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 Ruinius/financial-analyst-skills --skill financial_modelinggit clone --depth 1 https://github.com/Ruinius/financial-analyst-skillsWrote 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/ruinius/financial-analyst-skills/financial_modeling)<a href="https://agentmods.dev/skills/ruinius/financial-analyst-skills/financial_modeling"><img src="https://agentmods.dev/badge/skills/ruinius/financial-analyst-skills/financial_modeling/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ruinius/financial-analyst-skills/financial_modeling"><img src="https://agentmods.dev/badge/skills/ruinius/financial-analyst-skills/financial_modeling.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00037 | $0.00644 |
| Opus 5 | $0.00018 | $0.00322 |
| Sonnet 5 | $0.00007 | $0.00129 |
| Haiku 4.5 | $0.00004 | $0.00064 |
Grade A, and why
Financial Modeling 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 11d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Financial Modeling (Phase 6)
All modeling logic is consolidated into a single script that executes the complete sequence: WACC → Assumptions → DCF → Intrinsic Value.
- Execute the script:
python skills/financial_modeling/scripts/calculate.py {TICKER} {TICKER_metadata_path} - Verify it threw no errors.
What the Script Does
| Step | Action | Details |
|---|---|---|
| 1 | Fetch Market Data | Calls tools/market_data.py profile {TICKER} for share price, beta, market cap |
| 2 | Read Historical Data | Parses Financial History table from metadata for L4Q averages |
| 3 | Read Qualitative Data | Parses Economic Moat, Margin Outlook, Growth Outlook from metadata |
| 4 | Calculate WACC | CAPM with Blume-adjusted beta, capital structure weights |
| 5 | Generate Assumptions | Three-stage DCF assumptions blending historical trends + qualitative outlook |
| 6 | Run DCF Projections | 10-year projections with interpolated growth/margin, terminal value via Gordon Growth |
| 7 | Compute Intrinsic Value | Equity bridge: EV + Cash - Debt → Per Share |
| 7b | FX & ADR Conversion | If reporting currency != USD, convert IVPS to USD. Apply ADR ratio to share count if applicable |
| 8 | Update Metadata | Replaces WACC, Assumptions, DCF Model, and Intrinsic Value sections in markdown |
Prerequisites
output_data/TICKER/TICKER_metadata.mdmust exist with Financial History and Qualitative Assessment sections- Internet access required for Yahoo Finance market data lookup
- Python 3.10+ with
yfinanceinstalled
Key Parameters
| Parameter | Source | Default |
|---|---|---|
| Risk-Free Rate | Hardcoded (TODO: fetch 10Y Treasury) | 4.20% |
| Equity Risk Premium | Hardcoded | 5.00% |
| Terminal Growth | Moat rating: Wide=4%, Narrow=3%, None=2.5% | 3.00% |
| MCT | Derived from IC, default if negative IC | 100.0x |
| Tax Rate (statutory) | Hardcoded for WACC | 25% |
| Tax Rate (NOPAT) | L4Q average adjusted tax rate | Varies |
| WACC Bounds | Floor 6%, Cap 15% | — |
| FX Rate | market_data.py if Currency != USD | 1.0 |
| ADR Ratio | Parsed from metadata header | 1.0 |
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 50 lines · 37 tokens per session scan A 932f012da567
Financial Modeling is a skill published in the GitHub repository Ruinius/financial-analyst-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 37 tokens to every session and 644 once invoked, about $0.0002 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 2026-08-31.
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