[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-anthropic-comps-analysis":3,"mdc--txepnn-key":39,"related-repo-anthropic-comps-analysis":3807,"related-org-anthropic-comps-analysis":3917},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":12,"stars":29,"repoUrl":30,"updatedAt":31,"license":32,"forks":33,"topics":34,"repo":35,"sourceUrl":37,"mdContent":38},"comps-analysis","build comparable company valuation analyses","Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel\u002Fspreadsheet format.\n\n**Perfect for:**\n- Public company valuation (M&A, investment analysis)\n- Benchmarking performance vs. industry peers\n- Pricing IPOs or funding rounds\n- Identifying valuation outliers (over\u002Funder-valued)\n- Supporting investment committee presentations\n- Creating sector overview reports\n\n**Not ideal for:**\n- Private companies without comparable public peers\n- Highly diversified conglomerates\n- Distressed\u002Fbankrupt companies\n- Pre-revenue startups\n- Companies with unique business models\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},"anthropic","Anthropic","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fanthropic.png","anthropics",[13,17,20,23,26],{"name":14,"slug":15,"type":16},"Valuation","valuation","tag",{"name":18,"slug":19,"type":16},"Excel","excel",{"name":21,"slug":22,"type":16},"Finance","finance",{"name":24,"slug":25,"type":16},"Spreadsheets","spreadsheets",{"name":27,"slug":28,"type":16},"Investment Banking","investment-banking",33636,"https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services","2026-05-15T06:08:40.106962",null,4964,[],{"repoUrl":30,"stars":29,"forks":33,"topics":36,"description":32},[],"https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services\u002Ftree\u002FHEAD\u002Fplugins\u002Fagent-plugins\u002Fpitch-agent\u002Fskills\u002Fcomps-analysis","---\nname: comps-analysis\ndescription: |\n  Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel\u002Fspreadsheet format.\n\n  **Perfect for:**\n  - Public company valuation (M&A, investment analysis)\n  - Benchmarking performance vs. industry peers\n  - Pricing IPOs or funding rounds\n  - Identifying valuation outliers (over\u002Funder-valued)\n  - Supporting investment committee presentations\n  - Creating sector overview reports\n\n  **Not ideal for:**\n  - Private companies without comparable public peers\n  - Highly diversified conglomerates\n  - Distressed\u002Fbankrupt companies\n  - Pre-revenue startups\n  - Companies with unique business models\n---\n\n# Comparable Company Analysis\n\n## ⚠️ CRITICAL: Data Source Priority (READ FIRST)\n\n**ALWAYS follow this data source hierarchy:**\n\n1. **FIRST: Check for MCP data sources** - If S&P Kensho MCP, FactSet MCP, or Daloopa MCP are available, use them exclusively for financial and trading information\n2. **DO NOT use web search** if the above MCP data sources are available\n3. **ONLY if MCPs are unavailable:** Then use Bloomberg Terminal, SEC EDGAR filings, or other institutional sources\n4. **NEVER use web search as a primary data source** - it lacks the accuracy, audit trails, and reliability required for institutional-grade analysis\n\n**Why this matters:** MCP sources provide verified, institutional-grade data with proper citations. Web search results can be outdated, inaccurate, or unreliable for financial analysis.\n\n---\n\n## Overview\nThis skill teaches Claude to build institutional-grade comparable company analyses that combine operating metrics, valuation multiples, and statistical benchmarking. The output is a structured Excel\u002Fspreadsheet that enables informed investment decisions through peer comparison.\n\n**Reference Material & Contextualization:**\n\nAn example comparable company analysis is provided in `examples\u002Fcomps_example.xlsx`. When using this or other example files in this skill directory, use them intelligently:\n\n**DO use examples for:**\n- Understanding structural hierarchy (how sections flow)\n- Grasping the level of rigor expected (statistical depth, documentation standards)\n- Learning principles (clear headers, transparent formulas, audit trails)\n\n**DO NOT use examples for:**\n- Exact reproduction of format or metrics\n- Copying layout without considering context\n- Applying the same visual style regardless of audience\n\n**ALWAYS ask yourself first:**\n1. **\"Do you have a preferred format or should I adapt the template style?\"**\n2. **\"Who is the audience?\"** (Investment committee, board presentation, quick reference, detailed memo)\n3. **\"What's the key question?\"** (Valuation, growth analysis, competitive positioning, efficiency)\n4. **\"What's the context?\"** (M&A evaluation, investment decision, sector benchmarking, performance review)\n\n**Adapt based on specifics:**\n- **Industry context**: Big tech mega-caps need different metrics than emerging SaaS startups\n- **Sector-specific needs**: Add relevant metrics early (e.g., cloud ARR, enterprise customers, developer ecosystem for tech)\n- **Company familiarity**: Well-known companies may need less background, more focus on delta analysis\n- **Decision type**: M&A requires different emphasis than ongoing portfolio monitoring\n\n**Core principle:** Use template principles (clear structure, statistical rigor, transparent formulas) but vary execution based on context. The goal is institutional-quality analysis, not institutional-looking templates.\n\nUser-provided examples and explicit preferences always take precedence over defaults.\n\n## Core Philosophy\n**\"Build the right structure first, then let the data tell the story.\"**\n\nStart with headers that force strategic thinking about what matters, input clean data, build transparent formulas, and let statistics emerge automatically. A good comp should be immediately readable by someone who didn't build it.\n\n---\n\n## ⚠️ CRITICAL: Formulas Over Hardcodes + Step-by-Step Verification\n\n**Environment — Office JS vs Python:**\n- **If running inside Excel (Office Add-in \u002F Office JS):** Use Office JS directly (`Excel.run(async (context) => {...})`). Write formulas via `range.formulas = [[\"=E7\u002FC7\"]]`, not `range.values`. No separate recalc step — Excel handles it natively. Use `range.format.*` for colors\u002Ffonts.\n- **If generating a standalone .xlsx file:** Use Python\u002Fopenpyxl. Write `cell.value = \"=E7\u002FC7\"` (formula string).\n- Same principles either way — just translate the API calls.\n- **Office JS merged cell pitfall:** Do NOT call `.merge()` then set `.values` on the merged range (throws `InvalidArgument` — range still reports its pre-merge dimensions). Instead write the value to the top-left cell alone, then merge + format the full range:\n  ```js\n  ws.getRange(\"A1\").values = [[\"TECHNOLOGY — COMPARABLE COMPANY ANALYSIS\"]];\n  const hdr = ws.getRange(\"A1:H1\");\n  hdr.merge();\n  hdr.format.fill.color = \"#1F4E79\";\n  hdr.format.font.color = \"#FFFFFF\";\n  hdr.format.font.bold = true;\n  ```\n\n**Formulas, not hardcodes:**\n- Every derived value (margin, multiple, statistic) MUST be an Excel formula referencing input cells — never a pre-computed number pasted in\n- When using Python\u002Fopenpyxl to build the sheet: write `cell.value = \"=E7\u002FC7\"` (formula string), NOT `cell.value = 0.687` (computed result)\n- The only hardcoded values should be raw input data (revenue, EBITDA, share price, etc.) — and every one of those gets a cell comment with its source\n- Why: the model must update automatically when an input changes. A hardcoded margin is a silent bug waiting to happen.\n\n**Verify step-by-step with the user:**\n- After setting up the structure → show the user the header layout before filling data\n- After entering raw inputs → show the user the input block and confirm sources\u002Fperiods before building formulas\n- After building operating metrics formulas → show the calculated margins and sanity-check with the user before moving to valuation\n- After building valuation multiples → show the multiples and confirm they look reasonable before adding statistics\n- Do NOT build the entire sheet end-to-end and then present it — catch errors early by confirming each section\n\n---\n\n## Section 1: Document Structure & Setup\n\n### Header Block (Rows 1-3)\n```\nRow 1: [ANALYSIS TITLE] - COMPARABLE COMPANY ANALYSIS\nRow 2: [List of Companies with Tickers] • [Company 1 (TICK1)] • [Company 2 (TICK2)] • [Company 3 (TICK3)]\nRow 3: As of [Period] | All figures in [USD Millions\u002FBillions] except per-share amounts and ratios\n```\n\n**Why this matters:** Establishes context immediately. Anyone opening this file knows what they're looking at, when it was created, and how to interpret the numbers.\n\n### Visual Convention Standards (OPTIONAL - User preferences and uploaded templates always override)\n\n**IMPORTANT: These are suggested defaults only. Always prioritize:**\n1. User's explicit formatting preferences\n2. Formatting from any uploaded template files\n3. Company\u002Fteam style guides\n4. These defaults (only if no other guidance provided)\n\n**Suggested Font & Typography:**\n- **Font family**: Times New Roman (professional, readable, industry standard)\n- **Font size**: 11pt for data cells, 12pt for headers\n- **Bold text**: Section headers, company names, statistic labels\n\n**Default Color & Shading — Professional Blue\u002FGrey Palette (minimal is better):**\n- **Keep it restrained** — only blues and greys. Do NOT introduce greens, oranges, reds, or multiple accent colors. A clean comps sheet uses 3-4 colors total.\n- **Section headers** (e.g., \"OPERATING STATISTICS & FINANCIAL METRICS\"):\n  - Dark blue background (`#1F4E79` or `#17365D` navy)\n  - White bold text\n  - Full row shading across all columns\n- **Column headers** (e.g., \"Company\", \"Revenue\", \"Margin\"):\n  - Light blue background (`#D9E1F2` or similar pale blue)\n  - Black bold text\n  - Centered alignment\n- **Data rows**:\n  - White background for company data\n  - Black text for formulas; blue text for hardcoded inputs\n- **Statistics rows** (Maximum, 75th Percentile, etc.):\n  - Light grey background (`#F2F2F2`)\n  - Black text, left-aligned labels\n- **That's the whole palette**: dark blue + light blue + light grey + white. Nothing else unless the user's template says otherwise.\n\n**Suggested Formatting Conventions:**\n- **Decimal precision**:\n  - Percentages: 1 decimal (12.3%)\n  - Multiples: 1 decimal (13.5x)\n  - Dollar amounts: No decimals, thousands separator (69,632)\n  - Margins shown as percentages: 1 decimal (68.7%)\n- **Borders**: No borders (clean, minimal appearance)\n- **Alignment**: All metrics center-aligned for clean, uniform appearance\n- **Cell dimensions**: All column widths should be uniform\u002Feven, all row heights should be consistent (creates clean, professional grid)\n\n**Note:** If the user provides a template file or specifies different formatting, use that instead.\n\n---\n\n## Section 2: Operating Statistics & Financial Metrics\n\n### Core Columns (Start with these)\n1. **Company** - Names with consistent formatting\n2. **Revenue** - Size metric (can be LTM, quarterly, or annual depending on context)\n3. **Revenue Growth** - Year-over-year percentage change\n4. **Gross Profit** - Revenue minus cost of goods sold\n5. **Gross Margin** - GP\u002FRevenue (fundamental profitability)\n6. **EBITDA** - Earnings before interest, tax, depreciation, amortization\n7. **EBITDA Margin** - EBITDA\u002FRevenue (operating efficiency)\n\n### Optional Additions (Choose based on industry\u002Fpurpose)\n- **Quarterly vs LTM** - Include both if seasonality matters\n- **Free Cash Flow** - For capital-intensive or SaaS businesses\n- **FCF Margin** - FCF\u002FRevenue (cash generation efficiency)\n- **Net Income** - For mature, profitable companies\n- **Operating Income** - For businesses with varying D&A\n- **CapEx metrics** - For asset-heavy industries\n- **Rule of 40** - Specifically for SaaS (Growth % + Margin %)\n- **FCF Conversion** - For quality of earnings analysis (advanced)\n\n### Formula Examples (Using Row 7 as example)\n```excel\n\u002F\u002F Core ratios - these are always calculated\nGross Margin (F7): =E7\u002FC7\nEBITDA Margin (H7): =G7\u002FC7\n\n\u002F\u002F Optional ratios - include if relevant\nFCF Margin: =[FCF]\u002F[Revenue]\nNet Margin: =[Net Income]\u002F[Revenue]\nRule of 40: =[Growth %]+[FCF Margin %]\n```\n\n**Golden Rule:** Every ratio should be [Something] \u002F [Revenue] or [Something] \u002F [Something from this sheet]. Keep it simple.\n\n### Statistics Block (After company data)\n\n**CRITICAL: Add statistics formulas for all comparable metrics (ratios, margins, growth rates, multiples).**\n\n```\n[Leave one blank row for visual separation]\n- Maximum: =MAX(B7:B9)\n- 75th Percentile: =QUARTILE(B7:B9,3)\n- Median: =MEDIAN(B7:B9)\n- 25th Percentile: =QUARTILE(B7:B9,1)\n- Minimum: =MIN(B7:B9)\n```\n\n**Columns that NEED statistics (comparable metrics):**\n- Revenue Growth %, Gross Margin %, EBITDA Margin %, EPS\n- EV\u002FRevenue, EV\u002FEBITDA, P\u002FE, Dividend Yield %, Beta\n\n**Columns that DON'T need statistics (size metrics):**\n- Revenue, EBITDA, Net Income (absolute size varies by company scale)\n- Market Cap, Enterprise Value (not comparable across different-sized companies)\n\n**Note:** Add one blank row between company data and statistics rows for visual separation. Do NOT add a \"SECTOR STATISTICS\" or \"VALUATION STATISTICS\" header row.\n\n**Why quartiles matter:** They show distribution, not just average. A 75th percentile multiple tells you what \"premium\" companies trade at.\n\n---\n\n## Section 3: Valuation Multiples & Investment Metrics\n\n### Core Valuation Columns (Start with these)\n1. **Company** - Same order as operating section\n2. **Market Cap** - Current market valuation\n3. **Enterprise Value** - Market Cap ± Net Debt\u002FCash\n4. **EV\u002FRevenue** - How much market pays per dollar of sales\n5. **EV\u002FEBITDA** - How much market pays per dollar of earnings\n6. **P\u002FE Ratio** - Price relative to net earnings\n\n### Optional Valuation Metrics (Choose based on context)\n- **FCF Yield** - FCF\u002FMarket Cap (for cash-focused analysis)\n- **PEG Ratio** - P\u002FE\u002FGrowth Rate (for growth companies)\n- **Price\u002FBook** - Market value vs. book value (for asset-heavy businesses)\n- **ROE\u002FROA** - Return metrics (for profitability comparison)\n- **Revenue\u002FEBITDA CAGR** - Historical growth rates (for trend analysis)\n- **Asset Turnover** - Revenue\u002FAssets (for operational efficiency)\n- **Debt\u002FEquity** - Leverage (for capital structure analysis)\n\n**Key Principle:** Include 3-5 core multiples that matter for your industry. Don't include every possible metric just because you can.\n\n### Formula Examples\n```excel\n\u002F\u002F Core multiples - always include these\nEV\u002FRevenue: =[Enterprise Value]\u002F[LTM Revenue]\nEV\u002FEBITDA: =[Enterprise Value]\u002F[LTM EBITDA]\nP\u002FE Ratio: =[Market Cap]\u002F[Net Income]\n\n\u002F\u002F Optional multiples - include if data available\nFCF Yield: =[LTM FCF]\u002F[Market Cap]\nPEG Ratio: =[P\u002FE]\u002F[Growth Rate %]\n```\n\n### Cross-Reference Rule\n**CRITICAL:** Valuation multiples MUST reference the operating metrics section. Never input the same raw data twice. If revenue is in C7, then EV\u002FRevenue formula should reference C7.\n\n### Statistics Block\nSame structure as operating section: Max, 75th, Median, 25th, Min for every metric. Add one blank row for visual separation between company data and statistics. Do NOT add a \"VALUATION STATISTICS\" header row.\n\n---\n\n## Section 4: Notes & Methodology Documentation\n\n### Required Components\n\n**Data Sources & Quality:**\n- Where did the data come from? (S&P Kensho MCP, FactSet MCP, Daloopa MCP, Bloomberg, SEC filings)\n- What period does it cover? (Q4 2024, audited figures)\n- How was it verified? (Cross-checked against 10-K\u002F10-Q)\n- Note: Prioritize MCP data sources (S&P Kensho, FactSet, Daloopa) if available for better accuracy and traceability\n\n**Key Definitions:**\n- EBITDA calculation method (Gross Profit + D&A, or Operating Income + D&A)\n- Free Cash Flow formula (Operating CF - CapEx)\n- Special metrics explained (Rule of 40, FCF Conversion)\n- Time period definitions (LTM, CAGR calculation periods)\n\n**Valuation Methodology:**\n- How was Enterprise Value calculated? (Market Cap + Net Debt)\n- What growth rates were used? (Historical CAGR, forward estimates)\n- Any adjustments made? (One-time items excluded, normalized margins)\n\n**Analysis Framework:**\n- What's the investment thesis? (Cloud\u002FSaaS efficiency)\n- What metrics matter most? (Cash generation, capital efficiency)\n- How should readers interpret the statistics? (Quartiles provide context)\n\n---\n\n## Section 5: Choosing the Right Metrics (Decision Framework)\n\n### Start with \"What question am I answering?\"\n\n**\"Which company is undervalued?\"**\n→ Focus on: EV\u002FRevenue, EV\u002FEBITDA, P\u002FE, Market Cap\n→ Skip: Operational details, growth metrics\n\n**\"Which company is most efficient?\"**\n→ Focus on: Gross Margin, EBITDA Margin, FCF Margin, Asset Turnover\n→ Skip: Size metrics, absolute dollar amounts\n\n**\"Which company is growing fastest?\"**\n→ Focus on: Revenue Growth %, EBITDA CAGR, User\u002FCustomer Growth\n→ Skip: Margin metrics, leverage ratios\n\n**\"Which is the best cash generator?\"**\n→ Focus on: FCF, FCF Margin, FCF Conversion, CapEx intensity\n→ Skip: EBITDA, P\u002FE ratios\n\n### Industry-Specific Metric Selection\n\n**Software\u002FSaaS:**\nMust have: Revenue Growth, Gross Margin, Rule of 40\nOptional: ARR, Net Dollar Retention, CAC Payback\nSkip: Asset Turnover, Inventory metrics\n\n**Manufacturing\u002FIndustrials:**\nMust have: EBITDA Margin, Asset Turnover, CapEx\u002FRevenue\nOptional: ROA, Inventory Turns, Backlog\nSkip: Rule of 40, SaaS metrics\n\n**Financial Services:**\nMust have: ROE, ROA, Efficiency Ratio, P\u002FE\nOptional: Net Interest Margin, Loan Loss Reserves\nSkip: Gross Margin, EBITDA (not meaningful for banks)\n\n**Retail\u002FE-commerce:**\nMust have: Revenue Growth, Gross Margin, Inventory Turnover\nOptional: Same-Store Sales, Customer Acquisition Cost\nSkip: Heavy R&D or CapEx metrics\n\n### The \"5-10 Rule\"\n\n**5 operating metrics** - Revenue, Growth, 2-3 margins\u002Fefficiency metrics\n**5 valuation metrics** - Market Cap, EV, 3 multiples\n**= 10 total columns** - Enough to tell the story, not so many you lose the thread\n\nIf you have more than 15 metrics, you're probably including noise. Edit ruthlessly.\n\n---\n\n## Section 6: Best Practices & Quality Checks\n\n### Before You Start\n1. **Define the peer group** - Companies must be truly comparable (similar business model, scale, geography)\n2. **Choose the right period** - LTM smooths seasonality; quarterly shows trends\n3. **Standardize units upfront** - Millions vs. billions decision affects everything\n4. **Map data sources** - Know where each number comes from\n\n### As You Build\n1. **Input all raw data first** - Complete the blue text before writing formulas\n2. **Add cell comments to ALL hard-coded inputs** - Right-click cell → Insert Comment → Document source OR assumption\n\n   **For sourced data, cite exactly where it came from:**\n   - Example: \"Bloomberg Terminal - MSFT Equity DES, accessed 2024-10-02\"\n   - Example: \"Q4 2024 10-K filing, page 42, line item 'Total Revenue'\"\n   - Example: \"FactSet consensus estimate as of 2024-10-02\"\n   - **Include hyperlinks when possible**: Right-click cell → Link → paste URL to SEC filing, data source, or report\n\n   **For assumptions, explain the reasoning:**\n   - Example: \"Assumed 15% EBITDA margin based on peer median, company does not disclose\"\n   - Example: \"Estimated Enterprise Value as Market Cap + $50M net debt (from Q3 balance sheet, Q4 not yet available)\"\n   - Example: \"Forward P\u002FE based on street consensus EPS of $3.45 (average of 12 analyst estimates)\"\n\n   **Why this matters**: Enables audit trails, data verification, assumption transparency, and future updates\n3. **Build formulas row by row** - Test each calculation before moving on\n4. **Use absolute references for headers** - $C$6 locks the header row\n5. **Format consistently** - Percentages as percentages, not decimals\n6. **Add conditional formatting** - Highlight outliers automatically\n\n### Sanity Checks\n- **Margin test**: Gross margin > EBITDA margin > Net margin (always true by definition)\n- **Multiple reasonableness**: \n  - EV\u002FRevenue: typically 0.5-20x (varies widely by industry)\n  - EV\u002FEBITDA: typically 8-25x (fairly consistent across industries)\n  - P\u002FE: typically 10-50x (depends on growth rate)\n- **Growth-multiple correlation**: Higher growth usually means higher multiples\n- **Size-efficiency trade-off**: Larger companies often have better margins (scale benefits)\n\n### Common Mistakes to Avoid\n❌ Mixing market cap and enterprise value in formulas\n❌ Using different time periods for numerator and denominator (LTM vs quarterly)\n❌ Hardcoding numbers into formulas instead of cell references\n❌ **Hard-coded inputs without cell comments citing the source OR explaining the assumption**\n❌ Missing hyperlinks to SEC filings or data sources when available\n❌ Including too many metrics without clear purpose\n❌ Including non-comparable companies (different business models)\n❌ Using outdated data without disclosure\n❌ Calculating averages of percentages incorrectly (should be median)\n\n---\n\n## Section 6: Advanced Features\n\n### Dynamic Headers\nFor columns showing calculations, use clear unit labels:\n```\nRevenue Growth (YoY) % | EBITDA Margin | FCF Margin | Rule of 40\n```\n\n### Quartile Analysis Benefits\nInstead of just mean\u002Fmedian, quartiles show:\n- **75th percentile** = \"Premium\" companies trade here\n- **Median** = Typical market valuation\n- **25th percentile** = \"Discount\" territory\n\nThis helps answer: \"Is our target company trading rich or cheap vs. peers?\"\n\n### Industry-Specific Modifications\n\n**Software\u002FSaaS:**\n- Add: ARR, Net Dollar Retention, CAC Payback Period\n- Emphasize: Rule of 40, FCF margins, gross margins >70%\n\n**Healthcare:**\n- Add: R&D\u002FRevenue, Pipeline value, Regulatory status\n- Emphasize: EBITDA margins, growth rates, reimbursement risk\n\n**Industrials:**\n- Add: Backlog, Order book trends, Geographic mix\n- Emphasize: ROIC, asset turnover, cyclical adjustments\n\n**Consumer:**\n- Add: Same-store sales, Customer acquisition cost, Brand value\n- Emphasize: Revenue growth, gross margins, inventory turns\n\n---\n\n## Section 7: Workflow & Practical Tips\n\n### Step-by-Step Process\n1. **Set up structure** (30 minutes)\n   - Create all headers\n   - Format cells (blue for inputs, black for formulas)\n   - Lock in units and date references\n\n2. **Gather data** (60-90 minutes)\n   - Pull from primary sources (S&P Kensho MCP, FactSet MCP, Daloopa MCP if available; otherwise Bloomberg, SEC)\n   - Input all raw numbers in blue\n   - Document sources in notes section\n\n3. **Build formulas** (30 minutes)\n   - Start with simple ratios (margins)\n   - Progress to multiples (EV\u002FRevenue)\n   - Add cross-checks (do margins make sense?)\n\n4. **Add statistics** (15 minutes)\n   - Copy formula structure for all columns\n   - Verify ranges are correct (B7:B9, not B7:B10)\n   - Check quartile logic\n\n5. **Quality control** (30 minutes)\n   - Run sanity checks\n   - Verify formula references\n   - Check for #DIV\u002F0! or #REF! errors\n   - Compare against known benchmarks\n\n6. **Documentation** (15 minutes)\n   - Complete notes section\n   - Add data sources\n   - Define methodologies\n   - Date-stamp the analysis\n\n### Pro Tips\n- **Save templates**: Build once, reuse forever\n- **Color-code outliers**: Conditional formatting for values >2 standard deviations\n- **Link to source files**: Hyperlink to Bloomberg screenshots or SEC filings\n- **Version control**: Save as \"Comps_v1_2024-12-15\" with clear dating\n- **Collaborative reviews**: Have someone else check your formulas\n\n### Excel Formatting Checklist (Optional - adapt to user preferences)\n- [ ] Font set to user's preferred style (default: Times New Roman, 11pt data, 12pt headers)\n- [ ] Section headers formatted per user's template (default: dark blue #17365D with white bold text)\n- [ ] Column headers formatted per user's template (default: light blue\u002Fgray #D9E2F3 with black bold text)\n- [ ] Statistics rows formatted per user's template (default: light gray #F2F2F2)\n- [ ] No borders applied (clean, minimal appearance)\n- [ ] **Column widths set to uniform\u002Feven width** (creates clean, professional appearance)\n- [ ] **Row heights set to consistent height** (typically 20-25pt for data rows)\n- [ ] Numbers formatted with proper decimal precision and thousands separators\n- [ ] **All metrics center-aligned** for clean, uniform appearance\n- [ ] **One blank row for separation between company data and statistics rows**\n- [ ] **No separate \"SECTOR STATISTICS\" or \"VALUATION STATISTICS\" header rows**\n- [ ] **Every hard-coded input cell has a comment with either: (1) exact data source, OR (2) assumption explanation**\n- [ ] **Hyperlinks added to cells where applicable** (SEC filings, data provider pages, reports)\n\n---\n\n## Section 8: Example Template Layout\n\n**Simple Version (Start here):**\n```\n┌─────────────────────────────────────────────────────────────┐\n│ TECHNOLOGY - COMPARABLE COMPANY ANALYSIS                    │\n│ Microsoft • Alphabet • Amazon                               │\n│ As of Q4 2024 | All figures in USD Millions                │\n├─────────────────────────────────────────────────────────────┤\n│ OPERATING METRICS                                           │\n├──────────┬─────────┬─────────┬──────────┬──────────────────┤\n│ Company  │ Revenue │ Growth  │ Gross    │ EBITDA  │ EBITDA │\n│          │ (LTM)   │ (YoY)   │ Margin   │ (LTM)   │ Margin │\n├──────────┼─────────┼─────────┼──────────┼─────────┼────────┤\n│ MSFT     │ 261,400 │ 12.3%   │ 68.7%    │ 205,100 │ 78.4%  │\n│ GOOGL    │ 349,800 │ 11.8%   │ 57.9%    │ 239,300 │ 68.4%  │\n│ AMZN     │ 638,100 │ 10.5%   │ 47.3%    │ 152,600 │ 23.9%  │\n│          │         │         │          │         │        │ [blank row]\n│ Median   │ =MEDIAN │ =MEDIAN │ =MEDIAN  │ =MEDIAN │=MEDIAN │\n│ 75th %   │ =QUART  │ =QUART  │ =QUART   │ =QUART  │=QUART  │\n│ 25th %   │ =QUART  │ =QUART  │ =QUART   │ =QUART  │=QUART  │\n├─────────────────────────────────────────────────────────────┤\n│ VALUATION MULTIPLES                                         │\n├──────────┬──────────┬──────────┬──────────┬────────────────┤\n│ Company  │ Mkt Cap  │ EV       │ EV\u002FRev   │ EV\u002FEBITDA │ P\u002FE│\n├──────────┼──────────┼──────────┼──────────┼───────────┼────┤\n│ MSFT     │3,550,000 │3,530,000 │ 13.5x    │ 17.2x     │36.0│\n│ GOOGL    │2,030,000 │1,960,000 │  5.6x    │  8.2x     │24.5│\n│ AMZN     │2,226,000 │2,320,000 │  3.6x    │ 15.2x     │58.3│\n│          │          │          │          │           │    │ [blank row]\n│ Median   │ =MEDIAN  │ =MEDIAN  │ =MEDIAN  │ =MEDIAN   │=MED│\n│ 75th %   │ =QUART   │ =QUART   │ =QUART   │ =QUART    │=QRT│\n│ 25th %   │ =QUART   │ =QUART   │ =QUART   │ =QUART    │=QRT│\n└──────────┴──────────┴──────────┴──────────┴───────────┴────┘\n```\n\n**Add complexity only when needed:**\n- Include quarterly AND LTM if seasonality matters\n- Add FCF metrics if cash generation is key story\n- Include industry-specific metrics (Rule of 40 for SaaS, etc.)\n- Add more statistics rows if you have >5 companies\n\n---\n\n## Section 9: Industry-Specific Additions (Optional)\n\nOnly add these if they're critical to your analysis. Most comps work fine with just core metrics.\n\n**Software\u002FSaaS:**\nAdd if relevant: ARR, Net Dollar Retention, Rule of 40\n\n**Financial Services:**\nAdd if relevant: ROE, Net Interest Margin, Efficiency Ratio\n\n**E-commerce:**\nAdd if relevant: GMV, Take Rate, Active Buyers\n\n**Healthcare:**\nAdd if relevant: R&D\u002FRevenue, Pipeline Value, Patent Timeline\n\n**Manufacturing:**\nAdd if relevant: Asset Turnover, Inventory Turns, Backlog\n\n---\n\n## Section 10: Red Flags & Warning Signs\n\n### Data Quality Issues\n🚩 Inconsistent time periods (mixing quarterly and annual)  \n🚩 Missing data without explanation  \n🚩 Significant differences between data sources (>10% variance)\n\n### Valuation Red Flags\n🚩 Negative EBITDA companies being valued on EBITDA multiples (use revenue multiples instead)  \n🚩 P\u002FE ratios >100x without hypergrowth story  \n🚩 Margins that don't make sense for the industry\n\n### Comparability Issues\n🚩 Different fiscal year ends (causes timing problems)  \n🚩ixing pure-play and conglomerates  \n🚩 Materially different business models labeled as \"comps\"\n\n**When in doubt, exclude the company.** Better to have 3 perfect comps than 6 questionable ones.\n\n---\n\n## Section 11: Formulas Reference Guide\n\n### Essential Excel Formulas\n```excel\n\u002F\u002F Statistical Functions\n=AVERAGE(range)          \u002F\u002F Simple mean\n=MEDIAN(range)           \u002F\u002F Middle value\n=QUARTILE(range, 1)      \u002F\u002F 25th percentile\n=QUARTILE(range, 3)      \u002F\u002F 75th percentile\n=MAX(range)              \u002F\u002F Maximum value\n=MIN(range)              \u002F\u002F Minimum value\n=STDEV.P(range)          \u002F\u002F Standard deviation\n\n\u002F\u002F Financial Calculations\n=B7\u002FC7                   \u002F\u002F Simple ratio (Margin)\n=SUM(B7:B9)\u002F3            \u002F\u002F Average of multiple companies\n=IF(B7>0, C7\u002FB7, \"N\u002FA\")  \u002F\u002F Conditional calculation\n=IFERROR(C7\u002FD7, 0)       \u002F\u002F Handle divide by zero\n\n\u002F\u002F Cross-Sheet References\n='Sheet1'!B7             \u002F\u002F Reference another sheet\n=VLOOKUP(A7, Table1, 2)  \u002F\u002F Lookup from data table\n=INDEX(MATCH())          \u002F\u002F Advanced lookup\n\n\u002F\u002F Formatting\n=TEXT(B7, \"0.0%\")        \u002F\u002F Format as percentage\n=TEXT(C7, \"#,##0\")       \u002F\u002F Thousands separator\n```\n\n### Common Ratio Formulas\n```excel\nGross Margin = Gross Profit \u002F Revenue\nEBITDA Margin = EBITDA \u002F Revenue\nFCF Margin = Free Cash Flow \u002F Revenue\nFCF Conversion = FCF \u002F Operating Cash Flow\nROE = Net Income \u002F Shareholders' Equity\nROA = Net Income \u002F Total Assets\nAsset Turnover = Revenue \u002F Total Assets\nDebt\u002FEquity = Total Debt \u002F Shareholders' Equity\n```\n\n---\n\n## Key Principles Summary\n\n1. **Structure drives insight** - Right headers force right thinking\n2. **Less is more** - 5-10 metrics that matter beat 20 that don't\n3. **Choose metrics for your question** - Valuation analysis ≠ efficiency analysis\n4. **Statistics show patterns** - Median\u002Fquartiles reveal more than average\n5. **Transparency beats complexity** - Simple formulas everyone understands\n6. **Comparability is king** - Better to exclude than force a bad comp\n7. **Document your choices** - Explain which metrics and why in notes section\n\n---\n\n## Output Checklist\n\nBefore delivering a comp analysis, verify:\n- [ ] All companies are truly comparable\n- [ ] Data is from consistent time periods\n- [ ] Units are clearly labeled (millions\u002Fbillions)\n- [ ] Formulas reference cells, not hardcoded values\n- [ ] **All hard-coded input cells have comments with either: (1) exact data source with citation, OR (2) clear assumption with explanation**\n- [ ] **Hyperlinks added where relevant** (SEC EDGAR filings, Bloomberg pages, research reports)\n- [ ] Statistics include at least 5 metrics (Max, 75th, Med, 25th, Min)\n- [ ] Notes section documents sources and methodology\n- [ ] Visual formatting follows conventions (blue = input, black = formula)\n- [ ] Sanity checks pass (margins logical, multiples reasonable)\n- [ ] Date stamp is current (\"As of [Date]\")\n- [ ] Formula auditing shows no errors (#DIV\u002F0!, #REF!, #N\u002FA)\n\n---\n\n## Continuous Improvement\n\nAfter completing a comp analysis, ask:\n1. Did the statistics reveal unexpected insights?\n2. Were there any data gaps that limited analysis?\n3. Did stakeholders ask for metrics you didn't include?\n4. How long did it take vs. how long should it take?\n5. What would make this more useful next time?\n\nThe best comp analyses evolve with each iteration. Save templates, learn from feedback, and refine the structure based on what decision-makers actually use.\n",{"data":40,"body":41},{"name":4,"description":6},{"type":42,"children":43},"root",[44,53,60,70,115,125,129,135,140,148,162,170,189,197,215,223,264,272,315,325,330,336,344,349,352,358,366,812,820,858,866,894,897,903,910,920,929,935,943,966,974,1007,1015,1170,1178,1243,1253,1256,1262,1268,1341,1347,1430,1436,1511,1545,1551,1559,1568,1576,1589,1597,1610,1619,1629,1632,1638,1644,1706,1712,1785,1795,1801,1871,1877,1887,1893,1898,1901,1907,1913,1921,1944,1952,1975,1983,2001,2009,2027,2030,2036,2042,2052,2062,2072,2082,2088,2098,2108,2118,2128,2134,2158,2163,2166,2172,2178,2221,2227,2363,2369,2429,2435,2447,2450,2456,2462,2467,2476,2482,2487,2520,2525,2531,2538,2551,2559,2572,2580,2593,2601,2614,2617,2623,2629,2807,2813,2866,2872,3034,3037,3043,3051,3060,3068,3091,3094,3100,3105,3114,3123,3133,3142,3152,3155,3161,3167,3182,3188,3203,3209,3224,3234,3237,3243,3249,3452,3458,3529,3532,3538,3611,3614,3620,3625,3754,3757,3763,3768,3796,3801],{"type":45,"tag":46,"props":47,"children":49},"element","h1",{"id":48},"comparable-company-analysis",[50],{"type":51,"value":52},"text","Comparable Company Analysis",{"type":45,"tag":54,"props":55,"children":57},"h2",{"id":56},"️-critical-data-source-priority-read-first",[58],{"type":51,"value":59},"⚠️ CRITICAL: Data Source Priority (READ FIRST)",{"type":45,"tag":61,"props":62,"children":63},"p",{},[64],{"type":45,"tag":65,"props":66,"children":67},"strong",{},[68],{"type":51,"value":69},"ALWAYS follow this data source hierarchy:",{"type":45,"tag":71,"props":72,"children":73},"ol",{},[74,85,95,105],{"type":45,"tag":75,"props":76,"children":77},"li",{},[78,83],{"type":45,"tag":65,"props":79,"children":80},{},[81],{"type":51,"value":82},"FIRST: Check for MCP data sources",{"type":51,"value":84}," - If S&P Kensho MCP, FactSet MCP, or Daloopa MCP are available, use them exclusively for financial and trading information",{"type":45,"tag":75,"props":86,"children":87},{},[88,93],{"type":45,"tag":65,"props":89,"children":90},{},[91],{"type":51,"value":92},"DO NOT use web search",{"type":51,"value":94}," if the above MCP data sources are available",{"type":45,"tag":75,"props":96,"children":97},{},[98,103],{"type":45,"tag":65,"props":99,"children":100},{},[101],{"type":51,"value":102},"ONLY if MCPs are unavailable:",{"type":51,"value":104}," Then use Bloomberg Terminal, SEC EDGAR filings, or other institutional sources",{"type":45,"tag":75,"props":106,"children":107},{},[108,113],{"type":45,"tag":65,"props":109,"children":110},{},[111],{"type":51,"value":112},"NEVER use web search as a primary data source",{"type":51,"value":114}," - it lacks the accuracy, audit trails, and reliability required for institutional-grade analysis",{"type":45,"tag":61,"props":116,"children":117},{},[118,123],{"type":45,"tag":65,"props":119,"children":120},{},[121],{"type":51,"value":122},"Why this matters:",{"type":51,"value":124}," MCP sources provide verified, institutional-grade data with proper citations. Web search results can be outdated, inaccurate, or unreliable for financial analysis.",{"type":45,"tag":126,"props":127,"children":128},"hr",{},[],{"type":45,"tag":54,"props":130,"children":132},{"id":131},"overview",[133],{"type":51,"value":134},"Overview",{"type":45,"tag":61,"props":136,"children":137},{},[138],{"type":51,"value":139},"This skill teaches Claude to build institutional-grade comparable company analyses that combine operating metrics, valuation multiples, and statistical benchmarking. The output is a structured Excel\u002Fspreadsheet that enables informed investment decisions through peer comparison.",{"type":45,"tag":61,"props":141,"children":142},{},[143],{"type":45,"tag":65,"props":144,"children":145},{},[146],{"type":51,"value":147},"Reference Material & Contextualization:",{"type":45,"tag":61,"props":149,"children":150},{},[151,153,160],{"type":51,"value":152},"An example comparable company analysis is provided in ",{"type":45,"tag":154,"props":155,"children":157},"code",{"className":156},[],[158],{"type":51,"value":159},"examples\u002Fcomps_example.xlsx",{"type":51,"value":161},". 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The goal is institutional-quality analysis, not institutional-looking templates.",{"type":45,"tag":61,"props":326,"children":327},{},[328],{"type":51,"value":329},"User-provided examples and explicit preferences always take precedence over defaults.",{"type":45,"tag":54,"props":331,"children":333},{"id":332},"core-philosophy",[334],{"type":51,"value":335},"Core Philosophy",{"type":45,"tag":61,"props":337,"children":338},{},[339],{"type":45,"tag":65,"props":340,"children":341},{},[342],{"type":51,"value":343},"\"Build the right structure first, then let the data tell the story.\"",{"type":45,"tag":61,"props":345,"children":346},{},[347],{"type":51,"value":348},"Start with headers that force strategic thinking about what matters, input clean data, build transparent formulas, and let statistics emerge automatically. 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Valuation analysis ≠ efficiency analysis",{"type":45,"tag":75,"props":3572,"children":3573},{},[3574,3579],{"type":45,"tag":65,"props":3575,"children":3576},{},[3577],{"type":51,"value":3578},"Statistics show patterns",{"type":51,"value":3580}," - Median\u002Fquartiles reveal more than average",{"type":45,"tag":75,"props":3582,"children":3583},{},[3584,3589],{"type":45,"tag":65,"props":3585,"children":3586},{},[3587],{"type":51,"value":3588},"Transparency beats complexity",{"type":51,"value":3590}," - Simple formulas everyone understands",{"type":45,"tag":75,"props":3592,"children":3593},{},[3594,3599],{"type":45,"tag":65,"props":3595,"children":3596},{},[3597],{"type":51,"value":3598},"Comparability is king",{"type":51,"value":3600}," - Better to exclude than force a bad comp",{"type":45,"tag":75,"props":3602,"children":3603},{},[3604,3609],{"type":45,"tag":65,"props":3605,"children":3606},{},[3607],{"type":51,"value":3608},"Document your choices",{"type":51,"value":3610}," - Explain which metrics and why in notes section",{"type":45,"tag":126,"props":3612,"children":3613},{},[],{"type":45,"tag":54,"props":3615,"children":3617},{"id":3616},"output-checklist",[3618],{"type":51,"value":3619},"Output Checklist",{"type":45,"tag":61,"props":3621,"children":3622},{},[3623],{"type":51,"value":3624},"Before delivering a comp analysis, verify:",{"type":45,"tag":171,"props":3626,"children":3628},{"className":3627},[2875],[3629,3638,3647,3656,3665,3678,3693,3702,3711,3720,3729,3745],{"type":45,"tag":75,"props":3630,"children":3632},{"className":3631},[2880],[3633,3636],{"type":45,"tag":2883,"props":3634,"children":3635},{"disabled":1473,"type":2885},[],{"type":51,"value":3637}," All companies are truly comparable",{"type":45,"tag":75,"props":3639,"children":3641},{"className":3640},[2880],[3642,3645],{"type":45,"tag":2883,"props":3643,"children":3644},{"disabled":1473,"type":2885},[],{"type":51,"value":3646}," Data is from consistent time periods",{"type":45,"tag":75,"props":3648,"children":3650},{"className":3649},[2880],[3651,3654],{"type":45,"tag":2883,"props":3652,"children":3653},{"disabled":1473,"type":2885},[],{"type":51,"value":3655}," Units are clearly labeled (millions\u002Fbillions)",{"type":45,"tag":75,"props":3657,"children":3659},{"className":3658},[2880],[3660,3663],{"type":45,"tag":2883,"props":3661,"children":3662},{"disabled":1473,"type":2885},[],{"type":51,"value":3664}," Formulas reference cells, not hardcoded values",{"type":45,"tag":75,"props":3666,"children":3668},{"className":3667},[2880],[3669,3672,3673],{"type":45,"tag":2883,"props":3670,"children":3671},{"disabled":1473,"type":2885},[],{"type":51,"value":2933},{"type":45,"tag":65,"props":3674,"children":3675},{},[3676],{"type":51,"value":3677},"All hard-coded input cells have comments with either: (1) exact data source with citation, OR (2) clear assumption with explanation",{"type":45,"tag":75,"props":3679,"children":3681},{"className":3680},[2880],[3682,3685,3686,3691],{"type":45,"tag":2883,"props":3683,"children":3684},{"disabled":1473,"type":2885},[],{"type":51,"value":2933},{"type":45,"tag":65,"props":3687,"children":3688},{},[3689],{"type":51,"value":3690},"Hyperlinks added where relevant",{"type":51,"value":3692}," (SEC EDGAR filings, Bloomberg pages, research reports)",{"type":45,"tag":75,"props":3694,"children":3696},{"className":3695},[2880],[3697,3700],{"type":45,"tag":2883,"props":3698,"children":3699},{"disabled":1473,"type":2885},[],{"type":51,"value":3701}," Statistics include at least 5 metrics (Max, 75th, Med, 25th, Min)",{"type":45,"tag":75,"props":3703,"children":3705},{"className":3704},[2880],[3706,3709],{"type":45,"tag":2883,"props":3707,"children":3708},{"disabled":1473,"type":2885},[],{"type":51,"value":3710}," Notes section documents sources and methodology",{"type":45,"tag":75,"props":3712,"children":3714},{"className":3713},[2880],[3715,3718],{"type":45,"tag":2883,"props":3716,"children":3717},{"disabled":1473,"type":2885},[],{"type":51,"value":3719}," Visual formatting follows conventions (blue = input, black = formula)",{"type":45,"tag":75,"props":3721,"children":3723},{"className":3722},[2880],[3724,3727],{"type":45,"tag":2883,"props":3725,"children":3726},{"disabled":1473,"type":2885},[],{"type":51,"value":3728}," Sanity checks pass (margins logical, multiples reasonable)",{"type":45,"tag":75,"props":3730,"children":3732},{"className":3731},[2880],[3733,3736,3738,3743],{"type":45,"tag":2883,"props":3734,"children":3735},{"disabled":1473,"type":2885},[],{"type":51,"value":3737}," Date stamp is current (\"As of ",{"type":45,"tag":480,"props":3739,"children":3740},{},[3741],{"type":51,"value":3742},"Date",{"type":51,"value":3744},"\")",{"type":45,"tag":75,"props":3746,"children":3748},{"className":3747},[2880],[3749,3752],{"type":45,"tag":2883,"props":3750,"children":3751},{"disabled":1473,"type":2885},[],{"type":51,"value":3753}," Formula auditing shows no errors (#DIV\u002F0!, #REF!, #N\u002FA)",{"type":45,"tag":126,"props":3755,"children":3756},{},[],{"type":45,"tag":54,"props":3758,"children":3760},{"id":3759},"continuous-improvement",[3761],{"type":51,"value":3762},"Continuous Improvement",{"type":45,"tag":61,"props":3764,"children":3765},{},[3766],{"type":51,"value":3767},"After completing a comp analysis, ask:",{"type":45,"tag":71,"props":3769,"children":3770},{},[3771,3776,3781,3786,3791],{"type":45,"tag":75,"props":3772,"children":3773},{},[3774],{"type":51,"value":3775},"Did the statistics reveal unexpected insights?",{"type":45,"tag":75,"props":3777,"children":3778},{},[3779],{"type":51,"value":3780},"Were there any data gaps that limited analysis?",{"type":45,"tag":75,"props":3782,"children":3783},{},[3784],{"type":51,"value":3785},"Did stakeholders ask for metrics you didn't include?",{"type":45,"tag":75,"props":3787,"children":3788},{},[3789],{"type":51,"value":3790},"How long did it take vs. how long should it take?",{"type":45,"tag":75,"props":3792,"children":3793},{},[3794],{"type":51,"value":3795},"What would make this more useful next time?",{"type":45,"tag":61,"props":3797,"children":3798},{},[3799],{"type":51,"value":3800},"The best comp analyses evolve with each iteration. Save templates, learn from feedback, and refine the structure based on what decision-makers actually use.",{"type":45,"tag":3802,"props":3803,"children":3804},"style",{},[3805],{"type":51,"value":3806},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":3808,"total":3916},[3809,3824,3841,3860,3873,3890,3900],{"slug":3810,"name":3810,"fn":3811,"description":3812,"org":3813,"tags":3814,"stars":29,"repoUrl":30,"updatedAt":3823},"3-statement-model","fill out 3-statement financial models","Complete, populate and fill out 3-statement financial model templates (Income Statement, Balance Sheet, Cash Flow Statement) . Use when asked to fill out model templates, complete existing model frameworks, populate financial models with data, complete a partially filled IS\u002FBS\u002FCF framework, or link integrated financial statements within an existing template structure. Triggers include requests to fill in, complete, or populate a 3-statement model template",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3815,3816,3817,3820],{"name":18,"slug":19,"type":16},{"name":21,"slug":22,"type":16},{"name":3818,"slug":3819,"type":16},"Financial Modeling","financial-modeling",{"name":3821,"slug":3822,"type":16},"Financial Statements","financial-statements","2026-05-15T06:08:35.416766",{"slug":3825,"name":3825,"fn":3826,"description":3827,"org":3828,"tags":3829,"stars":29,"repoUrl":30,"updatedAt":3840},"accrual-schedule","build period-end accrual schedules","Build the period-end accrual schedule — for each accrual, compute the entry, cite the support, and draft the JE. Use during month-end close; the JE is a draft for controller approval, not a posting.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3830,3833,3834,3837],{"name":3831,"slug":3832,"type":16},"Accounting","accounting",{"name":21,"slug":22,"type":16},{"name":3835,"slug":3836,"type":16},"Journal Entry","journal-entry",{"name":3838,"slug":3839,"type":16},"Month-End Close","month-end-close","2026-05-06T05:38:41.445686",{"slug":3842,"name":3842,"fn":3843,"description":3844,"org":3845,"tags":3846,"stars":29,"repoUrl":30,"updatedAt":3859},"ai-readiness","identify AI opportunities in portfolio companies","Scan the portfolio for the highest-leverage AI opportunities and rank where to deploy operating-partner time. Ingests quarterly updates and financials across multiple portfolio companies, identifies quick wins at each, and stacks them into a single ranked action list. Use during quarterly portfolio reviews, annual planning, or when deciding which companies get AI investment first. Triggers on \"AI readiness\", \"AI opportunity scan\", \"where should we deploy AI\", \"AI across the portfolio\", \"AI quick wins\", or \"which portcos are ready for AI\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3847,3850,3853,3856],{"name":3848,"slug":3849,"type":16},"AI Infrastructure","ai-infrastructure",{"name":3851,"slug":3852,"type":16},"Operations","operations",{"name":3854,"slug":3855,"type":16},"Private Equity","private-equity",{"name":3857,"slug":3858,"type":16},"Strategy","strategy","2026-05-21T06:50:36.056814",{"slug":3861,"name":3861,"fn":3862,"description":3863,"org":3864,"tags":3865,"stars":29,"repoUrl":30,"updatedAt":3872},"audit-xls","audit spreadsheets for formula accuracy","Audit a spreadsheet for formula accuracy, errors, and common mistakes. Scopes to a selected range, a single sheet, or the entire model (including financial-model integrity checks like BS balance, cash tie-out, and logic sanity). Triggers on \"audit this sheet\", \"check my formulas\", \"find formula errors\", \"QA this spreadsheet\", \"sanity check this\", \"debug model\", \"model check\", \"model won't balance\", \"something's off in my model\", \"model review\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3866,3869,3870,3871],{"name":3867,"slug":3868,"type":16},"Audit","audit",{"name":18,"slug":19,"type":16},{"name":21,"slug":22,"type":16},{"name":24,"slug":25,"type":16},"2026-05-15T06:07:23.536125",{"slug":3874,"name":3874,"fn":3875,"description":3876,"org":3877,"tags":3878,"stars":29,"repoUrl":30,"updatedAt":3889},"bond-futures-basis","analyze bond futures basis","Analyze the bond futures basis by pricing futures, identifying the cheapest-to-deliver, and comparing with yield curves to assess delivery option value and basis trading opportunities. Use when analyzing bond futures, computing the basis, identifying CTD bonds, calculating implied repo rates, or evaluating basis trades.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3879,3882,3883,3886],{"name":3880,"slug":3881,"type":16},"Derivatives","derivatives",{"name":21,"slug":22,"type":16},{"name":3884,"slug":3885,"type":16},"Fixed Income","fixed-income",{"name":3887,"slug":3888,"type":16},"Trading","trading","2026-05-15T06:08:13.647174",{"slug":3891,"name":3891,"fn":3892,"description":3893,"org":3894,"tags":3895,"stars":29,"repoUrl":30,"updatedAt":3899},"bond-relative-value","perform bond relative value analysis","Perform relative value analysis on bonds by combining pricing, yield curve context, credit spreads, and scenario stress testing. Use when analyzing bond richness\u002Fcheapness, computing spread decomposition, comparing bonds, assessing bond value vs curves, or running rate shock scenarios.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3896,3897,3898],{"name":21,"slug":22,"type":16},{"name":3884,"slug":3885,"type":16},{"name":3887,"slug":3888,"type":16},"2026-05-15T06:08:11.151011",{"slug":3901,"name":3901,"fn":3902,"description":3903,"org":3904,"tags":3905,"stars":29,"repoUrl":30,"updatedAt":3915},"break-trace","trace reconciliation breaks to source transactions","Root-cause a reconciliation break to its source transaction or posting — follow the audit trail from the break row back to the originating entry on each side and state what differs and why. Use after gl-recon has classified a break.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3906,3907,3908,3911,3912],{"name":3831,"slug":3832,"type":16},{"name":3867,"slug":3868,"type":16},{"name":3909,"slug":3910,"type":16},"Debugging","debugging",{"name":21,"slug":22,"type":16},{"name":3913,"slug":3914,"type":16},"Reconciliation","reconciliation","2026-05-06T05:37:42.364074",62,{"items":3918,"total":4104},[3919,3940,3954,3966,3985,3997,4018,4038,4052,4067,4075,4088],{"slug":3920,"name":3920,"fn":3921,"description":3922,"org":3923,"tags":3924,"stars":3937,"repoUrl":3938,"updatedAt":3939},"algorithmic-art","create algorithmic art with p5.js","Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3925,3928,3931,3934],{"name":3926,"slug":3927,"type":16},"Creative","creative",{"name":3929,"slug":3930,"type":16},"Design","design",{"name":3932,"slug":3933,"type":16},"Generative Art","generative-art",{"name":3935,"slug":3936,"type":16},"JavaScript","javascript",161831,"https:\u002F\u002Fgithub.com\u002Fanthropics\u002Fskills","2026-04-06T17:56:15.455818",{"slug":3941,"name":3941,"fn":3942,"description":3943,"org":3944,"tags":3945,"stars":3937,"repoUrl":3938,"updatedAt":3953},"brand-guidelines","apply Anthropic brand colors and typography","Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3946,3949,3950],{"name":3947,"slug":3948,"type":16},"Branding","branding",{"name":3929,"slug":3930,"type":16},{"name":3951,"slug":3952,"type":16},"Typography","typography","2026-04-06T17:56:05.042852",{"slug":3955,"name":3955,"fn":3956,"description":3957,"org":3958,"tags":3959,"stars":3937,"repoUrl":3938,"updatedAt":3965},"canvas-design","create posters and visual art as PNG or PDF","Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3960,3961,3962],{"name":3926,"slug":3927,"type":16},{"name":3929,"slug":3930,"type":16},{"name":3963,"slug":3964,"type":16},"PDF","pdf","2026-04-06T17:56:03.794732",{"slug":3967,"name":3967,"fn":3968,"description":3969,"org":3970,"tags":3971,"stars":3937,"repoUrl":3938,"updatedAt":3984},"claude-api","build apps with the Claude API","Reference for the Claude API \u002F Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration.\nTRIGGER — read BEFORE opening the target file; don't skip because it \"looks like a one-liner\" — whenever: the prompt names Claude\u002FAnthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing\u002Fmodel choice\u002Flimits\u002Fcaching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent\u002FMCP\u002Ftool-definition\u002Fmulti-agent\u002FRAG\u002FLLM-judge\u002Fcomputer-use; generate\u002Fsummarize\u002Fextract\u002Fclassify\u002Frewrite\u002Fconverse over NL; debugging refusals\u002Fcutoffs\u002Fstreaming\u002Ftool-calls\u002Ftokens).\nSKIP only when another provider is being worked on (overrides all triggers): OpenAI\u002FGPT\u002FGemini\u002FLlama\u002FMistral\u002FCohere\u002FOllama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3972,3975,3976,3979,3981],{"name":3973,"slug":3974,"type":16},"Agents","agents",{"name":9,"slug":8,"type":16},{"name":3977,"slug":3978,"type":16},"Anthropic SDK","anthropic-sdk",{"name":3980,"slug":3967,"type":16},"Claude API",{"name":3982,"slug":3983,"type":16},"LLM","llm","2026-07-28T05:36:08.213335",{"slug":3986,"name":3986,"fn":3987,"description":3988,"org":3989,"tags":3990,"stars":3937,"repoUrl":3938,"updatedAt":3996},"doc-coauthoring","co-author documentation and technical specs","Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[3991,3993],{"name":2782,"slug":3992,"type":16},"documentation",{"name":3994,"slug":3995,"type":16},"Technical Writing","technical-writing","2026-04-06T17:56:14.18897",{"slug":3998,"name":3998,"fn":3999,"description":4000,"org":4001,"tags":4002,"stars":3937,"repoUrl":3938,"updatedAt":4017},"docx","create and edit Word documents","Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx or .dotx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4003,4006,4008,4011,4014],{"name":4004,"slug":4005,"type":16},"Documents","documents",{"name":4007,"slug":3998,"type":16},"DOCX",{"name":4009,"slug":4010,"type":16},"Office","office",{"name":4012,"slug":4013,"type":16},"Templates","templates",{"name":4015,"slug":4016,"type":16},"Word","word","2026-07-18T05:16:23.136271",{"slug":4019,"name":4019,"fn":4020,"description":4021,"org":4022,"tags":4023,"stars":3937,"repoUrl":3938,"updatedAt":4037},"frontend-design","design production-grade frontend interfaces","Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4024,4025,4028,4031,4034],{"name":3929,"slug":3930,"type":16},{"name":4026,"slug":4027,"type":16},"Frontend","frontend",{"name":4029,"slug":4030,"type":16},"React","react",{"name":4032,"slug":4033,"type":16},"Tailwind CSS","tailwind-css",{"name":4035,"slug":4036,"type":16},"UI Components","ui-components","2026-04-06T17:56:16.723469",{"slug":4039,"name":4039,"fn":4040,"description":4041,"org":4042,"tags":4043,"stars":3937,"repoUrl":3938,"updatedAt":4051},"internal-comms","write internal company communications","A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4044,4047,4048],{"name":4045,"slug":4046,"type":16},"Communications","communications",{"name":4012,"slug":4013,"type":16},{"name":4049,"slug":4050,"type":16},"Writing","writing","2026-04-06T17:56:20.695522",{"slug":4053,"name":4053,"fn":4054,"description":4055,"org":4056,"tags":4057,"stars":3937,"repoUrl":3938,"updatedAt":4066},"mcp-builder","build MCP servers","Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node\u002FTypeScript (MCP SDK).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4058,4059,4062,4063],{"name":3973,"slug":3974,"type":16},{"name":4060,"slug":4061,"type":16},"API Development","api-development",{"name":3982,"slug":3983,"type":16},{"name":4064,"slug":4065,"type":16},"MCP","mcp","2026-04-06T17:56:10.357665",{"slug":3964,"name":3964,"fn":4068,"description":4069,"org":4070,"tags":4071,"stars":3937,"repoUrl":3938,"updatedAt":4074},"read edit and manipulate PDF files","Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text\u002Ftables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting\u002Fdecrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4072,4073],{"name":4004,"slug":4005,"type":16},{"name":3963,"slug":3964,"type":16},"2026-04-06T17:56:02.483316",{"slug":4076,"name":4076,"fn":4077,"description":4078,"org":4079,"tags":4080,"stars":3937,"repoUrl":3938,"updatedAt":4087},"pptx","create and edit PowerPoint presentations","Use this skill any time a .pptx or .potx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx or .potx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates (.potx), layouts, speaker notes, or comments. Trigger whenever the user mentions \"deck,\" \"slides,\" \"presentation,\" or references a .pptx or .potx filename, regardless of what they plan to do with the content afterward. If a .pptx or .potx file needs to be opened, created, or touched, use this skill.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4081,4084],{"name":4082,"slug":4083,"type":16},"PowerPoint","powerpoint",{"name":4085,"slug":4086,"type":16},"Presentations","presentations","2026-07-18T05:16:24.1471",{"slug":4089,"name":4089,"fn":4090,"description":4091,"org":4092,"tags":4093,"stars":3937,"repoUrl":3938,"updatedAt":4103},"skill-creator","create and optimize agent skills","Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4094,4095,4096,4099,4102],{"name":3973,"slug":3974,"type":16},{"name":2782,"slug":3992,"type":16},{"name":4097,"slug":4098,"type":16},"Evals","evals",{"name":4100,"slug":4101,"type":16},"Performance","performance",{"name":3994,"slug":3995,"type":16},"2026-04-19T06:45:40.804",490]