Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add yennanliu/InvestSkill --skill dcf-valuationgit clone --depth 1 https://github.com/yennanliu/InvestSkillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yennanliu/investskill/dcf-valuation)<a href="https://agentmods.dev/skills/yennanliu/investskill/dcf-valuation"><img src="https://agentmods.dev/badge/skills/yennanliu/investskill/dcf-valuation.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00013 | $0.01125 |
| Opus 5 | $0.00006 | $0.00562 |
| Sonnet 5 | $0.00003 | $0.00225 |
| Haiku 4.5 | $0.00001 | $0.00112 |
Grade A, and why
dcf-valuation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DCF Valuation
This skill has been merged into
stock-valuation. Use/us-stock-analysis:stock-valuationfor comprehensive valuation including full DCF modeling, WACC decomposition, 3-scenario sensitivity analysis, and comparable company analysis.
Quick DCF Reference
WACC Formula and Components
WACC = Ke × (E/V) + Kd × (D/V)
Where:
Ke = Cost of Equity = Rf + β × (Rm − Rf) + Size Premium
Kd = After-Tax Cost of Debt = (Interest Expense / Total Debt) × (1 − Tax Rate)
E/V = Equity Weight = Equity Market Cap / (Equity Market Cap + Total Debt)
D/V = Debt Weight = Total Debt / (Equity Market Cap + Total Debt)
Typical WACC Ranges by Risk Profile:
Risk Profile WACC Range Examples
─────────────────────────────────────────────────────
Low risk (utility) 6–8% Regulated utilities, large cap staples
Medium risk 8–11% Large cap tech, established growth
High risk 11–15% Small cap, emerging market, cyclical
Very high risk 15–20%+ Early-stage, distressed, pre-revenue
Three-Scenario Names and Default Probabilities
Scenario Probability Narrative
Bull 20% Market share gains, margin expansion, favorable macro
Base 60% Historical trend continuation, guidance-aligned
Bear 20% Competitive pressure, margin compression, macro headwinds
Probability-Weighted IV = (20% × Bull IV) + (60% × Base IV) + (20% × Bear IV)
5×5 Sensitivity Table Template
Sensitivity Table — Intrinsic Value per Share ($)
Terminal Growth Rate
WACC 1.0% 1.5% 2.0% 2.5% 3.0%
6.0% $xxx $xxx $xxx $xxx $xxx
7.0% $xxx $xxx $xxx $xxx $xxx
8.0% $xxx $xxx $xxx $xxx $xxx ← Base Case
9.0% $xxx $xxx $xxx $xxx $xxx
10.0% $xxx $xxx $xxx $xxx $xxx
Terminal Value Formula
Gordon Growth Model: TV = FCF₁₀ × (1 + g) / (WACC − g)
Exit Multiple Method: TV = FCFₙ × (EV / FCF exit multiple)
Rule: Never set g > WACC. Flag if TV > 80% of total Enterprise Value.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 109 lines · 13 tokens per session scan A 071a726b22fc
dcf-valuation is a skill published in the GitHub repository yennanliu/InvestSkill (200 stars, last pushed yesterday), licensed MIT. It adds 13 tokens to every session and 1,125 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
dcf-model
DCF valuation: free cash flow projections, WACC, terminal value, sensitivity analysis.
comps-analysis
Comparable company analysis: operating metrics, valuation multiples, peer benchmarking.
initiating-coverage
Full equity research initiation: company research, financial model, valuation, charts, 30-50 page report.
ui-design
Design-quality reference for financial-research visual output: typography, color, composition, and avoiding generic AI aesthetics.
onboarding
First-time user onboarding to set up investment profile, watchlists, portfolio, and preferences.
user-profile
Manage user profile including watchlists, portfolio, and preferences.