# Valuation101

> A conversational FCFF intrinsic valuation plugin for Claude, built on Aswath Damodaran's fcffsimpleginzu spreadsheet methodology. You talk to it; it does the math.

## Documentation

- [Getting Started](https://valuation101.mintlify.app/docs/getting-started): Install the plugin and run your first valuation in under 5 minutes
- [How a Valuation is Performed](https://valuation101.mintlify.app/docs/how-it-works): The 8-phase FCFF pipeline from company name to intrinsic value per share
- [Data Handling](https://valuation101.mintlify.app/docs/data-pipeline): How SEC EDGAR XBRL data flows from raw API response to structured valuation inputs
- [Methodology](https://valuation101.mintlify.app/docs/methodology): Damodaran's FCFF framework — the academic foundation behind every calculation
- [Interpreting Results](https://valuation101.mintlify.app/docs/interpreting-results): How to read, evaluate, and act on a valuation output

## Modes

- [Expert Mode](https://valuation101.mintlify.app/docs/expert-mode): Full control over every DCF assumption
- [Novice Mode](https://valuation101.mintlify.app/docs/novice-mode): Guided walkthrough with explanations at every step
- [Feeling Lucky](https://valuation101.mintlify.app/docs/feeling-lucky): One-click valuation with sensible defaults in ~60 seconds

## Skills Reference

- [Skills Overview](https://valuation101.mintlify.app/skills/overview): All 19 skills with dependency graph, inputs, outputs, and execution order
- [company-identifier](https://valuation101.mintlify.app/skills/company-identifier): Resolve company name/ticker to confirmed identity (CIK, exchange, sector)
- [identify-required-statements](https://valuation101.mintlify.app/skills/identify-required-statements): Determine which SEC 10-K/10-Q filings are needed for the valuation
- [pull-raw-data](https://valuation101.mintlify.app/skills/pull-raw-data): Download the company's full XBRL fact set from SEC EDGAR
- [parse-raw-data-to-filings](https://valuation101.mintlify.app/skills/parse-raw-data-to-filings): Transform raw XBRL JSON into structured per-filing extracts
- [last-twelve-months](https://valuation101.mintlify.app/skills/last-twelve-months): Compute trailing-12-month financials for Damodaran's Input sheet
- [last-10-k](https://valuation101.mintlify.app/skills/last-10-k): Extract most recent annual 10-K financials
- [cost-of-capital](https://valuation101.mintlify.app/skills/cost-of-capital): Compute WACC using 3 methods (Detailed CAPM, Industry Average, Distribution)
- [earnings-guidance](https://valuation101.mintlify.app/skills/earnings-guidance): Extract forward-looking management guidance from earnings call transcripts
- [growth-and-profitability](https://valuation101.mintlify.app/skills/growth-and-profitability): Set the 4 forecast variables (revenue growth, margins, S/C, CoC) with convergence curves
- [fcff-model](https://valuation101.mintlify.app/skills/fcff-model): Run the core DCF engine — 10-year projection, terminal value, equity bridge
- [r-and-d-converter](https://valuation101.mintlify.app/skills/r-and-d-converter): Capitalize R&D expenses into a research asset
- [lease-converter](https://valuation101.mintlify.app/skills/lease-converter): Convert operating leases to debt equivalents
- [employee-options](https://valuation101.mintlify.app/skills/employee-options): Value outstanding employee stock options via Black-Scholes
- [failure-rate](https://valuation101.mintlify.app/skills/failure-rate): Estimate probability of corporate failure
- [fcff (orchestrator)](https://valuation101.mintlify.app/skills/fcff): Run the complete end-to-end FCFF valuation pipeline
- [diagnostics](https://valuation101.mintlify.app/skills/diagnostics): Damodaran's 6-step sanity check on the valuation output
- [valuation-report](https://valuation101.mintlify.app/skills/valuation-report): Generate a formatted .docx valuation report
- [case-study-generator](https://valuation101.mintlify.app/skills/case-study-generator): Generate a Mintlify MDX case study from a completed valuation run

## Python Library

- [Library Overview](https://valuation101.mintlify.app/lib/overview): Architecture of the deterministic math engine (12 modules)
- [dcf_engine.py](https://valuation101.mintlify.app/lib/dcf-engine): FCFF projection, terminal value, discounting, equity bridge
- [cost_of_capital.py](https://valuation101.mintlify.app/lib/cost-of-capital): WACC computation (3 methods), beta levering, synthetic ratings
- [curve_shapes.py](https://valuation101.mintlify.app/lib/curve-shapes): 6 convergence curve types for forecast variable transitions
- [adjustments (rd_converter.py & lease_converter.py)](https://valuation101.mintlify.app/lib/adjustments): R&D capitalization, lease conversion
- [option_value.py](https://valuation101.mintlify.app/lib/option-value): Dilution-adjusted Black-Scholes for employee options
- [failure_rate.py](https://valuation101.mintlify.app/lib/failure-rate): Default probability by bond rating or company age
- [lookup.py](https://valuation101.mintlify.app/lib/data-loader): Load Damodaran's reference datasets efficiently

## Case Studies

- [Case Study Guide](https://valuation101.mintlify.app/case-studies/case-study-guide): How to read a Valuation101 case study — manual overrides, company identification, filings, financials, WACC, forecasts
- [CoreWeave (CRWV)](https://valuation101.mintlify.app/case-studies/coreweave): Full Feeling Lucky FCFF valuation of a pre-profitability AI infrastructure company — $106.29/share vs. $75.00 market price. Covers every pipeline phase with real SEC EDGAR data, including edge cases: recent IPO, negative EBIT, extreme leverage, hyper-growth, earnings guidance integration, and missing XBRL fields.