dcf-builder
Build defensible DCF models with cited sources, Excel export, and sensitivity analysis
npx skills add majiayu000/claude-skill-registry --skill dcf-builder --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# DCF Builder Skill ## Purpose Build discounted cash flow (DCF) models from SEC filings with full source attribution. Outputs Excel workbook with formulas and Markdown summary. ## Usage ```python # Build DCF for Omnicom Group dcf = build_dcf( ticker_or_cik="OMC", currency="USD", scenario="base", forecast_years=5 ) ``` ## Workflow ### 1. Fetch Historical Financials ```python def fetch_historical_financials(cik): """Fetch historical financials from SEC EDGAR""" # Get company facts (XBRL aggregated data) url = f"https://data.sec.gov/api/xbrl/companyfacts/CIK{cik.zfill(10)}.json" response = requests.get(url, headers=EDGAR_HEADERS, timeout=30) response.raise_for_status() facts = response.json() # Extract key metrics financials = { 'revenue': extract_fact(facts, 'Revenues'), 'cogs': extract_fact(facts, 'CostOfRevenue'), 'operating_expenses': extract_fact(facts, 'OperatingExpenses'), 'depreciation': extract_fact(facts, 'DepreciationAndAmortization'), 'capex': extract_fact(facts, 'PaymentsToAcquirePropertyPlantAndEquipment'), 'tax_rate': extract_fact(facts, 'EffectiveIncomeTaxRateContinuingOperations'), 'cash': extract_fact(facts, 'Cash'), 'debt': extract_fact(facts, 'LongTermDebt'), 'shar
- Purpose
- Usage
- Workflow
- 1. Fetch Historical Financials
- 2. Compute WACC
- 3. Forecast Free Cash Flow
- 4. Calculate Terminal Value and Valuation
- 5. Sensitivity Analysis
- 6. Export to Excel
- 7. Generate Markdown Summary
- Evaluation
- References
What does the dcf-builder skill do?
Build defensible DCF models with cited sources, Excel export, and sensitivity analysis
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill dcf-builder --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.