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 LeadMagic/gtm-skills --skill financial-modelinggit clone --depth 1 https://github.com/LeadMagic/gtm-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/leadmagic/gtm-skills/financial-modeling)<a href="https://agentmods.dev/skills/leadmagic/gtm-skills/financial-modeling"><img src="https://agentmods.dev/badge/skills/leadmagic/gtm-skills/financial-modeling.svg" alt="Measured on agentmods" 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 | $0.00090 | $0.05683 |
| Opus 5 | $0.00045 | $0.02841 |
| Sonnet 5 | $0.00018 | $0.01137 |
| Haiku 4.5 | $0.00009 | $0.00568 |
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 3d 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 — 484 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SaaS Financial Modeling
Overview
Most founder financial models are fiction — aggressive growth curves with no operational logic underneath. The mistake: building a top-down model ("we'll capture 1% of a $100B market") instead of a bottom-up operating model ("we'll hire 3 AEs at $120K OTE, each producing $800K quota in month 6"). This skill covers building a real operating model that investors trust, boards respect, and YOU can use to make decisions. Now includes DCF valuation, consumption-based pricing models, cohort analysis, and full ARR bridge/build methodology.
When to Use
Trigger phrases: "financial model", "SaaS P&L", "runway calculation", "DCF valuation", "consumption pricing model", "cohort analysis", "ARR bridge", "headcount plan", "revenue forecast", "409A valuation", "unit economics model", "annual GTM budget", "operating budget", "variance review", "QuickBooks vs NetSuite"
Authoritative Foundations
David Skok — SaaS Unit Economics
LTV = (ARPA × Gross Margin %) ÷ Monthly Churn Rate. LTV/CAC > 3x is investable. CAC Payback < 12 months is good.
Aswath Damodaran — DCF Valuation
"The value of any asset is the present value of its expected future cash flows." For startups: high growth + high risk = high WACC (20-30% for early stage).
Ben Murray — The SaaS CFO
Three P&L layers: Revenue (new + expansion - churn), COGS (20-30%), OpEx
(S&M + R&D + G&A). Model per-head where possible. PE exits require EBITDA
bridge — see references/unit-economics-exit-bridge.md.
Meritech Capital — Public SaaS Benchmarks
For IPO-track scenarios, compare implied ARR growth, FCF margin, and Meritech Rule of 40 to public medians. references/meritech-saas-benchmarks.md. Private stage gates remain in references/benchmark-reconciliation.md.
Force Management — Pod Economics & Headcount Planning
Bottom-up headcount from pod economics: group SDR/AE/SE/CSM into pods, run
pod cost % of ARR (target ≤35% at 80% ramp), link quota attainment distribution
to hiring triggers. See references/force-management-playbook.md (repo root)
and references/unit-economics-exit-bridge.md.
What ships with it
11 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.
- references/benchmark-reconciliation.md 24 KB
- references/bookings-billings-revenue-matrix.md 5.4 KB
- references/force-management-playbook.md 6.6 KB
- references/framework-notes.md 1.2 KB
- references/gtm-budget-playbook.md 7.0 KB
- references/meritech-saas-benchmarks.md 7.5 KB
- references/saas-mrr-accounting-nuances.md 9.6 KB
- references/saas-tax-founder-awareness.md 2.2 KB
- references/unit-economics-exit-bridge.md 3.4 KB
- scripts/check-output.py 855 B runs code
- templates/output-template.md 2.5 KB
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.
- 3d ago First seen · 484 lines · 90 tokens per session scan A ba0b4d188b9e
financial-modeling is a skill published in the GitHub repository LeadMagic/gtm-skills (48 stars, last pushed today), licensed MIT. It adds 90 tokens to every session and 5,683 once invoked, about $0.0005 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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