dcf-model
Real DCF (Discounted Cash Flow) model creation for equity valuation. Retrieves financial data from SEC filings and analyst reports, builds comprehensive cash flow projections with proper WACC calculations, performs sensitivity analysis, and outputs professional Excel models with executive summaries. Use when users need to value a company using DCF methodology, request intrinsic value analysis, or ask for detailed financial modeling with growth projections and terminal value calculations.
Best for equity valuationWorks with GitHubLow risk
⌘source
- author
@anthropics- language
- Python
★11kstars
1.5kforks
May 6, 2026
✦overview.md
Key Features
- ·Institutional-quality DCF models
- ·SEC filings and analyst report data retrieval
- ·Proper WACC calculations
- ·Sensitivity analysis included
- ·Professional Excel output with executive summaries
Use Cases
- →User requests intrinsic value analysis of a public company
- →Investment analyst needs detailed financial modeling with growth projections
- →Portfolio manager requires terminal value calculation for a stock
- →Finance team builds a DCF model for M&A target valuation
Best for
- ✓equity valuation
- ✓investment analysts
- ✓financial modeling teams
Not ideal for
- !non-public company valuation
- !real-time stock pricing
- !options pricing
FAQs
name
dcf-model
description
Real DCF (Discounted Cash Flow) model creation for equity valuation. Retrieves financial data from SEC filings and analyst reports, builds comprehensive cash flow projections with proper WACC calculations, performs sensitivity analysis, and outputs professional Excel models with executive summaries. Use when users need to value a company using DCF methodology, request intrinsic value analysis, or ask for detailed financial modeling with growth projections and terminal value calculations.
DCF Model Builder
Overview
This skill creates institutional-quality DCF models for equity valuation following investment banking standards. Each analysis produces a detailed Excel model (with sensitivity analysis included at the bottom of the DCF sheet).
Tools
- Default to using all of the information provided by the user and MCP servers available for data sourcing.
Critical Constraints - Read These First
These constraints apply throughout all DCF model building. Review before starting:
Environment: Office JS vs Python/openpyxl:
- If running inside Excel (Office Add-in / Office JS environment): Use Office JS directly — do NOT use Python/openpyxl. Write formulas via
range.formulas = [["=D19*(1+$B$8)"]]. No separate recalc step needed; Excel calculates natively. Userange.format.*for styling. The same formulas-over-hardcodes rule applies: set.formulas, never.valuesfor derived cells. - If generating a standalone .xlsx file (no live Excel session): Use Python/openpyxl as described below, then run
recalc.pybefore delivery.
$install
1-click copynpx skills add anthropics/financial-services --skill dcf-modelSafety assessment
★
Clarity score
How clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
4/ 5
very goodClear and well structured, with only minor parts that might need a second read.
◎
Actionability score
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
4/ 5
highMostly actionable with clear steps; only a few small gaps remain.