[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M719G26FJS533HS7H4YJM8WK":3,"skill-same:01M719G26FJS533HS7H4YJM8WK":128},{"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":22,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":53,"ownerHtmlUrl":54,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":55,"install":56,"resources":69},"01M719G26FJS533HS7H4YJM8WK","financial-analyst",null,"Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis.","dahaliztupe-sketch\u002FKalmeron-Two","dahaliztupe-sketch","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F271085317?v=4","01M719765Q83P08JCQ1SWNQR0N","01M719766HQBGF44W90MPJKTD2",1,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000040","财务","PROFESSION","适用职业",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"analyst","financial analyst","for","forecast","dcf valuation","valuation","flow","analyzing","modeling","Budget","analyzing financial statements","financial statements","budget variance analysis","variance analysis","dcf","analysis","when","decision","company","spreadsheet","2026-11-10 10:12:30",false,"---\nname: \"financial-analyst\"\ndescription: Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis.\n---\n\n# Financial Analyst Skill\n\n## Overview\n\nProduction-ready financial analysis toolkit providing ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction. Designed for financial modeling, forecasting & budgeting, management reporting, business performance analysis, and investment analysis.\n\n## 5-Phase Workflow\n\n### Phase 1: Scoping\n- Define analysis objectives and stakeholder requirements\n- Identify data sources and time periods\n- Establish materiality thresholds and accuracy targets\n- Select appropriate analytical frameworks\n\n### Phase 2: Data Analysis & Modeling\n- Collect and validate financial data (income statement, balance sheet, cash flow)\n- **Validate input data completeness** before running ratio calculations (check for missing fields, nulls, or implausible values)\n- Calculate financial ratios across 5 categories (profitability, liquidity, leverage, efficiency, valuation)\n- Build DCF models with WACC and terminal value calculations; **cross-check DCF outputs against sanity bounds** (e.g., implied multiples vs. comparables)\n- Construct budget variance analyses with favorable\u002Funfavorable classification\n- Develop driver-based forecasts with scenario modeling\n\n### Phase 3: Insight Generation\n- Interpret ratio trends and benchmark against industry standards\n- Identify material variances and root causes\n- Assess valuation ranges through sensitivity analysis\n- Evaluate forecast scenarios (base\u002Fbull\u002Fbear) for decision support\n\n### Phase 4: Reporting\n- Generate executive summaries with key findings\n- Produce detailed variance reports by department and category\n- Deliver DCF valuation reports with sensitivity tables\n- Present rolling forecasts with trend analysis\n\n### Phase 5: Follow-up\n- Track forecast accuracy (target: +\u002F-5% revenue, +\u002F-3% expenses)\n- Monitor report delivery timeliness (target: 100% on time)\n- Update models with actuals as they become available\n- Refine assumptions based on variance analysis\n\n## Tools\n\n### 1. Ratio Calculator (`scripts\u002Fratio_calculator.py`)\n\nCalculate and interpret financial ratios from financial statement data.\n\n**Ratio Categories:**\n- **Profitability:** ROE, ROA, Gross Margin, Operating Margin, Net Margin\n- **Liquidity:** Current Ratio, Quick Ratio, Cash Ratio\n- **Leverage:** Debt-to-Equity, Interest Coverage, DSCR\n- **Efficiency:** Asset Turnover, Inventory Turnover, Receivables Turnover, DSO\n- **Valuation:** P\u002FE, P\u002FB, P\u002FS, EV\u002FEBITDA, PEG Ratio\n\n```bash\npython scripts\u002Fratio_calculator.py sample_financial_data.json\npython scripts\u002Fratio_calculator.py sample_financial_data.json --format json\npython scripts\u002Fratio_calculator.py sample_financial_data.json --category profitability\n```\n\n### 2. DCF Valuation (`scripts\u002Fdcf_valuation.py`)\n\nDiscounted Cash Flow enterprise and equity valuation with sensitivity analysis.\n\n**Features:**\n- WACC calculation via CAPM\n- Revenue and free cash flow projections (5-year default)\n- Terminal value via perpetuity growth and exit multiple methods\n- Enterprise value and equity value derivation\n- Two-way sensitivity analysis (discount rate vs growth rate)\n\n```bash\npython scripts\u002Fdcf_valuation.py valuation_data.json\npython scripts\u002Fdcf_valuation.py valuation_data.json --format json\npython scripts\u002Fdcf_valuation.py valuation_data.json --projection-years 7\n```\n\n### 3. Budget Variance Analyzer (`scripts\u002Fbudget_variance_analyzer.py`)\n\nAnalyze actual vs budget vs prior year performance with materiality filtering.\n\n**Features:**\n- Dollar and percentage variance calculation\n- Materiality threshold filtering (default: 10% or $50K)\n- Favorable\u002Funfavorable classification with revenue\u002Fexpense logic\n- Department and category breakdown\n- Executive summary generation\n\n```bash\npython scripts\u002Fbudget_variance_analyzer.py budget_data.json\npython scripts\u002Fbudget_variance_analyzer.py budget_data.json --format json\npython scripts\u002Fbudget_variance_analyzer.py budget_data.json --threshold-pct 5 --threshold-amt 25000\n```\n\n### 4. Forecast Builder (`scripts\u002Fforecast_builder.py`)\n\nDriver-based revenue forecasting with rolling cash flow projection and scenario modeling.\n\n**Features:**\n- Driver-based revenue forecast model\n- 13-week rolling cash flow projection\n- Scenario modeling (base\u002Fbull\u002Fbear cases)\n- Trend analysis using simple linear regression (standard library)\n\n```bash\npython scripts\u002Fforecast_builder.py forecast_data.json\npython scripts\u002Fforecast_builder.py forecast_data.json --format json\npython scripts\u002Fforecast_builder.py forecast_data.json --scenarios base,bull,bear\n```\n\n## Knowledge Bases\n\n| Reference | Purpose |\n|-----------|---------|\n| `references\u002Ffinancial-ratios-guide.md` | Ratio formulas, interpretation, industry benchmarks |\n| `references\u002Fvaluation-methodology.md` | DCF methodology, WACC, terminal value, comps |\n| `references\u002Fforecasting-best-practices.md` | Driver-based forecasting, rolling forecasts, accuracy |\n| `references\u002Findustry-adaptations.md` | Sector-specific metrics and considerations (SaaS, Retail, Manufacturing, Financial Services, Healthcare) |\n\n## Templates\n\n| Template | Purpose |\n|----------|---------|\n| `assets\u002Fvariance_report_template.md` | Budget variance report template |\n| `assets\u002Fdcf_analysis_template.md` | DCF valuation analysis template |\n| `assets\u002Fforecast_report_template.md` | Revenue forecast report template |\n\n## Key Metrics & Targets\n\n| Metric | Target |\n|--------|--------|\n| Forecast accuracy (revenue) | +\u002F-5% |\n| Forecast accuracy (expenses) | +\u002F-3% |\n| Report delivery | 100% on time |\n| Model documentation | Complete for all assumptions |\n| Variance explanation | 100% of material variances |\n\n## Input Data Format\n\nAll scripts accept JSON input files. See `assets\u002Fsample_financial_data.json` for the complete input schema covering all four tools.\n\n## Dependencies\n\n**None** - All scripts use Python standard library only (`math`, `statistics`, `json`, `argparse`, `datetime`). No numpy, pandas, or scipy required.\n","# Financial Analyst Skill\n\n## Overview\n\nProduction-ready financial analysis toolkit providing ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction. Designed for financial modeling, forecasting & budgeting, management reporting, business performance analysis, and investment analysis.\n\n## 5-Phase Workflow\n\n### Phase 1: Scoping\n- Define analysis objectives and stakeholder requirements\n- Identify data sources and time periods\n- Establish materiality thresholds and accuracy targets\n- Select appropriate analytical frameworks\n\n### Phase 2: Data Analysis & Modeling\n- Collect and validate financial data (income statement, balance sheet, cash flow)\n- **Validate input data completeness** before running ratio calculations (check for missing fields, nulls, or implausible values)\n- Calculate financial ratios across 5 categories (profitability, liquidity, leverage, efficiency, valuation)\n- Build DCF models with WACC and terminal value calculations; **cross-check DCF outputs against sanity bounds** (e.g., implied multiples vs. comparables)\n- Construct budget variance analyses with favorable\u002Funfavorable classification\n- Develop driver-based forecasts with scenario modeling\n\n### Phase 3: Insight Generation\n- Interpret ratio trends and benchmark against industry standards\n- Identify material variances and root causes\n- Assess valuation ranges through sensitivity analysis\n- Evaluate forecast scenarios (base\u002Fbull\u002Fbear) for decision support\n\n### Phase 4: Reporting\n- Generate executive summaries with key findings\n- Produce detailed variance reports by department and category\n- Deliver DCF valuation reports with sensitivity tables\n- Present rolling forecasts with trend analysis\n\n### Phase 5: Follow-up\n- Track forecast accuracy (target: +\u002F-5% revenue, +\u002F-3% expenses)\n- Monitor report delivery timeliness (target: 100% on time)\n- Update models with actuals as they become available\n- Refine assumptions based on variance analysis\n\n## Tools\n\n### 1. Ratio Calculator (`scripts\u002Fratio_calculator.py`)\n\nCalculate and interpret financial ratios from financial statement data.\n\n**Ratio Categories:**\n- **Profitability:** ROE, ROA, Gross Margin, Operating Margin, Net Margin\n- **Liquidity:** Current Ratio, Quick Ratio, Cash Ratio\n- **Leverage:** Debt-to-Equity, Interest Coverage, DSCR\n- **Efficiency:** Asset Turnover, Inventory Turnover, Receivables Turnover, DSO\n- **Valuation:** P\u002FE, P\u002FB, P\u002FS, EV\u002FEBITDA, PEG Ratio\n\n```bash\npython scripts\u002Fratio_calculator.py sample_financial_data.json\npython scripts\u002Fratio_calculator.py sample_financial_data.json --format json\npython scripts\u002Fratio_calculator.py sample_financial_data.json --category profitability\n```\n\n### 2. DCF Valuation (`scripts\u002Fdcf_valuation.py`)\n\nDiscounted Cash Flow enterprise and equity valuation with sensitivity analysis.\n\n**Features:**\n- WACC calculation via CAPM\n- Revenue and free cash flow projections (5-year default)\n- Terminal value via perpetuity growth and exit multiple methods\n- Enterprise value and equity value derivation\n- Two-way sensitivity analysis (discount rate vs growth rate)\n\n```bash\npython scripts\u002Fdcf_valuation.py valuation_data.json\npython scripts\u002Fdcf_valuation.py valuation_data.json --format json\npython scripts\u002Fdcf_valuation.py valuation_data.json --projection-years 7\n```\n\n### 3. Budget Variance Analyzer (`scripts\u002Fbudget_variance_analyzer.py`)\n\nAnalyze actual vs budget vs prior year performance with materiality filtering.\n\n**Features:**\n- Dollar and percentage variance calculation\n- Materiality threshold filtering (default: 10% or $50K)\n- Favorable\u002Funfavorable classification with revenue\u002Fexpense logic\n- Department and category breakdown\n- Executive summary generation\n\n```bash\npython scripts\u002Fbudget_variance_analyzer.py budget_data.json\npython scripts\u002Fbudget_variance_analyzer.py budget_data.json --format json\npython scripts\u002Fbudget_variance_analyzer.py budget_data.json --threshold-pct 5 --threshold-amt 25000\n```\n\n### 4. Forecast Builder (`scripts\u002Fforecast_builder.py`)\n\nDriver-based revenue forecasting with rolling cash flow projection and scenario modeling.\n\n**Features:**\n- Driver-based revenue forecast model\n- 13-week rolling cash flow projection\n- Scenario modeling (base\u002Fbull\u002Fbear cases)\n- Trend analysis using simple linear regression (standard library)\n\n```bash\npython scripts\u002Fforecast_builder.py forecast_data.json\npython scripts\u002Fforecast_builder.py forecast_data.json --format json\npython scripts\u002Fforecast_builder.py forecast_data.json --scenarios base,bull,bear\n```\n\n## Knowledge Bases\n\n| Reference | Purpose |\n|-----------|---------|\n| `references\u002Ffinancial-ratios-guide.md` | Ratio formulas, interpretation, industry benchmarks |\n| `references\u002Fvaluation-methodology.md` | DCF methodology, WACC, terminal value, comps |\n| `references\u002Fforecasting-best-practices.md` | Driver-based forecasting, rolling forecasts, accuracy |\n| `references\u002Findustry-adaptations.md` | Sector-specific metrics and considerations (SaaS, Retail, Manufacturing, Financial Services, Healthcare) |\n\n## Templates\n\n| Template | Purpose |\n|----------|---------|\n| `assets\u002Fvariance_report_template.md` | Budget variance report template |\n| `assets\u002Fdcf_analysis_template.md` | DCF valuation analysis template |\n| `assets\u002Fforecast_report_template.md` | Revenue forecast report template |\n\n## Key Metrics & Targets\n\n| Metric | Target |\n|--------|--------|\n| Forecast accuracy (revenue) | +\u002F-5% |\n| Forecast accuracy (expenses) | +\u002F-3% |\n| Report delivery | 100% on time |\n| Model documentation | Complete for all assumptions |\n| Variance explanation | 100% of material variances |\n\n## Input Data Format\n\nAll scripts accept JSON input files. See `assets\u002Fsample_financial_data.json` for the complete input schema covering all four tools.\n\n## Dependencies\n\n**None** - All scripts use Python standard library only (`math`, `statistics`, `json`, `argparse`, `datetime`). No numpy, pandas, or scipy required.\n",{"name":5,"description":7},"main","13d9afadbb6a87d6209fe4bd6ca2bbe4553119ac",".agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst",0,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two","https:\u002F\u002Fkalmeron-two.vercel.app","https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch","2026-10-05 12:24:53",{"source":8,"skillName":5,"commands":57,"prompt":67,"zipAvailable":68},[58,61,64],{"tool":59,"command":60},"npx","npx skills add dahaliztupe-sketch\u002FKalmeron-Two --skill financial-analyst",{"tool":62,"command":63},"bunx","bunx skills add dahaliztupe-sketch\u002FKalmeron-Two --skill financial-analyst",{"tool":65,"command":66},"pnpm","pnpm dlx skills add dahaliztupe-sketch\u002FKalmeron-Two --skill financial-analyst","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002FSKILL.md",true,[70,76,80,84,88,92,98,102,106,110,116,120,124],{"path":71,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":74,"sourceHtmlUrl":75},"assets\u002Fdcf_analysis_template.md","ASSET","资产文件",5930,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Fassets\u002Fdcf_analysis_template.md",{"path":77,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":78,"sourceHtmlUrl":79},"assets\u002Fexpected_output.json",5259,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Fassets\u002Fexpected_output.json",{"path":81,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":82,"sourceHtmlUrl":83},"assets\u002Fforecast_report_template.md",5189,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Fassets\u002Fforecast_report_template.md",{"path":85,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":86,"sourceHtmlUrl":87},"assets\u002Fsample_financial_data.json",6437,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Fassets\u002Fsample_financial_data.json",{"path":89,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":90,"sourceHtmlUrl":91},"assets\u002Fvariance_report_template.md",3863,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Fassets\u002Fvariance_report_template.md",{"path":93,"resourceType":94,"resourceTypeDesc":95,"sizeBytes":96,"sourceHtmlUrl":97},"references\u002Ffinancial-ratios-guide.md","REFERENCE","参考文档",9212,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Freferences\u002Ffinancial-ratios-guide.md",{"path":99,"resourceType":94,"resourceTypeDesc":95,"sizeBytes":100,"sourceHtmlUrl":101},"references\u002Fforecasting-best-practices.md",10012,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Freferences\u002Fforecasting-best-practices.md",{"path":103,"resourceType":94,"resourceTypeDesc":95,"sizeBytes":104,"sourceHtmlUrl":105},"references\u002Findustry-adaptations.md",2914,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Freferences\u002Findustry-adaptations.md",{"path":107,"resourceType":94,"resourceTypeDesc":95,"sizeBytes":108,"sourceHtmlUrl":109},"references\u002Fvaluation-methodology.md",7922,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Freferences\u002Fvaluation-methodology.md",{"path":111,"resourceType":112,"resourceTypeDesc":113,"sizeBytes":114,"sourceHtmlUrl":115},"scripts\u002Fbudget_variance_analyzer.py","SCRIPT","脚本",14574,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Fscripts\u002Fbudget_variance_analyzer.py",{"path":117,"resourceType":112,"resourceTypeDesc":113,"sizeBytes":118,"sourceHtmlUrl":119},"scripts\u002Fdcf_valuation.py",16803,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Fscripts\u002Fdcf_valuation.py",{"path":121,"resourceType":112,"resourceTypeDesc":113,"sizeBytes":122,"sourceHtmlUrl":123},"scripts\u002Fforecast_builder.py",19086,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Fscripts\u002Fforecast_builder.py",{"path":125,"resourceType":112,"resourceTypeDesc":113,"sizeBytes":126,"sourceHtmlUrl":127},"scripts\u002Fratio_calculator.py",16068,"https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffinance-skills\u002Ffinancial-analyst\u002Fscripts\u002Fratio_calculator.py",[129,146,169,187,216,247],{"skillNo":130,"name":131,"nameZh":6,"description":132,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":133,"sourceHtmlUrl":134,"categories":135,"keywords":141,"publishedAt":43},"01M719SWYD9RGS97HJ69PXWY62","add-new-agent","خطوات تفصيليّة لإضافة وكيل ذكاء اصطناعي جديد إلى منصّة Kalmeron من الفكرة إلى الإنتاج","https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002FSKILL.md",[136],{"categoryNo":137,"categoryName":138,"taxonomyType":139,"taxonomyTypeDesc":140},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[142,143,144,145],"add","add new agent","new","new agent",{"skillNo":147,"name":148,"nameZh":6,"description":149,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":150,"categories":151,"keywords":161,"publishedAt":43},"01M719SSKNBA7T5NS7V6DP0PX4","writing-skills","Use when creating new skills, editing existing skills, or verifying skills work before deployment","https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fwriting-skills\u002FSKILL.md",[152,155,158],{"categoryNo":153,"categoryName":154,"taxonomyType":139,"taxonomyTypeDesc":140},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":156,"categoryName":157,"taxonomyType":139,"taxonomyTypeDesc":140},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":159,"categoryName":160,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000036","内容创作者",[162,163,144,39,164,165,166,167,168],"writing skills","writing","work","editing","deployment","use","Existing",{"skillNo":170,"name":171,"nameZh":6,"description":172,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":173,"categories":174,"keywords":177,"publishedAt":43},"01M719SRFDNKA3044QD3FYZ05R","writing-plans","Use when you have a spec or requirements for a multi-step task, before touching code","https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fwriting-plans\u002FSKILL.md",[175,176],{"categoryNo":156,"categoryName":157,"taxonomyType":139,"taxonomyTypeDesc":140},{"categoryNo":159,"categoryName":160,"taxonomyType":20,"taxonomyTypeDesc":21},[178,163,179,180,181,182,39,167,25,183,184,185,186],"writing plans","plans","code","requirements","you","task","multi","spec","multi-step task",{"skillNo":188,"name":189,"nameZh":6,"description":190,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":191,"categories":192,"keywords":199,"publishedAt":43},"01M719SPN5FM1JYJSR9DGJQPZ0","web-design-guidelines","Review UI code for Web Interface Guidelines compliance. Use when asked to \"review my UI\", \"check accessibility\", \"audit design\", \"review UX\", or \"check my site against best practices\".","https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fweb-design-guidelines\u002FSKILL.md",[193,196],{"categoryNo":194,"categoryName":195,"taxonomyType":139,"taxonomyTypeDesc":140},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":197,"categoryName":198,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000032","设计师",[200,201,202,203,204,205,206,207,208,209,210,180,25,211,212,213,167,39,214,215],"web design","web design guidelines","web","design","guidelines","review","accessibility","ux","audit","compliance","check","vercel","interface","web interface guidelines","best practices","file",{"skillNo":217,"name":218,"nameZh":6,"description":219,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":220,"licenseFileUrl":6,"sourceHtmlUrl":221,"categories":222,"keywords":227,"publishedAt":43},"01M719SK11T05QYVPTWWYMYY5B","vitest","Set up Vitest testing in any project — detects project type (Cloudflare Workers, React, Node), generates vitest.config.ts, test setup, utilities, and sample tests. Also covers mocking patterns, coverage config, workspace setup, and Jest migration. Trigger with 'set up vitest', 'add tests', 'configure vitest', 'migrate from jest', 'vitest config', 'add unit tests', or 'testing setup'.","MIT","https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fvitest\u002FSKILL.md",[223,224],{"categoryNo":153,"categoryName":154,"taxonomyType":139,"taxonomyTypeDesc":140},{"categoryNo":225,"categoryName":226,"taxonomyType":139,"taxonomyTypeDesc":140},"01JBSEEDCAT000000000000009","前端开发",[218,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246],"cloudflare","cloudflare workers","config","node","sample","react","jest","migrate","configure","Utilities","up","testing","workspace setup","project","unit","SET","coverage","test setup","patterns",{"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":253,"publishedAt":43},"01M719SGV9R1N88QWAB7Y925HD","verification-loops","Use when about to claim work is complete, fixed, or passing, before committing or creating PRs. Requires running verification commands and confirming output before making any success claims. Evidence before assertions always.","https:\u002F\u002Fgithub.com\u002Fdahaliztupe-sketch\u002FKalmeron-Two\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fverification-loops\u002FSKILL.md",[],[254,255,256,257,167,258,259,260,261,262,263,264,164,265,266,39],"loops","verification","verification loops","claim","assertions","prs","complete","evidence","running","commands","about","claims","output"]