dcf-modeler
Builds DCF models with terminal value, WACC calculation, sensitivity tables
npx skills add a5c-ai/babysitter --skill dcf-modeler --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 Modeler ## Overview The DCF Modeler skill builds Discounted Cash Flow valuation models for venture capital analysis. While DCF is less common for early-stage VC, it supports late-stage growth investments, exit analysis, and LP return modeling where cash flow projections are meaningful. ## Capabilities ### Cash Flow Projection - Project operating cash flows - Model capital expenditure requirements - Estimate working capital changes - Handle loss-making growth phase transitions ### Discount Rate Calculation - Calculate WACC for appropriate structures - Apply venture-appropriate discount rates - Adjust for stage and risk profile - Model cost of equity with VC premiums ### Terminal Value Estimation - Calculate terminal value via exit multiple - Apply perpetuity growth method - Hybrid terminal value approaches - Terminal value sanity checks ### Sensitivity Analysis - Build sensitivity tables - Model key assumption impacts - Calculate value driver sensitivities - Create scenario matrices ## Usage ### Build DCF Model ``` Input: Financial projections, assumptions Process: Build cash flow model, calculate value Output: DCF valuation, model outputs ``` ### Calculate Discount Rate ``` I
- Overview
- Capabilities
- Cash Flow Projection
- Discount Rate Calculation
- Terminal Value Estimation
- Sensitivity Analysis
- Usage
- Build DCF Model
- Calculate Discount Rate
- Estimate Terminal Value
- Run Sensitivity Analysis
- DCF Components
- Integration Points
- Discount Rate Considerations
What does the dcf-modeler skill do?
Builds DCF models with terminal value, WACC calculation, sensitivity tables
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill dcf-modeler --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 a5c-ai/babysitter, a repository with 1,642 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.