Agent skill · business finance · nousresearch
dcf-model
Build discounted cash flow valuation workbooks in Excel.
Why this skill is useful
Provides detailed procedures for building DCF models in Excel, including specific formula requirements and sensitivity analysis structures that the AI wouldn't reliably generate on its own.
What it needs
About 12k tokens when loaded. Last updated 2026-08-07. 226,679 stars on the source repository.
What this skill does
Environment This skill assumes headless openpyxl — you are producing an .xlsx file on disk. Follow the excel-author skill's conventions for cell coloring, formulas, named ranges, and sensitivity tables. Recalculate before delivery: python /path/to/excel-author/scripts/recalc.py ./out/model.xlsx. 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: Formulas Over Hardcodes (NON-NEGOTIABLE): Every projection, margin, discount factor, PV, and sensitivity cell MUST be a live Excel formula — never a value computed in Python and written as a number When using openpyxl: ws["D20"] = "=D19(1+$B$8)" is correct; ws["D20"] = calculatedrevenue is WRONG The only hardcoded numbers permitted are: (1) raw historical inputs, (2) assumption drivers (growth rates, WACC inputs, terminal g), (3) current market data (share price, debt balance) If you catch yourself computing something in Python and writing the result — STOP. The model must flex when the user changes an assumption. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nousresearch/dcf-model