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unit-economics
Bottoms-up unit economics decomposition for any public company
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Bottoms-up unit economics decomposition for any public company
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
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| name | unit-economics |
| description | Bottoms-up unit economics decomposition for any public company |
| argument-hint | TICKER |
Perform a bottoms-up unit economics decomposition for the company specified by the user: $ARGUMENTS
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:
Look up the company by ticker using discover_companies. Capture:
company_idlatest_calendar_quarter — anchor for all period calculations below (see ../data-access.md Section 1.5)latest_fiscal_quarter../data-access.md Section 4.5Cast a wide net to discover ALL available series for this company. Search with multiple keyword sets to maximize coverage:
Collect all unique series IDs. Read every series name and description returned. This is how you learn what kind of business this is and what unit-level KPIs Daloopa tracks for it.
Based on series availability, classify the business into one of these archetypes (or a hybrid). This classification drives the entire report structure:
| If you find series like... | Archetype | Unit = |
|---|---|---|
| ARR, MRR, net dollar retention, customers, ACV, churn, CAC, LTV | SaaS / Subscription | Customer or subscription |
| Store count, same-store sales, AUV, restaurant-level margin, new openings | Unit-based retail / Restaurant | Store or unit |
| GMV, take rate, orders, AOV, active buyers/sellers | Marketplace / E-commerce | Order or transaction |
| Subscribers, ARPU, churn, content spend per sub | Consumer subscription (media/streaming) | Subscriber |
| Premiums written, loss ratio, combined ratio, policies in force | Insurance | Policy |
| NIM, loans, deposits, provision for credit losses, NCOs | Banking / Lending | Loan or account |
| ASP, units shipped, cost per unit, gross margin per unit | Hardware / Manufacturing | Unit shipped |
| AUM, management fee rate, performance fees, fund flows | Asset Management | Dollar of AUM |
| Revenue per available room (RevPAR), occupancy, ADR | Hospitality / Lodging | Room night |
| RPM, RASM, CASM, load factor, ASMs | Airlines / Transportation | Available seat mile |
| Revenue per user, DAU, MAU, ARPU, engagement | Digital platform / Advertising | User |
| Beds, admissions, revenue per admission, case mix | Healthcare facilities | Admission or bed |
| Acreage, production per acre, realized price per unit | Commodity / E&P | Unit of production |
If the business is a hybrid or doesn't fit neatly, construct a custom framework from the available series. The archetype is a starting guide, not a constraint.
Edge cases:
Calculate 10 quarters backward from latest_calendar_quarter. Pull all archetype-relevant series identified in Step 2 for those periods, plus standard financials:
Derived metrics (calculate from pulled data, label each as "(calc.)" and show formulas):
Search SEC filings for context on the unit economics. Use archetype-specific search terms:
Extract management commentary on pricing, retention, expansion, new unit openings, margin levers, etc. with document citations.
Section 1: Business Model & Unit Definition (brief)
Section 2: Revenue Decomposition
Section 3: Unit-Level Profitability The core of the report. Show margin/profitability at the unit level over time:
Section 4: Cohort / Vintage Analysis (if data supports it)
Section 5: Scalability & Operating Leverage
Section 6: Key Drivers & What to Watch This is the most analytically valuable section. Based on the data, identify:
Section 7: Summary Assessment
Analytical standards:
Use infra/chart_generator.py for charts. Include at minimum:
All charts must be embedded in the HTML as base64 data URIs (e.g., <img src="data:image/png;base64,...">) so the report is fully self-contained with no external file dependencies. After generating each chart PNG, read the file and convert to base64 for embedding. Do not use relative <img src="filename.png"> paths.
If chart_generator.py is unavailable, embed simple inline SVG charts directly in the HTML.
Save to reports/{TICKER}_unit_economics.html using the HTML report template from ../design-system.md. Write the full analysis as styled HTML with the design system CSS inlined. This is the final deliverable — no intermediate markdown step needed.
Structure the report with these sections:
<h1>{Company Name} ({TICKER}) — Unit Economics Analysis</h1>
<p>Generated: {date}</p>
<h2>Summary</h2>
{2-3 sentences: What is the "unit"? Are unit economics improving or deteriorating? Key takeaway.}
<h2>Business Model & Unit Definition</h2>
{Section 1 content}
<h2>Revenue Decomposition</h2>
<table>
| Component | Q(-9) | Q(-8) | ... | Q(latest) |
{Units, revenue per unit, revenue — with Daloopa citations and YoY growth sub-rows}
</table>
{Commentary on volume vs. price drivers}
<h2>Unit-Level Profitability</h2>
<table>
| Metric | Q(-9) | Q(-8) | ... | Q(latest) |
{Archetype-specific unit margins — with Daloopa citations}
</table>
{Commentary on unit economics trajectory}
<h2>Cohort / Vintage Analysis</h2>
{Section 4 content, or note if insufficient data}
<h2>Scalability & Operating Leverage</h2>
<table>
| Metric | Q(-9) | Q(-8) | ... | Q(latest) |
{Revenue growth vs cost growth, incremental margins}
</table>
{Operating leverage assessment}
<h2>Key Drivers & What to Watch</h2>
{Ranked drivers with sensitivity analysis and bull/bear scenarios}
<h2>Summary Assessment</h2>
{3-4 sentence verdict}
All financial figures must use Daloopa citation format: <a href="https://daloopa.com/src/{fundamental_id}">$X.XX million</a>
Tell the user where the HTML report was saved.
Highlight the 2-3 most important findings about the company's unit economics and what they signal for the investment case.