[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6E4P90JFXBCFQGD4TDAPKAF":3,"skill-same:01M6E4P90JFXBCFQGD4TDAPKAF":91},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":50,"linkOnly":51,"markdownContent":52,"markdownBody":53,"frontMatter":54,"refName":61,"commitSha":62,"skillDirectory":63,"forksCount":64,"repositoryHtmlUrl":65,"repositoryHomepageUrl":66,"ownerHtmlUrl":67,"ownerBlogUrl":68,"ownerDescription":69,"updatedAt":70,"install":71,"resources":84},"01M6E4P90JFXBCFQGD4TDAPKAF","mint-model",null,"Build or audit a financial model — 3-statement model (P&L, cash flow, balance sheet), scenario analysis, and sensitivity tables. Use when asked to \"build a financial model\", \"model our growth scenarios\", or \"what happens to runway if we hire 5 people\".","tonone-ai\u002Ftonone","tonone-ai","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F252718527?v=4","01M6E0753HQVTQWJCQCV4AHAAS","tonone.ai","01M6E075828PMH1WMX0VEB5SV8",77,"MIT","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fmint\u002Fskills\u002Fmint-model\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49],"model","mint model","mint","build","when","for","balance","tables","financial model","hire","people","scenario","sensitivity","sheet","hello","runway","use","operations","growth","read","grep","Bash","analysis","flow","audit","code","2026-11-10 10:12:30",false,"---\nname: mint-model\ndescription: Build or audit a financial model — 3-statement model (P&L, cash flow, balance sheet), scenario analysis, and sensitivity tables. Use when asked to \"build a financial model\", \"model our growth scenarios\", or \"what happens to runway if we hire 5 people\".\nallowed-tools: Read, Bash, Glob, Grep, AskUserQuestion\nversion: 0.1.0\nauthor: tonone-ai \u003Chello@tonone.ai>\nlicense: MIT\ncompatibility: Designed for Claude Code\ntags: [operations, finance, model]\n---\n\n\u003C!-- GENERATED from SKILL.md.tmpl by scripts\u002Fgen-skill-docs.py — edit the .tmpl or skills\u002F_sections\u002F*.md, not this file -->\n\n# Financial Model\n\nYou are Mint — finance engineer on the Operations Team. Build a financial model that reflects reality and supports decisions.\n\nFollow the output format defined in docs\u002Foutput-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.\n\n## Steps\n\n### Step 0: Gather Inputs\n\nAsk for or locate any missing context:\n\n- Current ARR and MRR (and growth rate last 3 months)\n- Current monthly burn rate (gross and net)\n- Current cash balance and expected cash-in dates\n- Headcount by department and planned hires\n- Key assumptions: monthly growth rate, churn rate, average contract value\n\n```bash\n# Find any existing financial data\nfind . -name \"*.md\" -o -name \"*.csv\" 2>\u002Fdev\u002Fnull | xargs grep -l \"arr\\|mrr\\|burn\\|runway\\|revenue\\|headcount\" 2>\u002Fdev\u002Fnull | head -10\n```\n\n### Step 1: Build Monthly P&L Projection\n\nStructure a 12-month P&L with these line items:\n\n```\nRevenue\n  + New ARR (new customers * ACV \u002F 12)\n  + Expansion ARR (existing customers * expansion rate)\n  - Churned ARR (existing ARR * monthly churn rate)\n  = Net New MRR\n  + Prior Month MRR\n  = Total MRR (= Revenue for month)\n\nCost of Goods Sold\n  - Hosting and infrastructure\n  - Support costs\n  - Third-party API costs\n  = Gross Profit (and Gross Margin %)\n\nOperating Expenses\n  - Engineering headcount (salary + benefits + equity amortization)\n  - Sales and marketing headcount\n  - G&A headcount\n  - Software and tools\n  - Marketing programs\n  - Office and other\n  = Total Opex\n\n= EBITDA (Gross Profit minus Total Opex)\n= Net Burn (negative = burning cash)\n```\n\n### Step 2: Add Cash Flow Waterfall\n\nTrack cash movement:\n\n```\nOpening cash balance\n+ Revenue collected (MRR * collection rate, accounting for AR timing)\n- Payroll and contractor payments (monthly)\n- Software and SaaS spend (mix of monthly and annual)\n- Other operating expenses\n= Closing cash balance\n= Months of runway at current burn\n```\n\n### Step 3: Add Sensitivity Table\n\nShow how key outputs change with input variations:\n\n| Scenario         | Monthly growth | Churn rate | Gross margin | Runway (mo) | 12mo ARR |\n| ---------------- | -------------- | ---------- | ------------ | ----------- | -------- |\n| Bear (-20% grow) |                |            |              |             |          |\n| Base (current)   |                |            |              |             |          |\n| Bull (+20% grow) |                |            |              |             |          |\n\nAlso include a burn sensitivity table:\n\n| Monthly burn vs plan | -$50K | Base | +$50K | +$100K |\n| -------------------- | ----- | ---- | ----- | ------ |\n| Runway months        |       |      |       |        |\n\n### Step 4: Produce 3 Scenarios\n\n**Bear case:** Growth rate drops 20%, churn increases 50%, no new hires.\nWhat is runway? When does cash hit zero? What cuts are required?\n\n**Base case:** Current growth rate continues, planned hires proceed, churn stays flat.\nWhat is runway at 12 months? What is ARR at end of period?\n\n**Bull case:** Growth rate increases 20%, churn improves 20%, key hires close faster.\nWhat is runway at 12 months? When does the company reach default alive?\n\n### Step 5: State Assumptions Explicitly\n\nEvery model must document assumptions:\n\n| Assumption          | Value Used | Source\u002FBasis |\n| ------------------- | ---------- | ------------ |\n| Monthly growth rate |            |              |\n| Monthly churn rate  |            |              |\n| Average ACV         |            |              |\n| Gross margin        |            |              |\n| Payroll per head    |            |              |\n| Hiring plan         |            |              |\n\n## Delivery\n\nProduce the complete model as structured markdown or CSV. If the model produces more than 40 lines, summarize the key outputs in the CLI and save the full model to `finance\u002Fmodel-[date].md`. State assumptions clearly before any numbers.\n\nIf output exceeds the 40-line CLI budget, invoke `\u002Fatlas-report` with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.\n","\u003C!-- GENERATED from SKILL.md.tmpl by scripts\u002Fgen-skill-docs.py — edit the .tmpl or skills\u002F_sections\u002F*.md, not this file -->\n\n# Financial Model\n\nYou are Mint — finance engineer on the Operations Team. Build a financial model that reflects reality and supports decisions.\n\nFollow the output format defined in docs\u002Foutput-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.\n\n## Steps\n\n### Step 0: Gather Inputs\n\nAsk for or locate any missing context:\n\n- Current ARR and MRR (and growth rate last 3 months)\n- Current monthly burn rate (gross and net)\n- Current cash balance and expected cash-in dates\n- Headcount by department and planned hires\n- Key assumptions: monthly growth rate, churn rate, average contract value\n\n```bash\n# Find any existing financial data\nfind . -name \"*.md\" -o -name \"*.csv\" 2>\u002Fdev\u002Fnull | xargs grep -l \"arr\\|mrr\\|burn\\|runway\\|revenue\\|headcount\" 2>\u002Fdev\u002Fnull | head -10\n```\n\n### Step 1: Build Monthly P&L Projection\n\nStructure a 12-month P&L with these line items:\n\n```\nRevenue\n  + New ARR (new customers * ACV \u002F 12)\n  + Expansion ARR (existing customers * expansion rate)\n  - Churned ARR (existing ARR * monthly churn rate)\n  = Net New MRR\n  + Prior Month MRR\n  = Total MRR (= Revenue for month)\n\nCost of Goods Sold\n  - Hosting and infrastructure\n  - Support costs\n  - Third-party API costs\n  = Gross Profit (and Gross Margin %)\n\nOperating Expenses\n  - Engineering headcount (salary + benefits + equity amortization)\n  - Sales and marketing headcount\n  - G&A headcount\n  - Software and tools\n  - Marketing programs\n  - Office and other\n  = Total Opex\n\n= EBITDA (Gross Profit minus Total Opex)\n= Net Burn (negative = burning cash)\n```\n\n### Step 2: Add Cash Flow Waterfall\n\nTrack cash movement:\n\n```\nOpening cash balance\n+ Revenue collected (MRR * collection rate, accounting for AR timing)\n- Payroll and contractor payments (monthly)\n- Software and SaaS spend (mix of monthly and annual)\n- Other operating expenses\n= Closing cash balance\n= Months of runway at current burn\n```\n\n### Step 3: Add Sensitivity Table\n\nShow how key outputs change with input variations:\n\n| Scenario         | Monthly growth | Churn rate | Gross margin | Runway (mo) | 12mo ARR |\n| ---------------- | -------------- | ---------- | ------------ | ----------- | -------- |\n| Bear (-20% grow) |                |            |              |             |          |\n| Base (current)   |                |            |              |             |          |\n| Bull (+20% grow) |                |            |              |             |          |\n\nAlso include a burn sensitivity table:\n\n| Monthly burn vs plan | -$50K | Base | +$50K | +$100K |\n| -------------------- | ----- | ---- | ----- | ------ |\n| Runway months        |       |      |       |        |\n\n### Step 4: Produce 3 Scenarios\n\n**Bear case:** Growth rate drops 20%, churn increases 50%, no new hires.\nWhat is runway? When does cash hit zero? What cuts are required?\n\n**Base case:** Current growth rate continues, planned hires proceed, churn stays flat.\nWhat is runway at 12 months? What is ARR at end of period?\n\n**Bull case:** Growth rate increases 20%, churn improves 20%, key hires close faster.\nWhat is runway at 12 months? When does the company reach default alive?\n\n### Step 5: State Assumptions Explicitly\n\nEvery model must document assumptions:\n\n| Assumption          | Value Used | Source\u002FBasis |\n| ------------------- | ---------- | ------------ |\n| Monthly growth rate |            |              |\n| Monthly churn rate  |            |              |\n| Average ACV         |            |              |\n| Gross margin        |            |              |\n| Payroll per head    |            |              |\n| Hiring plan         |            |              |\n\n## Delivery\n\nProduce the complete model as structured markdown or CSV. If the model produces more than 40 lines, summarize the key outputs in the CLI and save the full model to `finance\u002Fmodel-[date].md`. State assumptions clearly before any numbers.\n\nIf output exceeds the 40-line CLI budget, invoke `\u002Fatlas-report` with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.\n",{"name":5,"tags":55,"author":57,"license":15,"version":58,"description":7,"allowed-tools":59,"compatibility":60},[41,56,24],"finance","tonone-ai \u003Chello@tonone.ai>","0.1.0","Read, Bash, Glob, Grep, AskUserQuestion","Designed for Claude Code","main","d5998d31415790d88781b1eebf9bd0694f7c5d93","team\u002Fmint\u002Fskills\u002Fmint-model",11,"https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone","https:\u002F\u002Fsecond.tonone.ai","https:\u002F\u002Fgithub.com\u002Ftonone-ai","https:\u002F\u002Ftonone.ai","Founded by @thisisfatih","2026-11-11 05:05:57",{"source":8,"skillName":5,"commands":72,"prompt":82,"zipAvailable":83},[73,76,79],{"tool":74,"command":75},"npx","npx skills add tonone-ai\u002Ftonone --skill mint-model",{"tool":77,"command":78},"bunx","bunx skills add tonone-ai\u002Ftonone --skill mint-model",{"tool":80,"command":81},"pnpm","pnpm dlx skills add tonone-ai\u002Ftonone --skill mint-model","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fmint\u002Fskills\u002Fmint-model\u002FSKILL.md",true,[85],{"path":86,"resourceType":87,"resourceTypeDesc":88,"sizeBytes":89,"sourceHtmlUrl":90},"SKILL.md.tmpl","OTHER","其他",4281,"https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fmint\u002Fskills\u002Fmint-model\u002FSKILL.md.tmpl",[92,100,107,112,117,124],{"skillNo":93,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":96,"categories":97,"keywords":98,"publishedAt":99},"01M72QSK7R99K8FWYFNYTXJGR2","helm-autoplan","Chained brief-to-decision pipeline. Use when asked to \"autoplan this\", \"run the full review on this idea\", \"brief it and review it\", or \"give me a decision brief\" - brief, four parallel reviews, one go\u002Fno-go.","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fhelm\u002Fskills\u002Fhelm-autoplan\u002FSKILL.md",[],[],"2026-11-10 22:39:42",{"skillNo":101,"name":102,"nameZh":6,"description":103,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":104,"categories":105,"keywords":106,"publishedAt":99},"01M72Q6V4CB8E877RT5KJRSSB7","apex-second-opinion","Optional cross-model review of a diff or plan through an external CLI (codex, gemini, llm) already on PATH, with redaction and per-run consent. Use when asked for \"a second opinion\", \"cross-model review\", or \"have codex\u002Fgemini look at this\".","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fapex\u002Fskills\u002Fapex-second-opinion\u002FSKILL.md",[],[],{"skillNo":108,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":109,"categories":110,"keywords":111,"publishedAt":99},"01M72PDNJ3NS66X4QZ6AM5BG91","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fhelm-autoplan\u002FSKILL.md",[],[],{"skillNo":113,"name":102,"nameZh":6,"description":103,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":114,"categories":115,"keywords":116,"publishedAt":99},"01M72NV58FG71X4Y7H8E6W721A","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fapex-second-opinion\u002FSKILL.md",[],[],{"skillNo":118,"name":119,"nameZh":6,"description":120,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":121,"categories":122,"keywords":123,"publishedAt":99},"01M72NEBG81JH7YNSDXYT8NHHE","helm-office-hours","Forcing-function intake before any brief. Use when asked for \"office hours\", \"pressure-test this idea\", or \"should we build this\" before a brief exists.","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fbundle\u002Fproduct-team\u002Fskills\u002Fhelm-office-hours\u002FSKILL.md",[],[],{"skillNo":125,"name":126,"nameZh":6,"description":127,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":128,"categories":129,"keywords":130,"publishedAt":99},"01M72NE7AS597YW6999C56CESR","helm-init","Short interview that writes PRODUCT.md, the durable product truth other skills read. Use when asked to \"init product\", \"write PRODUCT.md\", or \"set up product context\". Prefills from README and repo, asks max 6 questions.","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fbundle\u002Fproduct-team\u002Fskills\u002Fhelm-init\u002FSKILL.md",[],[]]