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 seb1n/awesome-ai-agent-skills --skill financial-modelinggit clone --depth 1 https://github.com/seb1n/awesome-ai-agent-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/seb1n/awesome-ai-agent-skills/financial-modeling)<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/financial-modeling"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-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/seb1n/awesome-ai-agent-skills/financial-modeling"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/financial-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00041 | $0.01826 |
| Opus 5 | $0.00020 | $0.00913 |
| Sonnet 5 | $0.00008 | $0.00365 |
| Haiku 4.5 | $0.00004 | $0.00183 |
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 9d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Financial Modeling
Build structured financial projections including income statements, discounted cash flow (DCF) models, and valuation analyses. This skill takes a set of business assumptions and transforms them into multi-period financial forecasts with key metrics like NPV, IRR, EBITDA margins, and revenue growth rates. Suitable for startup fundraising, acquisition analysis, budgeting, and strategic planning.
Workflow
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Define Core Assumptions Gather all foundational inputs: revenue growth rates, pricing tiers, customer acquisition rates, churn, cost structures, tax rates, discount rates, and terminal growth rates. Validate that assumptions are internally consistent — for example, headcount growth should align with projected revenue capacity. Document each assumption with its source or rationale.
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Build the Revenue Model Construct a bottoms-up or top-down revenue forecast depending on available data. For subscription businesses, model MRR by cohort with expansion and churn. For transactional businesses, model volume × average transaction value. Break revenue into segments if the business has multiple product lines or geographies.
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Project Operating Expenses Forecast COGS, gross margin, and operating expenses by category: personnel, marketing, R&D, G&A, and infrastructure. Use a mix of fixed and variable cost assumptions. Tie headcount plans to compensation benchmarks. Model economies of scale where applicable — hosting costs per user should decline as volume grows.
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Calculate Free Cash Flows Derive EBITDA from the projected P&L, then adjust for capital expenditures, changes in working capital, and taxes to arrive at unlevered free cash flow (UFCF) for each period. Clearly separate operating cash flow from investing and financing activities.
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Compute Valuation Metrics Discount projected cash flows using WACC to compute enterprise value via DCF. Calculate terminal value using either a perpetuity growth model or an exit multiple approach. Derive NPV, IRR, and payback period. Run sensitivity tables across discount rate and growth rate ranges.
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.
- 9d ago First seen · 106 lines · 41 tokens per session scan A b5eb1bc27c6b
financial-modeling is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 1,826 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 2026-09-03.
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