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 saas-metrics-calculatorgit 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/saas-metrics-calculator)<a href="https://agentmods.dev/skills/leadmagic/gtm-skills/saas-metrics-calculator"><img src="https://agentmods.dev/badge/skills/leadmagic/gtm-skills/saas-metrics-calculator/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/leadmagic/gtm-skills/saas-metrics-calculator"><img src="https://agentmods.dev/badge/skills/leadmagic/gtm-skills/saas-metrics-calculator.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 | $0.00071 | $0.03888 |
| Opus 5 | $0.00036 | $0.01944 |
| Sonnet 5 | $0.00014 | $0.00778 |
| Haiku 4.5 | $0.00007 | $0.00389 |
Grade A, and why
saas-metrics-calculator 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 — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SaaS Metrics Calculator
Overview
SaaS metrics answer whether your business model works. The mistake: cherry-picking
the metric that makes you look good (usually ARR growth) and ignoring the metric
that tells the truth (usually churn or CAC payback). This skill calculates all
key metrics from minimal inputs, applies stage-aware benchmarks, diagnoses which
lever to pull first, and produces board-ready, investor-ready output. Every
formula is documented. Every benchmark is sourced. For exit weight by buyer
type, load references/metric-definitions-exit-weight.md.
Authoritative Foundations
- David Skok (forEntrepreneurs). LTV:CAC, CAC payback, fully loaded S&M — canonical formulas for diligence.
- Jason Lemkin / David Sacks. Burn multiple = net burn ÷ net new ARR;
primary capital-efficiency gate at Series A+. →
references/david-sacks-saas-metrics.md - Bessemer Cloud Atlas. Rule of 40, stage benchmarks, PLG essays.
→
references/bessemer-cloud-atlas.md - SaaS Capital / KeyBanc. Stage benchmarks for private B2B SaaS.
- Meritech Capital. Public SaaS cohort — implied ARR, Rule of 40 composition, NRR medians.
references/meritech-saas-benchmarks.md. Reconcile private vs public →references/benchmark-reconciliation.md.
When to Use
Trigger phrases: "calculate my SaaS metrics", "what is my LTV:CAC ratio?", "how long is my CAC payback?", "what is my NRR?", "run a complete metrics analysis", "what should my metrics be at this stage?", "SaaS benchmarks", "board metrics dashboard", "investor metrics package"
The Core Metrics (18 Formulas)
Revenue Metrics
MRR (Monthly Recurring Revenue) = Sum of all committed monthly subscription revenue. Normalize annual contracts to monthly: Annual ÷ 12. Exclude one-time PS unless board asks for total revenue.
Deep dive: definition variants (committed vs recognized vs billings), ASC 606 summary,
consumption, deferred revenue → references/saas-mrr-accounting-nuances.md.
Bridge template → templates/mrr-bridge-template.md.
Bookings vs billings vs revenue → references/bookings-billings-revenue-matrix.md.
Definition conflicts → references/benchmark-reconciliation.md (MRR / ARR row).
What ships with it
13 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/bessemer-cloud-atlas.md 3.2 KB
- references/bookings-billings-revenue-matrix.md 5.4 KB
- references/david-sacks-saas-metrics.md 2.6 KB
- references/framework-notes.md 1.1 KB
- references/gtm-lifecycle-stages.md 8.6 KB
- references/lifecycle-metrics-by-stage.md 7.9 KB
- references/meritech-saas-benchmarks.md 7.5 KB
- references/metric-definitions-exit-weight.md 3.7 KB
- references/saas-mrr-accounting-nuances.md 9.6 KB
- scripts/check-output.py 869 B runs code
- templates/mrr-bridge-template.md 2.5 KB
- templates/output-template.md 1.8 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.
- 7d ago First seen · 325 lines · 71 tokens per session scan A fb974eb4aea4
saas-metrics-calculator is a skill published in the GitHub repository LeadMagic/gtm-skills (49 stars, last pushed 4d ago), licensed MIT. It adds 71 tokens to every session and 3,888 once invoked, about $0.0004 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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