dcf-model skillA
dcf-model is agent-read markdown (skill) from ginlix-ai/langalpha: Build a DCF valuation in Excel: FCF projections, WACC, terminal value, scenarios, sensitivity grids, reverse DCF. Triggers on build a DCF, what is it worth, intrinsic value, fair value, price target from cash flows..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# DCF Model Builder Builds an institutional-quality DCF as a live Excel workbook: four sheets, three scenarios, three sensitivity grids, and a valuation a portfolio manager can argue with. A model that computes correctly and says nothing about the stock is half the job, so the construction rules and the judgement rules below are one document. Evidence labels, source tiers, staleness, the readiness posture and the intake limits: `.agents/skills/research-conventions/SKILL.md`, read before the first figure enters the workbook. - `recalc.py` reports errors, the case selector does not move the model, or the valuation looks wrong: read `.agents/skills/dcf-model/TROUBLESHOOTING.md`. - The revenue build needs the drivers of a particular sector, or the company is a bank, an insurer, a miner or a REIT: read `.agents/skills/dcf-model/references/sector-drivers.md`. ## Tools - **fundamentals MCP**: `get_financial_statements`, `get_financial_ratios`, `get_growth_metrics`, `get_historical_valuation`; diluted shares come from here - **macro MCP**: `get_treasury_rates`, `get_market_risk_premium` …
Read the whole file at its exact version.
How to install
mdr add ginlix-ai/langalpha/dcf-model@git:20260921.26f807bmdr add ginlix-ai/langalpha/dcf-model@sha256:1edb2e1ecdeff8f7Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_hhs6b26m7mpajqxt)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260921.26f807b latest | 2026-09-21 | 26f807b | 30,620 B | A | view · diff |
| git:20260915.99ad826 | 2026-09-15 | 99ad826 | 30,640 B | A | view · diff |
| git:20260826.8da358a | 2026-08-26 | 8da358a | 42,353 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (30620 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
ginlix-ai/langalpha · 1,774 stars · license Apache-2.0 · pushed 2026-09-24 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_hhs6b26m7mpajqxt GET https://markdownregistry.com/api/v1/resolve?ref=ginlix-ai/langalpha/dcf-model GET https://markdownregistry.com/api/v1/blob/1edb2e1ecdeff8f7b86129d6978926a003ad25a523dd15082c577f8042a2592e
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