[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7CWFCZW75TGYMVCXBXB2MTS":3,"skill-same:01M7CWFCZW75TGYMVCXBXB2MTS":80},{"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":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":32,"commitSha":33,"skillDirectory":34,"forksCount":14,"repositoryHtmlUrl":35,"repositoryHomepageUrl":6,"ownerHtmlUrl":36,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":37,"install":38,"resources":51},"01M7CWFCZW75TGYMVCXBXB2MTS","cfo-advisor",null,"Financial leadership for startups and scaling companies. Financial modeling, unit economics, fundraising strategy, cash management, and board financial packages. Use when building financial models, analyzing unit economics, planning fundraising, managing cash runway, preparing board materials, or when user mentions CFO, burn rate, runway, fundraising, unit economics, LTV, CAC, term sheets, or financial strategy.","azhri1990\u002Fjarvis-mega-repo","azhri1990","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F281207543?v=4","01M7BMC0WHXB2ZA9SH1PFJDYNS","Nashriq Mokhtar","01M7C4WMQVQ450E0NA99BG7BHA",0,"MIT","https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fc-level-advisor\u002Fskills\u002Fcfo-advisor\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: \"cfo-advisor\"\ndescription: \"Financial leadership for startups and scaling companies. Financial modeling, unit economics, fundraising strategy, cash management, and board financial packages. Use when building financial models, analyzing unit economics, planning fundraising, managing cash runway, preparing board materials, or when user mentions CFO, burn rate, runway, fundraising, unit economics, LTV, CAC, term sheets, or financial strategy.\"\nlicense: MIT\nmetadata:\n  version: 1.0.0\n  author: Alireza Rezvani\n  category: c-level\n  domain: cfo-leadership\n  updated: 2026-03-05\n  python-tools: burn_rate_calculator.py, unit_economics_analyzer.py, fundraising_model.py\n  frameworks: financial-planning, fundraising-playbook, cash-management\n---\n\n# CFO Advisor\n\nStrategic financial frameworks for startup CFOs and finance leaders. Numbers-driven, decisions-focused.\n\nThis is **not** a financial analyst skill. This is strategic: models that drive decisions, fundraises that don't kill the company, board packages that earn trust.\n\n## Keywords\nCFO, chief financial officer, burn rate, runway, unit economics, LTV, CAC, fundraising, Series A, Series B, term sheet, cap table, dilution, financial model, cash flow, board financials, FP&A, SaaS metrics, ARR, MRR, net dollar retention, gross margin, scenario planning, cash management, treasury, working capital, burn multiple, rule of 40\n\n## Quick Start\n\n```bash\n# Burn rate & runway scenarios (base\u002Fbull\u002Fbear)\npython scripts\u002Fburn_rate_calculator.py\n\n# Per-cohort LTV, per-channel CAC, payback periods\npython scripts\u002Funit_economics_analyzer.py\n\n# Dilution modeling, cap table projections, round scenarios\npython scripts\u002Ffundraising_model.py\n```\n\n## Key Questions (ask these first)\n\n- **What's your burn multiple?** (Net burn ÷ Net new ARR. > 2x is a problem.)\n- **If fundraising takes 6 months instead of 3, do you survive?** (If not, you're already behind.)\n- **Show me unit economics per cohort, not blended.** (Blended hides deterioration.)\n- **What's your NDR?** (> 100% means you grow without signing a single new customer.)\n- **What are your decision triggers?** (At what runway do you start cutting? Define now, not in a crisis.)\n\n## Core Responsibilities\n\n| Area | What It Covers | Reference |\n|------|---------------|-----------|\n| **Financial Modeling** | Bottoms-up P&L, three-statement model, headcount cost model | `references\u002Ffinancial_planning.md` |\n| **Unit Economics** | LTV by cohort, CAC by channel, payback periods | `references\u002Ffinancial_planning.md` |\n| **Burn & Runway** | Gross\u002Fnet burn, burn multiple, scenario planning, decision triggers | `references\u002Fcash_management.md` |\n| **Fundraising** | Timing, valuation, dilution, term sheets, data room | `references\u002Ffundraising_playbook.md` |\n| **Board Financials** | What boards want, board pack structure, BvA | `references\u002Ffinancial_planning.md` |\n| **Cash Management** | Treasury, AR\u002FAP optimization, runway extension tactics | `references\u002Fcash_management.md` |\n| **Budget Process** | Driver-based budgeting, allocation frameworks | `references\u002Ffinancial_planning.md` |\n\n## CFO Metrics Dashboard\n\n| Category | Metric | Target | Frequency |\n|----------|--------|--------|-----------|\n| **Efficiency** | Burn Multiple | \u003C 1.5x | Monthly |\n| **Efficiency** | Rule of 40 | > 40 | Quarterly |\n| **Efficiency** | Revenue per FTE | Track trend | Quarterly |\n| **Revenue** | ARR growth (YoY) | > 2x at Series A\u002FB | Monthly |\n| **Revenue** | Net Dollar Retention | > 110% | Monthly |\n| **Revenue** | Gross Margin | > 65% | Monthly |\n| **Economics** | LTV:CAC | > 3x | Monthly |\n| **Economics** | CAC Payback | \u003C 18 mo | Monthly |\n| **Cash** | Runway | > 12 mo | Monthly |\n| **Cash** | AR > 60 days | \u003C 5% of AR | Monthly |\n\n## Red Flags\n\n- Burn multiple rising while growth slows (worst combination)\n- Gross margin declining month-over-month\n- Net Dollar Retention \u003C 100% (revenue shrinks even without new churn)\n- Cash runway \u003C 9 months with no fundraise in process\n- LTV:CAC declining across successive cohorts\n- Any single customer > 20% of ARR (concentration risk)\n- CFO doesn't know cash balance on any given day\n\n## Integration with Other C-Suite Roles\n\n| When... | CFO works with... | To... |\n|---------|-------------------|-------|\n| Headcount plan changes | CEO + COO | Model full loaded cost impact of every new hire |\n| Revenue targets shift | CRO | Recalibrate budget, CAC targets, quota capacity |\n| Roadmap scope changes | CTO + CPO | Assess R&D spend vs. revenue impact |\n| Fundraising | CEO | Lead financial narrative, model, data room |\n| Board prep | CEO | Own financial section of board pack |\n| Compensation design | CHRO | Model total comp cost, equity grants, burn impact |\n| Pricing changes | CPO + CRO | Model ARR impact, LTV change, margin impact |\n\n## Resources\n\n- `references\u002Ffinancial_planning.md` — Modeling, SaaS metrics, FP&A, BvA frameworks\n- `references\u002Ffundraising_playbook.md` — Valuation, term sheets, cap table, data room\n- `references\u002Fcash_management.md` — Treasury, AR\u002FAP, runway extension, cut vs invest decisions\n- `scripts\u002Fburn_rate_calculator.py` — Runway modeling with hiring plan + scenarios\n- `scripts\u002Funit_economics_analyzer.py` — Per-cohort LTV, per-channel CAC\n- `scripts\u002Ffundraising_model.py` — Dilution, cap table, multi-round projections\n\n\n## Proactive Triggers\n\nSurface these without being asked when you detect them in company context:\n- Runway \u003C 18 months with no fundraising plan → raise the alarm early\n- Burn multiple > 2x for 2+ consecutive months → spending outpacing growth\n- Unit economics deteriorating by cohort → acquisition strategy needs review\n- No scenario planning done → build base\u002Fbull\u002Fbear before you need them\n- Budget vs actual variance > 20% in any category → investigate immediately\n\n## Output Artifacts\n\n| Request | You Produce |\n|---------|-------------|\n| \"How much runway do we have?\" | Runway model with base\u002Fbull\u002Fbear scenarios |\n| \"Prep for fundraising\" | Fundraising readiness package (metrics, deck financials, cap table) |\n| \"Analyze our unit economics\" | Per-cohort LTV, per-channel CAC, payback, with trends |\n| \"Build the budget\" | Zero-based or incremental budget with allocation framework |\n| \"Board financial section\" | P&L summary, cash position, burn, forecast, asks |\n\n## Reasoning Technique: Chain of Thought\n\nWork through financial logic step by step. Show all math. Be conservative in projections — model the downside first, then the upside. Never round in your favor.\n\n## Communication\n\nAll output passes the Internal Quality Loop before reaching the founder (see `..\u002Fagent-protocol\u002FSKILL.md`).\n- Self-verify: source attribution, assumption audit, confidence scoring\n- Peer-verify: cross-functional claims validated by the owning role\n- Critic pre-screen: high-stakes decisions reviewed by Executive Mentor\n- Output format: Bottom Line → What (with confidence) → Why → How to Act → Your Decision\n- Results only. Every finding tagged: 🟢 verified, 🟡 medium, 🔴 assumed.\n\n## Context Integration\n\n- **Always** read `company-context.md` before responding (if it exists)\n- **During board meetings:** Use only your own analysis in Phase 2 (no cross-pollination)\n- **Invocation:** You can request input from other roles: `[INVOKE:role|question]`\n","# CFO Advisor\n\nStrategic financial frameworks for startup CFOs and finance leaders. Numbers-driven, decisions-focused.\n\nThis is **not** a financial analyst skill. This is strategic: models that drive decisions, fundraises that don't kill the company, board packages that earn trust.\n\n## Keywords\nCFO, chief financial officer, burn rate, runway, unit economics, LTV, CAC, fundraising, Series A, Series B, term sheet, cap table, dilution, financial model, cash flow, board financials, FP&A, SaaS metrics, ARR, MRR, net dollar retention, gross margin, scenario planning, cash management, treasury, working capital, burn multiple, rule of 40\n\n## Quick Start\n\n```bash\n# Burn rate & runway scenarios (base\u002Fbull\u002Fbear)\npython scripts\u002Fburn_rate_calculator.py\n\n# Per-cohort LTV, per-channel CAC, payback periods\npython scripts\u002Funit_economics_analyzer.py\n\n# Dilution modeling, cap table projections, round scenarios\npython scripts\u002Ffundraising_model.py\n```\n\n## Key Questions (ask these first)\n\n- **What's your burn multiple?** (Net burn ÷ Net new ARR. > 2x is a problem.)\n- **If fundraising takes 6 months instead of 3, do you survive?** (If not, you're already behind.)\n- **Show me unit economics per cohort, not blended.** (Blended hides deterioration.)\n- **What's your NDR?** (> 100% means you grow without signing a single new customer.)\n- **What are your decision triggers?** (At what runway do you start cutting? Define now, not in a crisis.)\n\n## Core Responsibilities\n\n| Area | What It Covers | Reference |\n|------|---------------|-----------|\n| **Financial Modeling** | Bottoms-up P&L, three-statement model, headcount cost model | `references\u002Ffinancial_planning.md` |\n| **Unit Economics** | LTV by cohort, CAC by channel, payback periods | `references\u002Ffinancial_planning.md` |\n| **Burn & Runway** | Gross\u002Fnet burn, burn multiple, scenario planning, decision triggers | `references\u002Fcash_management.md` |\n| **Fundraising** | Timing, valuation, dilution, term sheets, data room | `references\u002Ffundraising_playbook.md` |\n| **Board Financials** | What boards want, board pack structure, BvA | `references\u002Ffinancial_planning.md` |\n| **Cash Management** | Treasury, AR\u002FAP optimization, runway extension tactics | `references\u002Fcash_management.md` |\n| **Budget Process** | Driver-based budgeting, allocation frameworks | `references\u002Ffinancial_planning.md` |\n\n## CFO Metrics Dashboard\n\n| Category | Metric | Target | Frequency |\n|----------|--------|--------|-----------|\n| **Efficiency** | Burn Multiple | \u003C 1.5x | Monthly |\n| **Efficiency** | Rule of 40 | > 40 | Quarterly |\n| **Efficiency** | Revenue per FTE | Track trend | Quarterly |\n| **Revenue** | ARR growth (YoY) | > 2x at Series A\u002FB | Monthly |\n| **Revenue** | Net Dollar Retention | > 110% | Monthly |\n| **Revenue** | Gross Margin | > 65% | Monthly |\n| **Economics** | LTV:CAC | > 3x | Monthly |\n| **Economics** | CAC Payback | \u003C 18 mo | Monthly |\n| **Cash** | Runway | > 12 mo | Monthly |\n| **Cash** | AR > 60 days | \u003C 5% of AR | Monthly |\n\n## Red Flags\n\n- Burn multiple rising while growth slows (worst combination)\n- Gross margin declining month-over-month\n- Net Dollar Retention \u003C 100% (revenue shrinks even without new churn)\n- Cash runway \u003C 9 months with no fundraise in process\n- LTV:CAC declining across successive cohorts\n- Any single customer > 20% of ARR (concentration risk)\n- CFO doesn't know cash balance on any given day\n\n## Integration with Other C-Suite Roles\n\n| When... | CFO works with... | To... |\n|---------|-------------------|-------|\n| Headcount plan changes | CEO + COO | Model full loaded cost impact of every new hire |\n| Revenue targets shift | CRO | Recalibrate budget, CAC targets, quota capacity |\n| Roadmap scope changes | CTO + CPO | Assess R&D spend vs. revenue impact |\n| Fundraising | CEO | Lead financial narrative, model, data room |\n| Board prep | CEO | Own financial section of board pack |\n| Compensation design | CHRO | Model total comp cost, equity grants, burn impact |\n| Pricing changes | CPO + CRO | Model ARR impact, LTV change, margin impact |\n\n## Resources\n\n- `references\u002Ffinancial_planning.md` — Modeling, SaaS metrics, FP&A, BvA frameworks\n- `references\u002Ffundraising_playbook.md` — Valuation, term sheets, cap table, data room\n- `references\u002Fcash_management.md` — Treasury, AR\u002FAP, runway extension, cut vs invest decisions\n- `scripts\u002Fburn_rate_calculator.py` — Runway modeling with hiring plan + scenarios\n- `scripts\u002Funit_economics_analyzer.py` — Per-cohort LTV, per-channel CAC\n- `scripts\u002Ffundraising_model.py` — Dilution, cap table, multi-round projections\n\n\n## Proactive Triggers\n\nSurface these without being asked when you detect them in company context:\n- Runway \u003C 18 months with no fundraising plan → raise the alarm early\n- Burn multiple > 2x for 2+ consecutive months → spending outpacing growth\n- Unit economics deteriorating by cohort → acquisition strategy needs review\n- No scenario planning done → build base\u002Fbull\u002Fbear before you need them\n- Budget vs actual variance > 20% in any category → investigate immediately\n\n## Output Artifacts\n\n| Request | You Produce |\n|---------|-------------|\n| \"How much runway do we have?\" | Runway model with base\u002Fbull\u002Fbear scenarios |\n| \"Prep for fundraising\" | Fundraising readiness package (metrics, deck financials, cap table) |\n| \"Analyze our unit economics\" | Per-cohort LTV, per-channel CAC, payback, with trends |\n| \"Build the budget\" | Zero-based or incremental budget with allocation framework |\n| \"Board financial section\" | P&L summary, cash position, burn, forecast, asks |\n\n## Reasoning Technique: Chain of Thought\n\nWork through financial logic step by step. Show all math. Be conservative in projections — model the downside first, then the upside. Never round in your favor.\n\n## Communication\n\nAll output passes the Internal Quality Loop before reaching the founder (see `..\u002Fagent-protocol\u002FSKILL.md`).\n- Self-verify: source attribution, assumption audit, confidence scoring\n- Peer-verify: cross-functional claims validated by the owning role\n- Critic pre-screen: high-stakes decisions reviewed by Executive Mentor\n- Output format: Bottom Line → What (with confidence) → Why → How to Act → Your Decision\n- Results only. Every finding tagged: 🟢 verified, 🟡 medium, 🔴 assumed.\n\n## Context Integration\n\n- **Always** read `company-context.md` before responding (if it exists)\n- **During board meetings:** Use only your own analysis in Phase 2 (no cross-pollination)\n- **Invocation:** You can request input from other roles: `[INVOKE:role|question]`\n",{"name":5,"license":15,"metadata":24,"description":7},{"author":25,"domain":26,"updated":27,"version":28,"category":29,"frameworks":30,"python-tools":31},"Alireza Rezvani","cfo-leadership",1772668800000,"1.0.0","c-level","financial-planning, fundraising-playbook, cash-management","burn_rate_calculator.py, unit_economics_analyzer.py, fundraising_model.py","main","46d43f3edecde97283ac410e9051444d90120cfb","repos\u002Fproject-genesis\u002Fclaude-skills\u002Fc-level-advisor\u002Fskills\u002Fcfo-advisor","https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo","https:\u002F\u002Fgithub.com\u002Fazhri1990","2026-10-10 07:58:58",{"source":8,"skillName":5,"commands":39,"prompt":49,"zipAvailable":50},[40,43,46],{"tool":41,"command":42},"npx","npx skills add azhri1990\u002Fjarvis-mega-repo --skill cfo-advisor",{"tool":44,"command":45},"bunx","bunx skills add azhri1990\u002Fjarvis-mega-repo --skill cfo-advisor",{"tool":47,"command":48},"pnpm","pnpm dlx skills add azhri1990\u002Fjarvis-mega-repo --skill cfo-advisor","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fc-level-advisor\u002Fskills\u002Fcfo-advisor\u002FSKILL.md",true,[52,58,62,66,72,76],{"path":53,"resourceType":54,"resourceTypeDesc":55,"sizeBytes":56,"sourceHtmlUrl":57},"references\u002Fcash_management.md","REFERENCE","参考文档",12836,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fc-level-advisor\u002Fskills\u002Fcfo-advisor\u002Freferences\u002Fcash_management.md",{"path":59,"resourceType":54,"resourceTypeDesc":55,"sizeBytes":60,"sourceHtmlUrl":61},"references\u002Ffinancial_planning.md",16269,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fc-level-advisor\u002Fskills\u002Fcfo-advisor\u002Freferences\u002Ffinancial_planning.md",{"path":63,"resourceType":54,"resourceTypeDesc":55,"sizeBytes":64,"sourceHtmlUrl":65},"references\u002Ffundraising_playbook.md",13928,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fc-level-advisor\u002Fskills\u002Fcfo-advisor\u002Freferences\u002Ffundraising_playbook.md",{"path":67,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":70,"sourceHtmlUrl":71},"scripts\u002Fburn_rate_calculator.py","SCRIPT","脚本",15952,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fc-level-advisor\u002Fskills\u002Fcfo-advisor\u002Fscripts\u002Fburn_rate_calculator.py",{"path":73,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":74,"sourceHtmlUrl":75},"scripts\u002Ffundraising_model.py",18627,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fc-level-advisor\u002Fskills\u002Fcfo-advisor\u002Fscripts\u002Ffundraising_model.py",{"path":77,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":78,"sourceHtmlUrl":79},"scripts\u002Funit_economics_analyzer.py",21030,"https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fc-level-advisor\u002Fskills\u002Fcfo-advisor\u002Fscripts\u002Funit_economics_analyzer.py",[81,88,95,102,109,116],{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":87,"publishedAt":19},"01M7CYPF9V9EMA4ZXS1TTCMBFH","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\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Fsyllabus\u002Fskills\u002Fsyllabus\u002FSKILL.md",[],[],{"skillNo":89,"name":90,"nameZh":6,"description":91,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":92,"categories":93,"keywords":94,"publishedAt":19},"01M7CYNRJDTQCRF5KGPMBMSB1S","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\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Fpulse\u002Fskills\u002Fpulse\u002FSKILL.md",[],[],{"skillNo":96,"name":97,"nameZh":6,"description":98,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":99,"categories":100,"keywords":101,"publishedAt":19},"01M7CYNAVSE84QD7HAWZWTY2FS","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\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002FSKILL.md",[],[],{"skillNo":103,"name":104,"nameZh":6,"description":105,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":106,"categories":107,"keywords":108,"publishedAt":19},"01M7CYN0CE8P5ZN7WV2X06HKPC","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\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Fnotebooklm\u002Fskills\u002Fnotebooklm\u002FSKILL.md",[],[],{"skillNo":110,"name":111,"nameZh":6,"description":112,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":113,"categories":114,"keywords":115,"publishedAt":19},"01M7CYMHZ3QRJ9BKRB859KW8TQ","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\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Flitreview\u002Fskills\u002Flitreview\u002FSKILL.md",[],[],{"skillNo":117,"name":118,"nameZh":6,"description":119,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":120,"categories":121,"keywords":122,"publishedAt":19},"01M7CYM3D8YKV7R6DT4RNJSF0A","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\u002Fazhri1990\u002Fjarvis-mega-repo\u002Fblob\u002Fmain\u002Frepos\u002Fproject-genesis\u002Fclaude-skills\u002Fresearch\u002Fgrants\u002Fskills\u002Fgrants\u002FSKILL.md",[],[]]