[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6C22YWKSWTJ0CFDS3YEAQ7S":3,"skill-same:01M6C22YWKSWTJ0CFDS3YEAQ7S":113},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":37,"linkOnly":38,"markdownContent":39,"markdownBody":40,"frontMatter":41,"refName":47,"commitSha":48,"skillDirectory":49,"forksCount":13,"repositoryHtmlUrl":50,"repositoryHomepageUrl":6,"ownerHtmlUrl":51,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":52,"install":53,"resources":66},"01M6C22YWKSWTJ0CFDS3YEAQ7S","roast",null,"Use when someone asks to roast an idea, pressure-test or stress-test an idea, validate a business idea, \"convene the panel\", get a brutal second opinion before building something, or says \"\u002Froast\". Spins up a 5-angle panel (Critic, Champion, Analyst, Investigator, Customer) that attacks the idea from every angle, then a Judge returns one GO \u002F RESHAPE \u002F KILL verdict with the cheapest test to de-risk it.","mne20114-hash\u002Fgest35bi","mne20114-hash","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F224168109?v=4","01M6C0JCR7334CZ39YWTZXX2NG","01M6C0JCWN0NBWMQTW1CPG2Z4G",0,"MIT","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast\u002FSKILL.md",[],[5,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36],"first","use","business","context","boardroom","andreessen","before building","persona","critic","go","risk","Tools","pipeline","Enterprise","onboarding","second opinion","validate","test","customer","2026-11-10 10:12:30",false,"---\nname: roast\ndescription: Use when someone asks to roast an idea, pressure-test or stress-test an idea, validate a business idea, \"convene the panel\", get a brutal second opinion before building something, or says \"\u002Froast\". Spins up a 5-angle panel (Critic, Champion, Analyst, Investigator, Customer) that attacks the idea from every angle, then a Judge returns one GO \u002F RESHAPE \u002F KILL verdict with the cheapest test to de-risk it.\nargument-hint: \"[the idea to roast]\"\nlicense: MIT\nmetadata:\n  version: 1.0.0\n  build_pattern: \"Path-B persona skill — adversarial panel + deterministic verdict tools\"\n  distinct_from: \"andreessen (single market-first lens, not a panel); c-level boardroom (enterprise C-suite pipeline requiring company-context onboarding); grill-me (interrogates, no verdict)\"\n---\n\n# Roast — 5-Angle Idea Panel → One Verdict\n\n> **Portability:** Reasoning-led skill with 3 stdlib Python tools. No external APIs, no LLM calls in\n> scripts. Works in Claude Code CLI and Claude.ai web. The panel does the depth; the Judge does the call.\n\n## What this does\n\nClaude's default is to agree with you. `\u002Froast` is the opposite. It convenes a panel of five\nindependent reviewers — **The Critic, The Champion, The Analyst, The Investigator, and The\nCustomer** — who tear an idea apart and build it up from every angle, then a Judge synthesizes\neverything into one honest verdict. Use it before you sink time and money into building the wrong\nthing.\n\nThe panel is adversarial on purpose. No reviewer is allowed to hedge or be polite. The point is to\nsurface what you can't see because you're too close to it.\n\n## Step 1 — Frame the idea\n\nIf `$ARGUMENTS` contains the idea, start there. Then ask the user a tight set of clarifying\nquestions so the panel has real context to work with. Ask only what hasn't already been provided.\nKeep it to 3-4 questions max, in one batch:\n\n1. **The idea** in one or two sentences (what it is, what it does).\n2. **Who it's for** and **how it makes money** (the buyer + the price\u002Fmodel).\n3. **Your edge** — relevant skills, audience, or assets you already have.\n4. **Constraints** — budget, timeline, how fast you need first dollar.\n\nIf the user says \"just run it\" or gives you enough already, skip the questions and proceed. Don't\nover-interrogate. One round, then run the panel.\n\nAssemble the brief with `scripts\u002Fbrief_builder.py` — it normalizes the four load-bearing inputs into\none paragraph and tells you if anything critical is still missing before you spend five subagents:\n\n```bash\npython scripts\u002Fbrief_builder.py \\\n  --idea \"AI that drafts grant applications for small nonprofits from a 10-min intake call\" \\\n  --who \"1-3 person nonprofits with no grant writer\" \\\n  --money \"$99\u002Fmo SaaS\" --edge \"I ran a nonprofit for 8 years\" \\\n  --constraints \"bootstrapped, first dollar in 30 days\"\n```\n\nPaste the resulting brief verbatim into every panelist's prompt, so all five judge the same thing.\n\n## Step 2 — Run the 5-angle panel (5 reviewers, in parallel)\n\nSpin up **all five reviewers in parallel in a single message** (one Task call each,\n`subagent_type: general-purpose`). Paste the same brief into each, then give each its mandate below.\n\nEach panelist must return: a one-line stance, their 3-5 sharpest points, the single most important\nthing the user must hear, and a 1-10 score on their own dimension (1 = walk away, 10 = no-brainer).\n\n**1. The Critic — \"What kills this?\"**\n> You are The Critic on an idea panel. Assume this idea fails. Your job is to find the fatal flaws, the fastest way it dies, and the load-bearing assumptions that are probably wrong. Be ruthless and specific. No hedging, no \"but it could work.\" Attack the weakest points. THE BRIEF: [brief]\n\n**2. The Champion — \"What's the 10x upside?\"**\n> You are The Champion on an idea panel. Make the strongest possible case FOR this idea. Find the biggest upside, the 10x version, the adjacent opportunities and unlock points the founder isn't seeing. Fight for the potential. Be specific about where the real money and leverage could be. THE BRIEF: [brief]\n\n**3. The Analyst — \"Does the logic actually hold?\"**\n> You are The Analyst on an idea panel. Use NO outside research and NO web. Reason purely from first principles: does the core mechanism make sense, do the incentives line up, is the underlying logic sound, does the math even work in theory? Strip it to fundamentals and tell us if it holds together. THE BRIEF: [brief]\n\n**4. The Investigator — \"What does the real market say?\"**\n> You are The Investigator on an idea panel. Use web search. Bring real-world evidence: who the existing competitors are, market size or demand signals, what comparable products charge, whether this is validated by what's already out there or contradicted by it. Cite what you find. Is the real world saying yes or no? THE BRIEF: [brief]\n\n**5. The Customer — \"Would I actually pay?\"**\n> You are The Customer on an idea panel. Role-play the exact target customer described in the brief. React as them, in first person. Would you actually pay for this? What's your real objection? What would make you choose a competitor or just do nothing instead? What price feels right, and what would make you say yes today? Be the honest, slightly skeptical customer, not a cheerleader. THE BRIEF: [brief]\n\n## Step 3 — Call the verdict\n\nOnce all five return, YOU act as the Judge. Read every panelist's findings, weigh them, and\nsynthesize one decisive verdict. **Do not just average the scores.** Run the five scores through the\nsynthesizer so the call is reproducible weighting, not vibes — then name the real tension between the\nreviewers and resolve it in prose:\n\n```bash\npython scripts\u002Fverdict_synthesizer.py \\\n  --critic 4 --champion 8 --analyst 7 --investigator 5 --customer 6\n```\n\nThe tool weights demand (Customer) and survival (Critic) heaviest and the bull (Champion) lightest,\napplies hard gates (a Customer who won't pay, or a fatal flaw the Critic landed, vetoes a GO), and\nflags the widest disagreement as the tension you must resolve. Use its verdict + confidence as your\nspine; write the prose yourself.\n\nFold in the **economics lens** yourself: rough pricing, realistic time-to-first-dollar, and whether\nthe user can actually ship this fast given the edge they described. Then design the cheapest test\nfrom the riskiest assumption the panel surfaced:\n\n```bash\npython scripts\u002Fcheapest_test_designer.py --risk price --price 99\n```\n\nOutput the verdict in this exact shape:\n\n```\n## THE VERDICT: GO \u002F RESHAPE \u002F KILL\nConfidence: [low \u002F medium \u002F high]\n\n**The call in one line:** [the decision, plainly]\n\n**Why:** [2-3 sentences resolving the panel's tension]\n\n**Biggest risk:** [the single thing most likely to kill it]\n**Biggest upside:** [the strongest reason to do it]\n\n**Money read:** [rough price, time-to-first-dollar, can they ship fast]\n\n**The cheapest 48-hour test:** [the smallest, fastest thing they can do\nto validate the riskiest assumption BEFORE building anything]\n\n**If RESHAPE:** [the specific pivot that fixes the fatal flaw while keeping the upside]\n```\n\nThen list the five panel scores in one line: `Critic X\u002F10 · Champion X\u002F10 · Analyst X\u002F10 · Investigator X\u002F10 · Customer X\u002F10`.\n\n## Tooling\n\n| Script | Role |\n|---|---|\n| `scripts\u002Fbrief_builder.py` | Normalizes the 4 load-bearing inputs into one shared brief; flags missing\u002Fthin inputs before the panel convenes. |\n| `scripts\u002Fverdict_synthesizer.py` | Weights the 5 panel scores (Customer + Critic heaviest, Champion lightest), applies veto gates, flags the real tension → GO \u002F RESHAPE \u002F KILL + confidence. |\n| `scripts\u002Fcheapest_test_designer.py` | Maps the riskiest assumption (demand\u002Fprice\u002Ffeasibility\u002Fdifferentiation\u002Fchannel\u002Fretention) to a concrete 48-hour test with pass\u002Ffail signals. |\n\n## References\n\n- [`references\u002Fadversarial_panel_canon.md`](references\u002Fadversarial_panel_canon.md) — why a diverse adversarial panel beats one reviewer (red-teaming, devil's advocacy, dialectical inquiry; 7 sources)\n- [`references\u002Fverdict_synthesis_method.md`](references\u002Fverdict_synthesis_method.md) — the weighting, the veto gates, and why you must not average (6 sources)\n- [`references\u002Fcheapest_test_canon.md`](references\u002Fcheapest_test_canon.md) — demand testing before building: smoke test, pre-sale, concierge, fake-door (7 sources)\n\n## Assets\n\n- [`assets\u002Froast_brief_worksheet.md`](assets\u002Froast_brief_worksheet.md) — fillable 4-input brief worksheet\n- [`assets\u002Fexample_roast_verdict.md`](assets\u002Fexample_roast_verdict.md) — a full worked roast (brief → 5 panel scores → tension → verdict → cheapest test)\n\n## Rules\n\n- Every reviewer stays in character. None of them hedges or softens. The value is in the friction.\n- The Judge must make an actual call. \"It depends\" is not a verdict. Pick GO, RESHAPE, or KILL and own it.\n- **Do not average the scores.** A high mean can hide a fatal split or a vetoed dimension — run the synthesizer and resolve the tension it names.\n- The cheapest 48-hour test is the most important output. It's how the user finds out if they're right without building the whole thing.\n- Keep the final verdict skimmable. The panel does the depth; the Judge does the decision.\n\n## Anti-Patterns To Reject\n\n- Softening the verdict to spare feelings (\"there's definitely something here…\"). If it's a KILL, say KILL.\n- Averaging the five scores into a mushy 6\u002F10 and calling it a day.\n- Letting the Champion's enthusiasm override a Customer who won't pay or a Critic who found the fatal flaw.\n- Ending on advice with no falsifiable test (\"go validate it\"). Name the test, the cost, and the pass\u002Ffail line.\n- Running the panel on a one-line brief so all five argue past each other.\n\n## Distinct From (don't reach for the wrong tool)\n\n- **`productivity\u002Fandreessen`** — a single market-first operator. `roast` is five independent lenses → a judge. Use andreessen when you specifically want the market-dominates thesis; use roast when you want 360° coverage.\n- **`c-level-advisor` boardroom \u002F `\u002Fcs:boardroom`** — an enterprise C-suite pipeline that needs `company-context.md` onboarding and outputs a board memo. `roast` is a zero-setup, solo-founder, 90-second gut check.\n- **`engineering\u002Fgrill-me`** — interrogates a plan one question at a time to reach shared understanding. It does not issue a GO\u002FKILL verdict. Roast judges; grill-me clarifies.\n\n---\n\n**Version:** 1.0.0\n**Build pattern:** Path-B persona skill — adversarial panel preserved + deterministic verdict tooling added.\n","# Roast — 5-Angle Idea Panel → One Verdict\n\n> **Portability:** Reasoning-led skill with 3 stdlib Python tools. No external APIs, no LLM calls in\n> scripts. Works in Claude Code CLI and Claude.ai web. The panel does the depth; the Judge does the call.\n\n## What this does\n\nClaude's default is to agree with you. `\u002Froast` is the opposite. It convenes a panel of five\nindependent reviewers — **The Critic, The Champion, The Analyst, The Investigator, and The\nCustomer** — who tear an idea apart and build it up from every angle, then a Judge synthesizes\neverything into one honest verdict. Use it before you sink time and money into building the wrong\nthing.\n\nThe panel is adversarial on purpose. No reviewer is allowed to hedge or be polite. The point is to\nsurface what you can't see because you're too close to it.\n\n## Step 1 — Frame the idea\n\nIf `$ARGUMENTS` contains the idea, start there. Then ask the user a tight set of clarifying\nquestions so the panel has real context to work with. Ask only what hasn't already been provided.\nKeep it to 3-4 questions max, in one batch:\n\n1. **The idea** in one or two sentences (what it is, what it does).\n2. **Who it's for** and **how it makes money** (the buyer + the price\u002Fmodel).\n3. **Your edge** — relevant skills, audience, or assets you already have.\n4. **Constraints** — budget, timeline, how fast you need first dollar.\n\nIf the user says \"just run it\" or gives you enough already, skip the questions and proceed. Don't\nover-interrogate. One round, then run the panel.\n\nAssemble the brief with `scripts\u002Fbrief_builder.py` — it normalizes the four load-bearing inputs into\none paragraph and tells you if anything critical is still missing before you spend five subagents:\n\n```bash\npython scripts\u002Fbrief_builder.py \\\n  --idea \"AI that drafts grant applications for small nonprofits from a 10-min intake call\" \\\n  --who \"1-3 person nonprofits with no grant writer\" \\\n  --money \"$99\u002Fmo SaaS\" --edge \"I ran a nonprofit for 8 years\" \\\n  --constraints \"bootstrapped, first dollar in 30 days\"\n```\n\nPaste the resulting brief verbatim into every panelist's prompt, so all five judge the same thing.\n\n## Step 2 — Run the 5-angle panel (5 reviewers, in parallel)\n\nSpin up **all five reviewers in parallel in a single message** (one Task call each,\n`subagent_type: general-purpose`). Paste the same brief into each, then give each its mandate below.\n\nEach panelist must return: a one-line stance, their 3-5 sharpest points, the single most important\nthing the user must hear, and a 1-10 score on their own dimension (1 = walk away, 10 = no-brainer).\n\n**1. The Critic — \"What kills this?\"**\n> You are The Critic on an idea panel. Assume this idea fails. Your job is to find the fatal flaws, the fastest way it dies, and the load-bearing assumptions that are probably wrong. Be ruthless and specific. No hedging, no \"but it could work.\" Attack the weakest points. THE BRIEF: [brief]\n\n**2. The Champion — \"What's the 10x upside?\"**\n> You are The Champion on an idea panel. Make the strongest possible case FOR this idea. Find the biggest upside, the 10x version, the adjacent opportunities and unlock points the founder isn't seeing. Fight for the potential. Be specific about where the real money and leverage could be. THE BRIEF: [brief]\n\n**3. The Analyst — \"Does the logic actually hold?\"**\n> You are The Analyst on an idea panel. Use NO outside research and NO web. Reason purely from first principles: does the core mechanism make sense, do the incentives line up, is the underlying logic sound, does the math even work in theory? Strip it to fundamentals and tell us if it holds together. THE BRIEF: [brief]\n\n**4. The Investigator — \"What does the real market say?\"**\n> You are The Investigator on an idea panel. Use web search. Bring real-world evidence: who the existing competitors are, market size or demand signals, what comparable products charge, whether this is validated by what's already out there or contradicted by it. Cite what you find. Is the real world saying yes or no? THE BRIEF: [brief]\n\n**5. The Customer — \"Would I actually pay?\"**\n> You are The Customer on an idea panel. Role-play the exact target customer described in the brief. React as them, in first person. Would you actually pay for this? What's your real objection? What would make you choose a competitor or just do nothing instead? What price feels right, and what would make you say yes today? Be the honest, slightly skeptical customer, not a cheerleader. THE BRIEF: [brief]\n\n## Step 3 — Call the verdict\n\nOnce all five return, YOU act as the Judge. Read every panelist's findings, weigh them, and\nsynthesize one decisive verdict. **Do not just average the scores.** Run the five scores through the\nsynthesizer so the call is reproducible weighting, not vibes — then name the real tension between the\nreviewers and resolve it in prose:\n\n```bash\npython scripts\u002Fverdict_synthesizer.py \\\n  --critic 4 --champion 8 --analyst 7 --investigator 5 --customer 6\n```\n\nThe tool weights demand (Customer) and survival (Critic) heaviest and the bull (Champion) lightest,\napplies hard gates (a Customer who won't pay, or a fatal flaw the Critic landed, vetoes a GO), and\nflags the widest disagreement as the tension you must resolve. Use its verdict + confidence as your\nspine; write the prose yourself.\n\nFold in the **economics lens** yourself: rough pricing, realistic time-to-first-dollar, and whether\nthe user can actually ship this fast given the edge they described. Then design the cheapest test\nfrom the riskiest assumption the panel surfaced:\n\n```bash\npython scripts\u002Fcheapest_test_designer.py --risk price --price 99\n```\n\nOutput the verdict in this exact shape:\n\n```\n## THE VERDICT: GO \u002F RESHAPE \u002F KILL\nConfidence: [low \u002F medium \u002F high]\n\n**The call in one line:** [the decision, plainly]\n\n**Why:** [2-3 sentences resolving the panel's tension]\n\n**Biggest risk:** [the single thing most likely to kill it]\n**Biggest upside:** [the strongest reason to do it]\n\n**Money read:** [rough price, time-to-first-dollar, can they ship fast]\n\n**The cheapest 48-hour test:** [the smallest, fastest thing they can do\nto validate the riskiest assumption BEFORE building anything]\n\n**If RESHAPE:** [the specific pivot that fixes the fatal flaw while keeping the upside]\n```\n\nThen list the five panel scores in one line: `Critic X\u002F10 · Champion X\u002F10 · Analyst X\u002F10 · Investigator X\u002F10 · Customer X\u002F10`.\n\n## Tooling\n\n| Script | Role |\n|---|---|\n| `scripts\u002Fbrief_builder.py` | Normalizes the 4 load-bearing inputs into one shared brief; flags missing\u002Fthin inputs before the panel convenes. |\n| `scripts\u002Fverdict_synthesizer.py` | Weights the 5 panel scores (Customer + Critic heaviest, Champion lightest), applies veto gates, flags the real tension → GO \u002F RESHAPE \u002F KILL + confidence. |\n| `scripts\u002Fcheapest_test_designer.py` | Maps the riskiest assumption (demand\u002Fprice\u002Ffeasibility\u002Fdifferentiation\u002Fchannel\u002Fretention) to a concrete 48-hour test with pass\u002Ffail signals. |\n\n## References\n\n- [`references\u002Fadversarial_panel_canon.md`](references\u002Fadversarial_panel_canon.md) — why a diverse adversarial panel beats one reviewer (red-teaming, devil's advocacy, dialectical inquiry; 7 sources)\n- [`references\u002Fverdict_synthesis_method.md`](references\u002Fverdict_synthesis_method.md) — the weighting, the veto gates, and why you must not average (6 sources)\n- [`references\u002Fcheapest_test_canon.md`](references\u002Fcheapest_test_canon.md) — demand testing before building: smoke test, pre-sale, concierge, fake-door (7 sources)\n\n## Assets\n\n- [`assets\u002Froast_brief_worksheet.md`](assets\u002Froast_brief_worksheet.md) — fillable 4-input brief worksheet\n- [`assets\u002Fexample_roast_verdict.md`](assets\u002Fexample_roast_verdict.md) — a full worked roast (brief → 5 panel scores → tension → verdict → cheapest test)\n\n## Rules\n\n- Every reviewer stays in character. None of them hedges or softens. The value is in the friction.\n- The Judge must make an actual call. \"It depends\" is not a verdict. Pick GO, RESHAPE, or KILL and own it.\n- **Do not average the scores.** A high mean can hide a fatal split or a vetoed dimension — run the synthesizer and resolve the tension it names.\n- The cheapest 48-hour test is the most important output. It's how the user finds out if they're right without building the whole thing.\n- Keep the final verdict skimmable. The panel does the depth; the Judge does the decision.\n\n## Anti-Patterns To Reject\n\n- Softening the verdict to spare feelings (\"there's definitely something here…\"). If it's a KILL, say KILL.\n- Averaging the five scores into a mushy 6\u002F10 and calling it a day.\n- Letting the Champion's enthusiasm override a Customer who won't pay or a Critic who found the fatal flaw.\n- Ending on advice with no falsifiable test (\"go validate it\"). Name the test, the cost, and the pass\u002Ffail line.\n- Running the panel on a one-line brief so all five argue past each other.\n\n## Distinct From (don't reach for the wrong tool)\n\n- **`productivity\u002Fandreessen`** — a single market-first operator. `roast` is five independent lenses → a judge. Use andreessen when you specifically want the market-dominates thesis; use roast when you want 360° coverage.\n- **`c-level-advisor` boardroom \u002F `\u002Fcs:boardroom`** — an enterprise C-suite pipeline that needs `company-context.md` onboarding and outputs a board memo. `roast` is a zero-setup, solo-founder, 90-second gut check.\n- **`engineering\u002Fgrill-me`** — interrogates a plan one question at a time to reach shared understanding. It does not issue a GO\u002FKILL verdict. Roast judges; grill-me clarifies.\n\n---\n\n**Version:** 1.0.0\n**Build pattern:** Path-B persona skill — adversarial panel preserved + deterministic verdict tooling added.\n",{"name":5,"license":14,"metadata":42,"description":7,"argument-hint":46},{"version":43,"build_pattern":44,"distinct_from":45},"1.0.0","Path-B persona skill — adversarial panel + deterministic verdict tools","andreessen (single market-first lens, not a panel); c-level boardroom (enterprise C-suite pipeline requiring company-context onboarding); grill-me (interrogates, no verdict)","[the idea to roast]","main","510dd2917e051cc953dc55f56fd6ef442aa01b38","claude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi","https:\u002F\u002Fgithub.com\u002Fmne20114-hash","2026-10-28 07:50:31",{"source":8,"skillName":5,"commands":54,"prompt":64,"zipAvailable":65},[55,58,61],{"tool":56,"command":57},"npx","npx skills add mne20114-hash\u002Fgest35bi --skill roast",{"tool":59,"command":60},"bunx","bunx skills add mne20114-hash\u002Fgest35bi --skill roast",{"tool":62,"command":63},"pnpm","pnpm dlx skills add mne20114-hash\u002Fgest35bi --skill roast","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast\u002FSKILL.md",true,[67,73,77,83,87,91,95,99,105,109],{"path":68,"resourceType":69,"resourceTypeDesc":70,"sizeBytes":71,"sourceHtmlUrl":72},"assets\u002Fexample_roast_verdict.md","ASSET","资产文件",3969,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast\u002Fassets\u002Fexample_roast_verdict.md",{"path":74,"resourceType":69,"resourceTypeDesc":70,"sizeBytes":75,"sourceHtmlUrl":76},"assets\u002Froast_brief_worksheet.md",1535,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast\u002Fassets\u002Froast_brief_worksheet.md",{"path":78,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":81,"sourceHtmlUrl":82},"README.md","REFERENCE","参考文档",1701,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast\u002FREADME.md",{"path":84,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":85,"sourceHtmlUrl":86},"references\u002Fadversarial_panel_canon.md",5668,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast\u002Freferences\u002Fadversarial_panel_canon.md",{"path":88,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":89,"sourceHtmlUrl":90},"references\u002Fboundaries.md",389,"https:\u002F\u002Fgithub.com\u002FNharu\u002Fcc-cmds\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Flint-interview-record-sections\u002FFAIL-11-reader-morning-report\u002Fskills\u002Fautopilot\u002Freferences\u002Fboundaries.md",{"path":92,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":93,"sourceHtmlUrl":94},"references\u002Fcheapest_test_canon.md",4475,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast\u002Freferences\u002Fcheapest_test_canon.md",{"path":96,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":97,"sourceHtmlUrl":98},"references\u002Fverdict_synthesis_method.md",5336,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast\u002Freferences\u002Fverdict_synthesis_method.md",{"path":100,"resourceType":101,"resourceTypeDesc":102,"sizeBytes":103,"sourceHtmlUrl":104},"scripts\u002Fbrief_builder.py","SCRIPT","脚本",5626,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast\u002Fscripts\u002Fbrief_builder.py",{"path":106,"resourceType":101,"resourceTypeDesc":102,"sizeBytes":107,"sourceHtmlUrl":108},"scripts\u002Fcheapest_test_designer.py",8413,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast\u002Fscripts\u002Fcheapest_test_designer.py",{"path":110,"resourceType":101,"resourceTypeDesc":102,"sizeBytes":111,"sourceHtmlUrl":112},"scripts\u002Fverdict_synthesizer.py",9919,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fproductivity\u002Froast\u002Fskills\u002Froast\u002Fscripts\u002Fverdict_synthesizer.py",[114,152,174,197,222,242],{"skillNo":115,"name":116,"nameZh":6,"description":117,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":118,"categories":119,"keywords":133,"publishedAt":37},"01M6C27N3H0F9RGG2KASPASH04","syllabus","Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Use when the user uploads a syllabus, course outline, or curriculum document and wants supplementary readings (e.g., 'create a reading list from this syllabus', 'find recent papers for my course') — even casual mentions with a syllabus attached should trigger this skill.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fsyllabus\u002Fskills\u002Fsyllabus\u002FSKILL.md",[120,125,128],{"categoryNo":121,"categoryName":122,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000002","文档处理","SCENARIO","使用场景",{"categoryNo":126,"categoryName":127,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":129,"categoryName":130,"taxonomyType":131,"taxonomyTypeDesc":132},"01JBSEEDCAT000000000000034","行政与办公人员","PROFESSION","适用职业",[116,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,19,151],"docx","pr","create","intake","search","audit","integrity","checkpoint","learning","js","format","direct","Rules","find","consensus","list","extract","outcomes",{"skillNo":153,"name":154,"nameZh":6,"description":155,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":156,"categories":157,"keywords":162,"publishedAt":37},"01M6C27DMGZ4D6ERNHSVA8H8RJ","pulse","Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X\u002FTwitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend\u002Fsentiment\u002Fproblems\u002Fopportunities\u002Fcomparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Use when the user requests multi-source recency intelligence on a topic (e.g., 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]'), and for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpulse\u002Fskills\u002Fpulse\u002FSKILL.md",[158,161],{"categoryNo":159,"categoryName":160,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":126,"categoryName":127,"taxonomyType":123,"taxonomyTypeDesc":124},[154,163,164,135,165,137,139,166,167,140,168,169,170,171,145,146,172,147,173,19],"research","web","sentiment analysis","sentiment","Citations","analysis","discovery","open","tool","twitter","user",{"skillNo":175,"name":176,"nameZh":6,"description":177,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":178,"categories":179,"keywords":185,"publishedAt":37},"01M6C279M59X635VPD6Y9R616J","patent","Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search \u002F freedom-to-operate \u002F competitive landscape \u002F acquisition diligence \u002F litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Use when the user asks for patent searching or analysis (e.g., 'prior art search for [invention]', 'freedom to operate analysis for [product]'). Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002FSKILL.md",[180,181,182],{"categoryNo":121,"categoryName":122,"taxonomyType":123,"taxonomyTypeDesc":124},{"categoryNo":126,"categoryName":127,"taxonomyType":123,"taxonomyTypeDesc":124},{"categoryNo":183,"categoryName":184,"taxonomyType":131,"taxonomyTypeDesc":132},"01JBSEEDCAT000000000000037","律师与法务",[176,134,135,186,187,188,137,138,139,168,189,190,191,146,192,193,194,195,19,196],"competitive landscape","routing","product","commits","Word","text","acquisition","decisions","strategy","coverage","advice",{"skillNo":198,"name":199,"nameZh":6,"description":200,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":201,"categories":202,"keywords":207,"publishedAt":37},"01M6C275RZWNRB3CCB14QQM7ES","notebooklm","Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio\u002FVideo Overviews, Mind Maps, Reports incl. Briefing Doc\u002FStudy Guide\u002FFAQ, Flashcards, Quiz, slide decks, infographics — discover the exact set from the live Studio panel; the UI evolves fast), and creating new notebooks. Requires browser automation environment — fails gracefully when unavailable.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fnotebooklm\u002Fskills\u002Fnotebooklm\u002FSKILL.md",[203,206],{"categoryNo":204,"categoryName":205,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":126,"categoryName":127,"taxonomyType":123,"taxonomyTypeDesc":124},[199,208,209,163,210,211,212,213,214,215,216,217,170,191,145,218,219,220,221,19],"google","browser automation","automation","generate","browser","fast","SET","doc","Video","Audio","check","ask","environment","overview",{"skillNo":223,"name":224,"nameZh":6,"description":225,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":226,"categories":227,"keywords":232,"publishedAt":37},"01M6C2717B0QDJ3Y4PJP77BMW5","litreview","Academic literature orientation skill that searches papers via free keyless APIs (PubMed E-utilities + OpenAlex) by default — with the Consensus MCP as an optional enhancement lane when connected — builds a strategic search plan using PICO (default) or SPIDER \u002F Decomposition \u002F hybrid as fallbacks, and synthesizes findings into a formatted Word (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5\u002F10\u002F20 queries) controls coverage vs. speed. Output is a 'launching pad' — an orientation guide that lets a researcher dive in confidently, not a finished review. Use when the user starts literature-oriented research (e.g., 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'). Do NOT use for single one-off paper searches wanting a quick list — that's a plain PubMed\u002FOpenAlex (or Consensus) query.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Flitreview\u002Fskills\u002Flitreview\u002FSKILL.md",[228,229,230,231],{"categoryNo":121,"categoryName":122,"taxonomyType":123,"taxonomyTypeDesc":124},{"categoryNo":159,"categoryName":160,"taxonomyType":123,"taxonomyTypeDesc":124},{"categoryNo":126,"categoryName":127,"taxonomyType":123,"taxonomyTypeDesc":124},{"categoryNo":129,"categoryName":130,"taxonomyType":131,"taxonomyTypeDesc":132},[224,134,233,234,235,135,137,138,236,237,238,141,239,190,240,146,148,241,195,19],"MCP","writing","review","lane","keyless","literature review","plan","researcher","question",{"skillNo":243,"name":244,"nameZh":6,"description":245,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":246,"categories":247,"keywords":252,"publishedAt":37},"01M6C26X5G3WDVWQ40Y16ZS19F","grants","NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance\u002FInnovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget\u002Fscope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation. Use when the user asks about research funding or makes any grant-related request (e.g., 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research'). NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fgrants\u002Fskills\u002Fgrants\u002FSKILL.md",[248,249,250,251],{"categoryNo":121,"categoryName":122,"taxonomyType":123,"taxonomyTypeDesc":124},{"categoryNo":159,"categoryName":160,"taxonomyType":123,"taxonomyTypeDesc":124},{"categoryNo":126,"categoryName":127,"taxonomyType":123,"taxonomyTypeDesc":124},{"categoryNo":129,"categoryName":130,"taxonomyType":131,"taxonomyTypeDesc":132},[244,134,163,135,253,137,138,139,254,255,140,168,190,146,147,148,194,220,19,256],"help","data","Budget","innovation"]