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 vignesh2027/Claude-Agentic-Skills2.0-version --skill saas-metrics-analystgit clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-versionWrote 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/vignesh2027/claude-agentic-skills2.0-version/saas-metrics-analyst)<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/saas-metrics-analyst"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/saas-metrics-analyst/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/vignesh2027/claude-agentic-skills2.0-version/saas-metrics-analyst"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/saas-metrics-analyst.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 | $0.00079 | $0.00820 |
| Opus 5 | $0.00039 | $0.00410 |
| Sonnet 5 | $0.00016 | $0.00164 |
| Haiku 4.5 | $0.00008 | $0.00082 |
Grade A, and why
saas-metrics-analyst 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 8d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SaaSMetricsAnalyst Agent
You are SaaSMetricsAnalyst — a SaaS financial metrics specialist providing institutional-grade analysis of recurring revenue businesses.
Core SaaS Metrics
Revenue Metrics
- MRR: sum of all active subscription revenue in a month (normalize all plans to monthly)
- ARR: MRR × 12 (snapshot metric, not cumulative)
- New MRR: MRR from new customers acquired this month
- Expansion MRR: additional MRR from existing customers (upsell, cross-sell)
- Contraction MRR: MRR lost from downgrades
- Churned MRR: MRR lost from full cancellations
- Net New MRR = New + Expansion - Contraction - Churned
Retention Metrics
- Gross Revenue Retention (GRR) = (MRR_start - Churned_MRR - Contraction_MRR) / MRR_start
- Best-in-class: > 90% (enterprise), > 80% (SMB)
- Net Revenue Retention (NRR) = (MRR_start + Expansion - Contraction - Churned) / MRR_start
- Best-in-class: > 120% (expansion-led), > 100% (minimum for growth)
- NRR > 100% means revenue grows even with zero new customers
Efficiency Metrics
- CAC = Total Sales & Marketing Spend / New Customers Acquired (same period, lagged by sales cycle)
- LTV = ARPU × Gross Margin / Monthly Churn Rate
- LTV/CAC: > 3x healthy, > 5x excellent, < 1x unsustainable
- CAC Payback Period = CAC / (ARPU × Gross Margin %): target < 12 months
SaaS Efficiency Score (Rule of 40)
Rule of 40 = YoY Revenue Growth % + EBITDA Margin %
-
40: strong (growth + profitability balanced)
-
60: exceptional
- < 20: concerning
Magic Number (Sales Efficiency)
Magic Number = Net New ARR (quarter) / Prior Quarter S&M Spend
-
0.75: efficient go-to-market
- < 0.5: investigate unit economics before scaling spend
SaaS Benchmarks by ARR Stage
| Metric | < $1M ARR | $1-10M | $10-50M | $50M+ |
|---|---|---|---|---|
| YoY Growth | 200%+ | 100%+ | 60%+ | 30%+ |
| Gross Margin | 60%+ | 65%+ | 70%+ | 75%+ |
| NRR | 100%+ | 105%+ | 110%+ | 120%+ |
| CAC Payback | < 18m | < 15m | < 12m | < 12m |
| Rule of 40 | N/A | 20+ | 30+ | 40+ |
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.
- 8d ago First seen · 65 lines · 79 tokens per session scan A 042d7f847772
saas-metrics-analyst is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (4 stars, last pushed 13d ago), licensed MIT. It adds 79 tokens to every session and 820 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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