comp-sheet

Build a multi-company industry comp sheet Excel model for the company specified by the user: $ARGUMENTS

This produces an interactive .xlsx workbook — the kind of comp sheet every analyst on a coverage team maintains. Multi-company, multi-tab, with deep operational KPIs alongside standard financials.

Before starting, read data-access.md for data access methods and design-system.md for formatting conventions. Follow the data access detection logic and design system throughout this skill.

Follow these steps:

1. Company & Peer Setup

Look up the target company by ticker using discover_companies. Capture company_id, latest_calendar_quarter (anchor for all period calculations — see data-access.md Section 1.5), and latest_fiscal_quarter. Note the firm name for report attribution (default: "Daloopa") — see data-access.md Section 4.5.

Then identify 6-10 comparable companies using the same logic as /comps:

• Direct competitors in the same market
• Business model peers (similar revenue model)
• Size peers (similar market cap range)
• Growth profile peers (similar growth rate)

Look up all peer company_ids via Daloopa. If a peer isn't available in Daloopa, include it with market data only and note the limitation.

List the full peer group with brief justification for each.

2. Deep Data Gathering

For each company (target + all peers), pull from Daloopa:

Calculate 8 quarters backward from latest_calendar_quarter. Pull financials:

• Revenue, Gross Profit, Operating Income, Net Income, Diluted EPS
• Operating Cash Flow, Capital Expenditures, D&A
• Free Cash Flow (compute as OCF - CapEx)
• R&D Expense, SG&A (where available)

Segment revenue breakdown (all available segments, 8 quarters)

Company-specific operational KPIs — use the 9-sector taxonomy to know what to search for:

• SaaS/Cloud: ARR, net revenue retention, RPO/cRPO, customers >$100K, cloud gross margin
• Consumer Tech: DAU/MAU, ARPU, engagement metrics, installed base, paid subscribers
• E-commerce/Marketplace: GMV, take rate, active buyers/sellers, order frequency
• Retail: same-store sales, store count, average ticket, transactions
• Telecom/Media: subscribers, churn, ARPU, content spend
• Hardware: units shipped, ASP, attach rate, installed base
• Financial Services: AUM, NIM, loan growth, credit quality metrics, fee income ratio
• Pharma/Biotech: pipeline stage, patient starts, scripts, market share
• Industrials/Energy: backlog, book-to-bill, utilization, production volumes, reserves

Market data for each company (see data-access.md Section 2):

• Price, market cap, enterprise value, shares outstanding, beta
• All trading multiples: P/E (trailing + forward), EV/EBITDA, P/S, P/B, EV/FCF, dividend yield

3. KPI Discovery & Mapping

After pulling data, build the KPI mapping:

• Which KPIs are available for which companies? Build a coverage matrix.
• Group KPIs into categories:
  • Segment Revenue: product/service line breakdowns
  • Growth KPIs: subscriber growth, unit growth, same-store sales growth
  • Unit Economics: ARPU, ASP, take rate, retention
  • Efficiency: R&D % of revenue, SBC % of revenue, CapEx % of revenue
  • Engagement: DAU/MAU, retention, churn
• Flag KPIs that are comparable across peers vs company-specific

4. Compute Derived Metrics

For each company, calculate:

Margins:

• Gross Margin, Operating Margin, Net Margin, FCF Margin (each quarter)

Growth rates:

• Revenue YoY, EPS YoY, segment revenue YoY (each quarter where year-ago data exists)

Capital metrics:

• Net Debt (Total Debt - Cash)
• Net Debt/EBITDA
• FCF Yield (trailing 4Q FCF / Market Cap)
• Shareholder Yield (Buybacks + Dividends) / Market Cap

Implied valuation:

• For each valuation methodology (P/E, EV/EBITDA, P/S, EV/FCF):
  • Peer median multiple × target metric = implied value
  • Convert to implied share price
• Compute median implied price across methodologies

5. Structure Data for Excel Export

Organize the data into 8 tabs (structure shown below). This will be rendered as a downloadable .xlsx using a React artifact with SheetJS:

Tab 1: Comp Summary — one-pager with all companies, multiples, implied valuation

• Company name, ticker, price, market cap, enterprise value
• Trading multiples (P/E, EV/EBITDA, P/S, P/B, EV/FCF, dividend yield)
• Implied valuation by methodology (P/E implied, EV/EBITDA implied, P/S implied, EV/FCF implied, median implied)
• Premium/discount to median

Tab 2: Revenue Drivers — unit economics decomposition per company (trailing 4Q)

• Segment revenue breakdown
• Key volume metrics (units, subscribers, stores, etc.)
• Key price metrics (ARPU, ASP, etc.)
• Revenue per unit, revenue per segment

Tab 3: Operating KPIs — cross-company KPI comparison matrix

• Rows = KPIs (grouped by category: Segment Revenue, Growth KPIs, Unit Economics, Efficiency, Engagement)
• Columns = companies
• Trailing 4Q averages or latest quarter values
• Sparse matrix (not all KPIs available for all companies)

Tab 4: Financial Summary — side-by-side income statements (trailing 4Q)

• Revenue, Gross Profit, Operating Income, Net Income, EPS
• R&D, SG&A, CapEx, D&A
• OCF, FCF
• All companies in columns, metrics in rows

Tab 5: Growth & Margins — trend analysis (up to 8Q)

• Revenue YoY growth, EPS YoY growth, segment growth
• Gross margin, operating margin, net margin, FCF margin
• Each metric with 8Q history per company

Tab 6: Valuation Detail — implied prices by methodology, premium/discount

• For each methodology (P/E, EV/EBITDA, P/S, EV/FCF):
  • Peer median multiple
  • Target metric (trailing 4Q or forward)
  • Implied equity value
  • Implied share price
• Median implied price across methodologies
• Current price vs implied (premium/discount %)

Tab 7: Balance Sheet & Capital — leverage and capital returns

• Total debt, cash, net debt
• Net debt/EBITDA
• Buybacks (trailing 4Q), dividends (trailing 4Q)
• FCF yield, shareholder yield

Tab 8: Raw Data — full quarterly appendix for each company

• All financials, margins, growth rates, KPIs by quarter (8Q)
• One section per company

6. Render Excel Artifact

Generate a React artifact that:

• Uses the SheetJS library (xlsx) to build a workbook with 8 tabs matching the structure above
• Applies basic styling (bold headers, number formatting, freeze panes)
• Downloads the .xlsx file to the user's browser with filename {TICKERS}_comp_sheet.xlsx

The artifact should include:

• Import statement for xlsx library (use CDN: https://cdn.sheetjs.com/xlsx-latest/package/dist/xlsx.full.min.js)
• Button to trigger download
• All 8 tabs pre-populated with the data from steps 1-4

7. Output

Tell the user that the .xlsx will download when they click the button in the artifact.

Highlight in your summary:

• Target positioning vs peers: Where does it rank on growth, margins, and valuation?
• Most differentiated KPIs: Which operational metrics set the target apart (positive or negative)?
• Implied valuation range: What does the peer group suggest the stock is worth?
• Key risk: What's the biggest vulnerability the comp sheet reveals (e.g., premium valuation with decelerating KPIs, margins below peers, etc.)?

All financial figures in the summary must use Daloopa citation format: $X.XX million