[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6C1MCD2KAX3R3DTD20NSKGS":3,"skill-same:01M6C1MCD2KAX3R3DTD20NSKGS":121},{"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":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":53,"commitSha":54,"skillDirectory":55,"forksCount":13,"repositoryHtmlUrl":56,"repositoryHomepageUrl":6,"ownerHtmlUrl":57,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":58,"install":59,"resources":72},"01M6C1MCD2KAX3R3DTD20NSKGS","karpathy-coder",null,"Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. Triggers on \"review my diff\", \"check complexity\", \"am I overcomplicating this\", \"karpathy check\", \"before I commit\", or any code quality concern where the LLM might be overcoding.","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\u002Fengineering\u002Fkarpathy-coder\u002Fskills\u002Fkarpathy-coder\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"karpathy coder","coder","anti-patterns","writing","surgical-changes","simplicity","karpathy","discipline","use","karpathy check","check","code-quality","code","code quality","commit","codex","antigravity","gemini","cli","review","2026-11-10 10:12:30",false,"---\nname: karpathy-coder\ndescription: Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. Triggers on \"review my diff\", \"check complexity\", \"am I overcomplicating this\", \"karpathy check\", \"before I commit\", or any code quality concern where the LLM might be overcoding.\ncontext: fork\nversion: 2.9.0\nauthor: claude-code-skills\nlicense: MIT\ntags: [code-quality, discipline, karpathy, simplicity, surgical-changes, anti-patterns, review]\ncompatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]\n---\n\n# Karpathy Coder — Active Coding Discipline\n\nDerived from [Andrej Karpathy's observations](https:\u002F\u002Fx.com\u002Fkarpathy\u002Fstatus\u002F2015883857489522876) on LLM coding pitfalls. This is **not just guidelines** — it ships Python tools that detect violations, a review agent, a slash command, and a pre-commit hook.\n\n> \"The models make wrong assumptions on your behalf and just run along with them without checking. They don't manage their confusion, don't seek clarifications, don't surface inconsistencies, don't present tradeoffs, don't push back when they should.\"\n>\n> \"They really like to overcomplicate code and APIs, bloat abstractions, don't clean up dead code... implement a bloated construction over 1000 lines when 100 would do.\"\n>\n> \"LLMs are exceptionally good at looping until they meet specific goals... Don't tell it what to do, give it success criteria and watch it go.\"\n>\n> — Andrej Karpathy\n\n## The four principles\n\n### 1. Think Before Coding\n\n**Don't assume. Don't hide confusion. Surface tradeoffs.**\n\n- State assumptions explicitly. If uncertain, ask.\n- If multiple interpretations exist, present them — don't pick silently.\n- If a simpler approach exists, say so. Push back when warranted.\n- If something is unclear, stop. Name what's confusing. Ask.\n\n### 2. Simplicity First\n\n**Minimum code that solves the problem. Nothing speculative.**\n\n- No features beyond what was asked.\n- No abstractions for single-use code.\n- No \"flexibility\" or \"configurability\" that wasn't requested.\n- No error handling for impossible scenarios.\n- If you write 200 lines and it could be 50, rewrite it.\n\n**The test:** Would a senior engineer say this is overcomplicated? If yes, simplify.\n\n### 3. Surgical Changes\n\n**Touch only what you must. Clean up only your own mess.**\n\n- Don't \"improve\" adjacent code, comments, or formatting.\n- Don't refactor things that aren't broken.\n- Match existing style, even if you'd do it differently.\n- If you notice unrelated dead code, mention it — don't delete it.\n- Remove imports\u002Fvariables\u002Ffunctions that YOUR changes made unused.\n- Don't remove pre-existing dead code unless asked.\n\n**The test:** Every changed line should trace directly to the user's request.\n\n### 4. Goal-Driven Execution\n\n**Define success criteria. Loop until verified.**\n\n| Instead of... | Transform to... |\n|---|---|\n| \"Add validation\" | \"Write tests for invalid inputs, then make them pass\" |\n| \"Fix the bug\" | \"Write a test that reproduces it, then make it pass\" |\n| \"Refactor X\" | \"Ensure tests pass before and after\" |\n\nFor multi-step tasks, state a brief plan:\n\n```\n1. [Step] → verify: [check]\n2. [Step] → verify: [check]\n3. [Step] → verify: [check]\n```\n\n## Slash command\n\n`\u002Fkarpathy-check` — Run the full 4-principle review on your staged changes.\n\n## Python tools (`scripts\u002F`)\n\nAll tools are stdlib-only. Run with `--help`.\n\n| Script | What it detects |\n|---|---|\n| `complexity_checker.py` | Over-engineering: too many classes, deep nesting, high cyclomatic complexity, unused params, premature abstractions |\n| `diff_surgeon.py` | Diff noise: lines that don't trace to the stated goal — comment changes, style drift, drive-by refactors |\n| `assumption_linter.py` | Hidden assumptions in a plan: unasked features, missing clarifications, silent interpretation choices |\n| `goal_verifier.py` | Weak success criteria: vague plans without verifiable checks, missing test assertions |\n\n## Sub-agent\n\n`karpathy-reviewer` — Runs all 4 principles against a diff. Dispatched by `\u002Fkarpathy-check` or manually before committing.\n\n## Pre-commit hook\n\n`hooks\u002Fkarpathy-gate.sh` — runs `complexity_checker.py` and `diff_surgeon.py` on staged files. Warns (non-blocking) when violations are found. Wire it via `.claude\u002Fsettings.json` or Husky.\n\n## References\n\n- `references\u002Fkarpathy-principles.md` — the source quotes, deeper context, when to relax each principle\n- `references\u002Fanti-patterns.md` — 10+ before\u002Fafter examples across Python, TypeScript, and shell\n- `references\u002Fenforcement-patterns.md` — how to wire hooks, CI integration, team adoption\n\n## When to relax\n\nThese principles bias toward **caution over speed**. For trivial tasks (typo fixes, obvious one-liners), use judgment. The principles matter most on:\n\n- Non-trivial implementations (>20 lines changed)\n- Code you don't fully understand\n- Multi-step tasks with unclear requirements\n- Anything that will be reviewed by humans\n\n## Cross-tool compatibility\n\nInstalls via plugin for Claude Code. For other tools, copy the principles into your schema file:\n\n| Tool | Schema file |\n|---|---|\n| Claude Code | `CLAUDE.md` (auto-loaded by plugin) |\n| Codex CLI | `AGENTS.md` |\n| Cursor | `AGENTS.md` or `.cursorrules` |\n| Antigravity \u002F OpenCode \u002F Gemini CLI | `AGENTS.md` |\n\n## Related skills (chains via `context: fork`)\n\n- **`self-eval`** — honest quality scoring after completing work\n- **`code-reviewer`** — broader code review; karpathy-coder focuses on the 4 LLM-specific pitfalls\n- **`llm-wiki`** — compound knowledge; karpathy-coder ensures you don't overcomplicate while building it\n","# Karpathy Coder — Active Coding Discipline\n\nDerived from [Andrej Karpathy's observations](https:\u002F\u002Fx.com\u002Fkarpathy\u002Fstatus\u002F2015883857489522876) on LLM coding pitfalls. This is **not just guidelines** — it ships Python tools that detect violations, a review agent, a slash command, and a pre-commit hook.\n\n> \"The models make wrong assumptions on your behalf and just run along with them without checking. They don't manage their confusion, don't seek clarifications, don't surface inconsistencies, don't present tradeoffs, don't push back when they should.\"\n>\n> \"They really like to overcomplicate code and APIs, bloat abstractions, don't clean up dead code... implement a bloated construction over 1000 lines when 100 would do.\"\n>\n> \"LLMs are exceptionally good at looping until they meet specific goals... Don't tell it what to do, give it success criteria and watch it go.\"\n>\n> — Andrej Karpathy\n\n## The four principles\n\n### 1. Think Before Coding\n\n**Don't assume. Don't hide confusion. Surface tradeoffs.**\n\n- State assumptions explicitly. If uncertain, ask.\n- If multiple interpretations exist, present them — don't pick silently.\n- If a simpler approach exists, say so. Push back when warranted.\n- If something is unclear, stop. Name what's confusing. Ask.\n\n### 2. Simplicity First\n\n**Minimum code that solves the problem. Nothing speculative.**\n\n- No features beyond what was asked.\n- No abstractions for single-use code.\n- No \"flexibility\" or \"configurability\" that wasn't requested.\n- No error handling for impossible scenarios.\n- If you write 200 lines and it could be 50, rewrite it.\n\n**The test:** Would a senior engineer say this is overcomplicated? If yes, simplify.\n\n### 3. Surgical Changes\n\n**Touch only what you must. Clean up only your own mess.**\n\n- Don't \"improve\" adjacent code, comments, or formatting.\n- Don't refactor things that aren't broken.\n- Match existing style, even if you'd do it differently.\n- If you notice unrelated dead code, mention it — don't delete it.\n- Remove imports\u002Fvariables\u002Ffunctions that YOUR changes made unused.\n- Don't remove pre-existing dead code unless asked.\n\n**The test:** Every changed line should trace directly to the user's request.\n\n### 4. Goal-Driven Execution\n\n**Define success criteria. Loop until verified.**\n\n| Instead of... | Transform to... |\n|---|---|\n| \"Add validation\" | \"Write tests for invalid inputs, then make them pass\" |\n| \"Fix the bug\" | \"Write a test that reproduces it, then make it pass\" |\n| \"Refactor X\" | \"Ensure tests pass before and after\" |\n\nFor multi-step tasks, state a brief plan:\n\n```\n1. [Step] → verify: [check]\n2. [Step] → verify: [check]\n3. [Step] → verify: [check]\n```\n\n## Slash command\n\n`\u002Fkarpathy-check` — Run the full 4-principle review on your staged changes.\n\n## Python tools (`scripts\u002F`)\n\nAll tools are stdlib-only. Run with `--help`.\n\n| Script | What it detects |\n|---|---|\n| `complexity_checker.py` | Over-engineering: too many classes, deep nesting, high cyclomatic complexity, unused params, premature abstractions |\n| `diff_surgeon.py` | Diff noise: lines that don't trace to the stated goal — comment changes, style drift, drive-by refactors |\n| `assumption_linter.py` | Hidden assumptions in a plan: unasked features, missing clarifications, silent interpretation choices |\n| `goal_verifier.py` | Weak success criteria: vague plans without verifiable checks, missing test assertions |\n\n## Sub-agent\n\n`karpathy-reviewer` — Runs all 4 principles against a diff. Dispatched by `\u002Fkarpathy-check` or manually before committing.\n\n## Pre-commit hook\n\n`hooks\u002Fkarpathy-gate.sh` — runs `complexity_checker.py` and `diff_surgeon.py` on staged files. Warns (non-blocking) when violations are found. Wire it via `.claude\u002Fsettings.json` or Husky.\n\n## References\n\n- `references\u002Fkarpathy-principles.md` — the source quotes, deeper context, when to relax each principle\n- `references\u002Fanti-patterns.md` — 10+ before\u002Fafter examples across Python, TypeScript, and shell\n- `references\u002Fenforcement-patterns.md` — how to wire hooks, CI integration, team adoption\n\n## When to relax\n\nThese principles bias toward **caution over speed**. For trivial tasks (typo fixes, obvious one-liners), use judgment. The principles matter most on:\n\n- Non-trivial implementations (>20 lines changed)\n- Code you don't fully understand\n- Multi-step tasks with unclear requirements\n- Anything that will be reviewed by humans\n\n## Cross-tool compatibility\n\nInstalls via plugin for Claude Code. For other tools, copy the principles into your schema file:\n\n| Tool | Schema file |\n|---|---|\n| Claude Code | `CLAUDE.md` (auto-loaded by plugin) |\n| Codex CLI | `AGENTS.md` |\n| Cursor | `AGENTS.md` or `.cursorrules` |\n| Antigravity \u002F OpenCode \u002F Gemini CLI | `AGENTS.md` |\n\n## Related skills (chains via `context: fork`)\n\n- **`self-eval`** — honest quality scoring after completing work\n- **`code-reviewer`** — broader code review; karpathy-coder focuses on the 4 LLM-specific pitfalls\n- **`llm-wiki`** — compound knowledge; karpathy-coder ensures you don't overcomplicate while building 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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",[128,133,136],{"categoryNo":129,"categoryName":130,"taxonomyType":131,"taxonomyTypeDesc":132},"01JBSEEDCAT000000000000002","文档处理","SCENARIO","使用场景",{"categoryNo":134,"categoryName":135,"taxonomyType":131,"taxonomyTypeDesc":132},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":137,"categoryName":138,"taxonomyType":139,"taxonomyTypeDesc":140},"01JBSEEDCAT000000000000034","行政与办公人员","PROFESSION","适用职业",[124,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,26,159],"docx","pr","create","intake","search","audit","integrity","checkpoint","learning","js","format","direct","Rules","find","consensus","list","extract","outcomes",{"skillNo":161,"name":162,"nameZh":6,"description":163,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":164,"categories":165,"keywords":170,"publishedAt":38},"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",[166,169],{"categoryNo":167,"categoryName":168,"taxonomyType":131,"taxonomyTypeDesc":132},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":134,"categoryName":135,"taxonomyType":131,"taxonomyTypeDesc":132},[162,171,172,143,173,145,147,174,175,148,176,177,178,179,153,154,180,155,181,26],"research","web","sentiment analysis","sentiment","Citations","analysis","discovery","open","tool","twitter","user",{"skillNo":183,"name":184,"nameZh":6,"description":185,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":186,"categories":187,"keywords":193,"publishedAt":38},"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",[188,189,190],{"categoryNo":129,"categoryName":130,"taxonomyType":131,"taxonomyTypeDesc":132},{"categoryNo":134,"categoryName":135,"taxonomyType":131,"taxonomyTypeDesc":132},{"categoryNo":191,"categoryName":192,"taxonomyType":139,"taxonomyTypeDesc":140},"01JBSEEDCAT000000000000037","律师与法务",[184,142,143,194,195,196,145,146,147,176,197,198,199,154,200,201,202,203,26,204],"competitive landscape","routing","product","commits","Word","text","acquisition","decisions","strategy","coverage","advice",{"skillNo":206,"name":207,"nameZh":6,"description":208,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":209,"categories":210,"keywords":215,"publishedAt":38},"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",[211,214],{"categoryNo":212,"categoryName":213,"taxonomyType":131,"taxonomyTypeDesc":132},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":134,"categoryName":135,"taxonomyType":131,"taxonomyTypeDesc":132},[207,216,217,171,218,219,220,221,222,223,224,225,178,199,153,28,226,227,228,26],"google","browser automation","automation","generate","browser","fast","SET","doc","Video","Audio","ask","environment","overview",{"skillNo":230,"name":231,"nameZh":6,"description":232,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":233,"categories":234,"keywords":239,"publishedAt":38},"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",[235,236,237,238],{"categoryNo":129,"categoryName":130,"taxonomyType":131,"taxonomyTypeDesc":132},{"categoryNo":167,"categoryName":168,"taxonomyType":131,"taxonomyTypeDesc":132},{"categoryNo":134,"categoryName":135,"taxonomyType":131,"taxonomyTypeDesc":132},{"categoryNo":137,"categoryName":138,"taxonomyType":139,"taxonomyTypeDesc":140},[231,142,240,21,37,143,145,146,241,242,243,149,244,198,245,154,156,246,203,26],"MCP","lane","keyless","literature review","plan","researcher","question",{"skillNo":248,"name":249,"nameZh":6,"description":250,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":251,"categories":252,"keywords":257,"publishedAt":38},"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",[253,254,255,256],{"categoryNo":129,"categoryName":130,"taxonomyType":131,"taxonomyTypeDesc":132},{"categoryNo":167,"categoryName":168,"taxonomyType":131,"taxonomyTypeDesc":132},{"categoryNo":134,"categoryName":135,"taxonomyType":131,"taxonomyTypeDesc":132},{"categoryNo":137,"categoryName":138,"taxonomyType":139,"taxonomyTypeDesc":140},[249,142,171,143,258,145,146,147,259,260,148,176,198,154,155,156,202,227,26,261],"help","data","Budget","innovation"]