44,"resources":57},"01M6DCWE9G1XD7KMH9DCTFT9CJ","recall-workflow-agent",null,"Use when you need the exact input PROMPT or final OUTPUT of a specific subagent from a past Workflow \u002F ultracode fan-out run — reviewing or recovering what one fanned-out agent (a lens, a verifier, the synthesizer) actually received or returned after the run scrolled off screen or the session compacted. Identify it by a distinctive phrase from its prompt or output, the workflow name, or by listing the run's agents.","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\u002Frecall-workflow-agent\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32],"workflow","recall","recall workflow agent","run","subagent","prompt","session","use","verifier","2026-11-10 10:12:30",false,"---\nname: recall-workflow-agent\ndescription: Use when you need the exact input PROMPT or final OUTPUT of a specific subagent from a past Workflow \u002F ultracode fan-out run — reviewing or recovering what one fanned-out agent (a lens, a verifier, the synthesizer) actually received or returned after the run scrolled off screen or the session compacted. Identify it by a distinctive phrase from its prompt or output, the workflow name, or by listing the run's agents.\n---\n\n# recall-workflow-agent\n\n## Overview\nEvery Workflow subagent's full transcript is written to disk as JSONL. To get one agent's prompt + output you locate its `agent-\u003Cid>.jsonl` and read it — you do NOT re-run the workflow or ask the user. **The reliable locator is a distinctive PHRASE, because the readable agent label is not stored on disk.**\n\n## Where it lives\n```\n~\u002F.claude\u002Fprojects\u002F\u003Cproject>\u002F\u003Csession>\u002Fsubagents\u002Fworkflows\u002F\u003Cwf_id>\u002F\n    journal.jsonl          # per agent: {type, key:\u003CHASH>, agentId, result:\u003Cthe OUTPUT>}\n    agent-\u003CagentId>.jsonl  # per agent: full transcript (prompt = its user msg; + turns)\n~\u002F.claude\u002Fprojects\u002F\u003COTHER-project>\u002F\u003Csession>\u002Fworkflows\u002Fscripts\u002F\u003Cname>-\u003Cwf_id>.js   # the script (holds the labels)\n```\n**Gotcha:** the transcript dir is under the SESSION's project, which is frequently a *different* `\u003Cproject>` than where the `.js` script lives. Never assume co-location — a phrase grep finds it wherever it is.\n\n## Do this — the bundled tool locates + extracts + saves the files\n```bash\nS=~\u002F.agents\u002Fskills\u002Frecall-workflow-agent\u002Fscripts\u002Fextract_workflow_agent.py\n# best: a phrase you SAW in the output, or a phrase from the prompt\u002Flens task:\npython \"$S\" --phrase \"Vaporware-filtered maturity table\" --slug decision --print\n# don't know a phrase? list every agent in the run (previewed by its report HEADLINE), then pick:\npython \"$S\" --workflow multiai-orchestration-research --list\n# scope a phrase to one run if it's ambiguous:\npython \"$S\" --workflow \u003Cname> --phrase \"\u003Cdistinctive>\"\n\n### Identify by (most→least reliable)\n### Common mistakes\n","# recall-workflow-agent\n\n## Overview\nEvery Workflow subagent's full transcript is written to disk as JSONL. To get one agent's prompt + output you locate its `agent-\u003Cid>.jsonl` and read it — you do NOT re-run the workflow or ask the user. **The reliable locator is a distinctive PHRASE, because the readable agent label is not stored on disk.**\n\n## Where it lives\n```\n~\u002F.claude\u002Fprojects\u002F\u003Cproject>\u002F\u003Csession>\u002Fsubagents\u002Fworkflows\u002F\u003Cwf_id>\u002F\n    journal.jsonl          # per agent: {type, key:\u003CHASH>, agentId, result:\u003Cthe OUTPUT>}\n    agent-\u003CagentId>.jsonl  # per agent: full transcript (prompt = its user msg; + turns)\n~\u002F.claude\u002Fprojects\u002F\u003COTHER-project>\u002F\u003Csession>\u002Fworkflows\u002Fscripts\u002F\u003Cname>-\u003Cwf_id>.js   # the script (holds the labels)\n```\n**Gotcha:** the transcript dir is under the SESSION's project, which is frequently a *different* `\u003Cproject>` than where the `.js` script lives. Never assume co-location — a phrase grep finds it wherever it is.\n\n## Do this — the bundled tool locates + extracts + saves the files\n```bash\nS=~\u002F.agents\u002Fskills\u002Frecall-workflow-agent\u002Fscripts\u002Fextract_workflow_agent.py\n# best: a phrase you SAW in the output, or a phrase from the prompt\u002Flens task:\npython \"$S\" --phrase \"Vaporware-filtered maturity table\" --slug decision --print\n# don't know a phrase? list every agent in the run (previewed by its report HEADLINE), then pick:\npython \"$S\" --workflow multiai-orchestration-research --list\n# scope a phrase to one run if it's ambiguous:\npython \"$S\" --workflow \u003Cname> --phrase \"\u003Cdistinctive>\"\n\n### Identify by (most→least reliable)\n### Common mistakes\n",{"name":5,"description":7},"main","a298c929b6cbd662e1fce54302ce520d5ceea1a5","platform\u002Frouting\u002Ffixtures\u002Fhome\u002F.agents\u002Fskills\u002Frecall-workflow-agent","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain","https:\u002F\u002Fgithub.com\u002FPrekzursil","2026-11-02 14:30:57",{"source":8,"skillName":5,"commands":45,"prompt":55,"zipAvailable":56},[46,49,52],{"tool":47,"command":48},"npx","npx skills add Prekzursil\u002Fagent-skills-toolchain --skill recall-workflow-agent",{"tool":50,"command":51},"bunx","bunx skills add Prekzursil\u002Fagent-skills-toolchain --skill recall-workflow-agent",{"tool":53,"command":54},"pnpm","pnpm dlx skills add Prekzursil\u002Fagent-skills-toolchain --skill recall-workflow-agent","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\u002Frecall-workflow-agent\u002FSKILL.md",true,[],[59,80,106,133,147,163],{"skillNo":60,"name":61,"nameZh":6,"description":62,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":63,"categories":64,"keywords":65,"publishedAt":33},"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",[],[66,67,68,69,70,71,72,73,74,31,75,76,77,78,79],"clarify requirements","clarify","requirements","risk","options","task","prompts","goal","scanning","context","repo","injection","execution","file",{"skillNo":81,"name":82,"nameZh":6,"description":83,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":84,"categories":85,"keywords":87,"publishedAt":33},"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",[86],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[88,89,90,91,92,93,94,95,96,97,98,99,24,100,31,101,102,103,104,105],"openmm md","how","decision","pick","linux","analyze","tool","stack","open","NVIDIA","gpu","license","windows","free","molecular dynamics","local","do","MCP",{"skillNo":107,"name":108,"nameZh":6,"description":109,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":110,"categories":111,"keywords":118,"publishedAt":33},"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",[112,115],{"categoryNo":113,"categoryName":114,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000003","演示文稿",{"categoryNo":116,"categoryName":117,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",[119,120,121,122,123,124,125,126,127,128,89,129,130,131,132],"review","visual","visual review","pages","web","false","iteration","take","check","slides","ui","screenshot","playwright","screenshots",{"skillNo":134,"name":135,"nameZh":6,"description":136,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":137,"categories":138,"keywords":139,"publishedAt":33},"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",[],[135,140,141,142,143,144,145,146],"setup","report","project","installation","project setup","issues","state",{"skillNo":148,"name":149,"nameZh":6,"description":150,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":151,"categories":152,"keywords":154,"publishedAt":33},"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",[153],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[149,155,71,156,157,158,31,159,160,161,162],"start issue","issue","ready","work on issue","user","work","work on","development",{"skillNo":164,"name":140,"nameZh":6,"description":165,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":166,"categories":167,"keywords":168,"publishedAt":33},"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",[],[140,142,103,169,144,170],"files","interactive"]