[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DBEMKJ520B365955YX9BPE":3,"skill-same:01M6DBEMKJ520B365955YX9BPE":75},{"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},"01M6DBEMKJ520B365955YX9BPE","grill-with-docs",null,"Use when stress-testing a plan against the workspace's domain knowledge and prior decisions - challenge terminology, sharpen fuzzy language, and write resolved decisions back. Use when the user says grill against our docs or decisions, or wants a glossary-aware design grill. NOT for a plain plan interview (use grill-me) or a program-scale scope (use grill-me-extensive).","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\u002Fgrill-with-docs\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"docs","grill with docs","grill","challenge","domain","me","terminology","back","grill-me","use","interview","write","testing","decisions","workspace","glossary","sharpen","plan","knowledge","design","2026-11-10 10:12:30",false,"---\nname: grill-with-docs\ndescription: Use when stress-testing a plan against the workspace's domain knowledge and prior decisions - challenge terminology, sharpen fuzzy language, and write resolved decisions back. Use when the user says grill against our docs or decisions, or wants a glossary-aware design grill. NOT for a plain plan interview (use grill-me) or a program-scale scope (use grill-me-extensive).\n---\n\n# Grill With Docs\n\n## Overview\n\nGrill a plan, but **grounded in the workspace's actual accumulated knowledge** instead of a per-repo glossary file. Pull the domain glossary and prior decisions from **basic-memory** (the semantic D: vault) and the **event-ledger**, challenge the plan against them, and write every resolved decision **back** into those same stores.\n\nThis beats grilling against a repo-local `CONTEXT.md` \u002F `docs\u002Fadr\u002F` set: the stores are cross-project, semantic, always current, and the SessionStart hook replays the ledger after compaction — so the grounding and the decisions both survive context loss.\n\n## This is a layer, not a new grill\n\nDo **not** re-implement the questioning loop. Run the existing grill for the cadence, then add the store-awareness on top:\n\n- Single plan -> `grill-me` (interview relentlessly, one question at a time, recommend each answer, explore the codebase instead of asking when a question is answerable).\n- Wide \u002F under-specified program -> `grill-me-extensive` (the 7-step method: scout, diverge, structure, foundation-first, one-at-a-time, capture, converge — plus its grill modes).\n\n`grill-with-docs` = those, plus the four domain moves and the load\u002Fcapture wiring below.\n\n## Before the grill — load the grounding\n\nRecall is the part everyone skips. Do it first so your challenges are grounded, not generic:\n\n- `mcp__basic-memory__search_notes` \u002F `mcp__basic-memory__build_context` for the domain glossary and prior decisions in this area; `mcp__basic-memory__recent_activity` for what changed lately.\n- Read recent **event-ledger** decisions (`~\u002F.claude\u002Fevent-ledger\u002F`, or `note.py` history) so you grill against what was already decided, not from a blank slate.\n\nIf a relevant term or decision already exists, that is your grounding. If the plan contradicts it, that is your **first** challenge.\n\n## During the grill — the four domain moves\n\nOne question at a time, each with your recommended answer (the grill-me discipline). Layer these in:\n\n1. **Challenge against the glossary.** A term that conflicts with the stored definition: call it out immediately. \"Memory defines 'cancellation' as X, but you seem to mean Y — which is it?\"\n2. **Sharpen fuzzy language.** Vague or overloaded term: propose a precise canonical term. \"You said 'account' — do you mean the Customer or the User? Those are different things.\"\n3. **Discuss concrete scenarios.** Stress-test domain relationships with specific edge-case scenarios that force precision about the boundaries between concepts.\n4. **Cross-reference the code.** When the user states how something works, check whether the code agrees. On a contradiction, surface it: \"Your code cancels entire Orders, but you just said partial cancellation is possible — which is right?\"\n\n## Capture decisions back — close the loop\n\nAs each decision crystallises, write it where the workspace looks for it — **inline, not batched** (long grills outlive a context window):\n\n- Decision \u002F rationale -> `python ~\u002F.claude\u002Fhooks\u002Fevent-ledger\u002Fnote.py --kind decision \"\u003Cresolved decision + why>\"`.\n- A dead-end ruled out -> `--kind failure` with falsifiable preconditions; a milestone that overturns a prior dead-end uses `--supersedes` so it is retired, not re-walked.\n- A durable glossary term or cross-project decision -> `mcp__basic-memory__write_note` so recall surfaces it on the next project.\n- **Temporal validity:** when a decision corrects an earlier one, mark the old note `superseded_by:` and the new one `valid_as_of:` (mirrors `note.py --supersedes`). Recall then surfaces current truth and retired dead-ends are not silently re-walked.\n\n## Why this beats CONTEXT.md \u002F ADR files\n\n- One semantic store across every project, not a per-repo glossary you forget to read or keep in sync.\n- Decisions land in the same ledger the SessionStart hook replays after compaction — they are recoverable, not stranded in a file.\n- No new file taxonomy to maintain; the stores already exist and auto-load on recall.\n\nIf a repo genuinely also wants a committed, human-readable glossary or ADR, you can still write one — but the stores are the source of truth, and the committed file is a derived artifact.\n\n---\n_Idea adapted from the `grill-with-docs` skill in https:\u002F\u002Fgithub.com\u002Fmattpocock\u002Fskills — MIT License, Copyright (c) 2026 Matt Pocock. This is a workspace-native rebuild: grounding and decision capture are rewired from CONTEXT.md\u002Fdocs\u002Fadr files to basic-memory + the event-ledger, and the grilling loop composes with grill-me \u002F grill-me-extensive rather than duplicating it. Original under MIT; full notice in LICENSE (this folder). Built 2026-06-30._\n","# Grill With Docs\n\n## Overview\n\nGrill a plan, but **grounded in the workspace's actual accumulated knowledge** instead of a per-repo glossary file. Pull the domain glossary and prior decisions from **basic-memory** (the semantic D: vault) and the **event-ledger**, challenge the plan against them, and write every resolved decision **back** into those same stores.\n\nThis beats grilling against a repo-local `CONTEXT.md` \u002F `docs\u002Fadr\u002F` set: the stores are cross-project, semantic, always current, and the SessionStart hook replays the ledger after compaction — so the grounding and the decisions both survive context loss.\n\n## This is a layer, not a new grill\n\nDo **not** re-implement the questioning loop. Run the existing grill for the cadence, then add the store-awareness on top:\n\n- Single plan -> `grill-me` (interview relentlessly, one question at a time, recommend each answer, explore the codebase instead of asking when a question is answerable).\n- Wide \u002F under-specified program -> `grill-me-extensive` (the 7-step method: scout, diverge, structure, foundation-first, one-at-a-time, capture, converge — plus its grill modes).\n\n`grill-with-docs` = those, plus the four domain moves and the load\u002Fcapture wiring below.\n\n## Before the grill — load the grounding\n\nRecall is the part everyone skips. Do it first so your challenges are grounded, not generic:\n\n- `mcp__basic-memory__search_notes` \u002F `mcp__basic-memory__build_context` for the domain glossary and prior decisions in this area; `mcp__basic-memory__recent_activity` for what changed lately.\n- Read recent **event-ledger** decisions (`~\u002F.claude\u002Fevent-ledger\u002F`, or `note.py` history) so you grill against what was already decided, not from a blank slate.\n\nIf a relevant term or decision already exists, that is your grounding. If the plan contradicts it, that is your **first** challenge.\n\n## During the grill — the four domain moves\n\nOne question at a time, each with your recommended answer (the grill-me discipline). Layer these in:\n\n1. **Challenge against the glossary.** A term that conflicts with the stored definition: call it out immediately. \"Memory defines 'cancellation' as X, but you seem to mean Y — which is it?\"\n2. **Sharpen fuzzy language.** Vague or overloaded term: propose a precise canonical term. \"You said 'account' — do you mean the Customer or the User? Those are different things.\"\n3. **Discuss concrete scenarios.** Stress-test domain relationships with specific edge-case scenarios that force precision about the boundaries between concepts.\n4. **Cross-reference the code.** When the user states how something works, check whether the code agrees. On a contradiction, surface it: \"Your code cancels entire Orders, but you just said partial cancellation is possible — which is right?\"\n\n## Capture decisions back — close the loop\n\nAs each decision crystallises, write it where the workspace looks for it — **inline, not batched** (long grills outlive a context window):\n\n- Decision \u002F rationale -> `python ~\u002F.claude\u002Fhooks\u002Fevent-ledger\u002Fnote.py --kind decision \"\u003Cresolved decision + why>\"`.\n- A dead-end ruled out -> `--kind failure` with falsifiable preconditions; a milestone that overturns a prior dead-end uses `--supersedes` so it is retired, not re-walked.\n- A durable glossary term or cross-project decision -> `mcp__basic-memory__write_note` so recall surfaces it on the next project.\n- **Temporal validity:** when a decision corrects an earlier one, mark the old note `superseded_by:` and the new one `valid_as_of:` (mirrors `note.py --supersedes`). Recall then surfaces current truth and retired dead-ends are not silently re-walked.\n\n## Why this beats CONTEXT.md \u002F ADR files\n\n- One semantic store across every project, not a per-repo glossary you forget to read or keep in sync.\n- Decisions land in the same ledger the SessionStart hook replays after compaction — they are recoverable, not stranded in a file.\n- No new file taxonomy to maintain; the stores already exist and auto-load on recall.\n\nIf a repo genuinely also wants a committed, human-readable glossary or ADR, you can still write one — but the stores are the source of truth, and the committed file is a derived artifact.\n\n---\n_Idea adapted from the `grill-with-docs` skill in https:\u002F\u002Fgithub.com\u002Fmattpocock\u002Fskills — MIT License, Copyright (c) 2026 Matt Pocock. This is a workspace-native rebuild: grounding and decision capture are rewired from CONTEXT.md\u002Fdocs\u002Fadr files to basic-memory + the event-ledger, and the grilling loop composes with grill-me \u002F grill-me-extensive rather than duplicating it. Original under MIT; full notice in LICENSE (this folder). Built 2026-06-30._\n",{"name":5,"description":7},"main","a298c929b6cbd662e1fce54302ce520d5ceea1a5",".agents\u002Fskills\u002Fgrill-with-docs","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 grill-with-docs",{"tool":56,"command":57},"bunx","bunx skills add Prekzursil\u002Fagent-skills-toolchain --skill grill-with-docs",{"tool":59,"command":60},"pnpm","pnpm dlx skills add Prekzursil\u002Fagent-skills-toolchain --skill grill-with-docs","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fgrill-with-docs\u002FSKILL.md",true,[64,69],{"path":65,"resourceType":65,"resourceTypeDesc":66,"sizeBytes":67,"sourceHtmlUrl":68},"LICENSE","许可证",1068,"https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fgrill-with-docs\u002FLICENSE",{"path":70,"resourceType":71,"resourceTypeDesc":72,"sizeBytes":73,"sourceHtmlUrl":74},"SKILL.sm","OTHER","其他",276,"https:\u002F\u002Fgithub.com\u002Fcrystian\u002Fskill-map\u002Fblob\u002Fmain\u002Ffixtures\u002Fdemo\u002F.claude\u002Fskills\u002Fcheck-links\u002FSKILL.sm",[76,97,128,155,169,185],{"skillNo":77,"name":78,"nameZh":6,"description":79,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":80,"categories":81,"keywords":82,"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",[],[83,84,85,86,87,88,89,90,91,28,92,93,94,95,96],"clarify requirements","clarify","requirements","risk","options","task","prompts","goal","scanning","context","repo","injection","execution","file",{"skillNo":98,"name":99,"nameZh":6,"description":100,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":101,"categories":102,"keywords":108,"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",[103],{"categoryNo":104,"categoryName":105,"taxonomyType":106,"taxonomyTypeDesc":107},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[109,110,111,112,113,114,115,116,117,118,119,120,121,122,28,123,124,125,126,127],"openmm md","how","decision","pick","linux","analyze","tool","stack","open","NVIDIA","gpu","license","workflow","windows","free","molecular dynamics","local","do","MCP",{"skillNo":129,"name":130,"nameZh":6,"description":131,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":132,"categories":133,"keywords":140,"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",[134,137],{"categoryNo":135,"categoryName":136,"taxonomyType":106,"taxonomyTypeDesc":107},"01JBSEEDCAT000000000000003","演示文稿",{"categoryNo":138,"categoryName":139,"taxonomyType":106,"taxonomyTypeDesc":107},"01JBSEEDCAT000000000000008","测试与质量",[141,142,143,144,145,146,147,148,149,150,110,151,152,153,154],"review","visual","visual review","pages","web","false","iteration","take","check","slides","ui","screenshot","playwright","screenshots",{"skillNo":156,"name":157,"nameZh":6,"description":158,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":159,"categories":160,"keywords":161,"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",[],[157,162,163,164,165,166,167,168],"setup","report","project","installation","project setup","issues","state",{"skillNo":170,"name":171,"nameZh":6,"description":172,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":173,"categories":174,"keywords":176,"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",[175],{"categoryNo":104,"categoryName":105,"taxonomyType":106,"taxonomyTypeDesc":107},[171,177,88,178,179,180,28,181,182,183,184],"start issue","issue","ready","work on issue","user","work","work on","development",{"skillNo":186,"name":162,"nameZh":6,"description":187,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":188,"categories":189,"keywords":190,"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",[],[162,164,125,191,166,192],"files","interactive"]