dcf-modeler
Builds DCF models with terminal value, WACC calculation, sensitivity tables
Best use case
dcf-modeler is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Builds DCF models with terminal value, WACC calculation, sensitivity tables
Teams using dcf-modeler should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/dcf-modeler/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How dcf-modeler Compares
| Feature / Agent | dcf-modeler | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Builds DCF models with terminal value, WACC calculation, sensitivity tables
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 ``` Input: Company profile, capital structure Process: Calculate appropriate discount rate Output: WACC/discount rate, methodology notes ``` ### Estimate Terminal Value ``` Input: Terminal year financials, exit assumptions Process: Calculate terminal value Output: Terminal value, percentage of total value ``` ### Run Sensitivity Analysis ``` Input: Base case model, sensitivity parameters Process: Calculate sensitivities across ranges Output: Sensitivity tables, tornado charts ``` ## DCF Components | Component | VC Considerations | |-----------|-------------------| | Projection Period | 5-10 years to steady state | | Discount Rate | 20-40%+ for early stage | | Terminal Value | Often 60-80%+ of total value | | Cash Flows | May be negative for years | | Exit Multiple | Primary terminal method | ## Integration Points - **DCF Analysis Process**: Core modeling skill - **Financial Model Validator**: Validate model inputs - **Multiple Calculator**: Terminal value multiples - **Sensitivity Analyst (Agent)**: Support analysis ## Discount Rate Considerations | Stage | Typical Discount Rate | |-------|----------------------| | Seed | 40-60% | | Series A | 35-50% | | Series B | 30-40% | | Growth | 20-30% | | Late Stage | 15-25% | ## Best Practices 1. DCF is supplementary for early-stage VC 2. Use realistic projections, not hockey sticks 3. Heavily weight terminal value sensitivities 4. Consider probability-weighted scenarios 5. Triangulate with VC method and comparables
Related Skills
threat-modeler
Generate threat models using STRIDE, PASTA, or VAST methodologies
systems-dynamics-modeler
Skill for building and simulating systems dynamics models
noise-modeler
Quantum noise modeling skill for simulation and hardware characterization
pymc-bayesian-modeler
PyMC probabilistic programming skill for hierarchical Bayesian models in physics data analysis
comsol-multiphysics-modeler
COMSOL finite element skill for multiphysics simulations including electromagnetics, heat transfer, and fluid dynamics
environmental-fate-modeler
Environmental nanosafety skill for modeling nanomaterial environmental fate and transport
linear-program-modeler
Mathematical programming skill for formulating and solving linear programming models for resource allocation, production planning, and capacity optimization.
water-distribution-modeler
Water distribution system modeling skill for pipe networks, pump analysis, and fire flow
kinetic-modeler
Reaction kinetics modeling skill for parameter estimation, mechanism validation, and rate equation development
consequence-modeler
Consequence analysis skill for dispersion modeling, fire/explosion analysis, and effect zone determination
opensim-modeler
OpenSim musculoskeletal modeling skill for biomechanical simulation and analysis
scenario-modeler
Monte Carlo simulations for exit scenarios, return distributions