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 varunk130/ai-gtm-skill-library --skill revenue-analyticsgit clone --depth 1 https://github.com/varunk130/ai-gtm-skill-libraryWrote 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/varunk130/ai-gtm-skill-library/revenue-analytics)<a href="https://agentmods.dev/skills/varunk130/ai-gtm-skill-library/revenue-analytics"><img src="https://agentmods.dev/badge/skills/varunk130/ai-gtm-skill-library/revenue-analytics/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/varunk130/ai-gtm-skill-library/revenue-analytics"><img src="https://agentmods.dev/badge/skills/varunk130/ai-gtm-skill-library/revenue-analytics.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 | $0.00069 | $0.01390 |
| Opus 5.5 | $0.00028 | $0.00556 |
| Sonnet 5.5 | $0.00014 | $0.00278 |
| Haiku 4.5 | $0.00007 | $0.00139 |
Grade A, and why
revenue-analytics 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 1mo 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Revenue Analytics (LADDER Framework)
Design a revenue analytics layer that answers where revenue is being created, where it's leaking, and which lever to pull next - not a dashboard of vanity totals. LADDER decomposes ARR, attributes it, diagnoses drivers, and turns analysis into named actions.
Core Principle
Revenue analytics fails when it stops at the totals. Reporting ARR up-and-to-the-right tells you nothing actionable. LADDER decomposes revenue into the components a leadership team can act on within a quarter.
The LADDER Framework
| Letter | Stage | The Question |
|---|---|---|
| L | Leading Indicators | Which forward-looking metrics predict ARR movement 1-2 quarters out? |
| A | Attribution | Where does new ARR come from - channel, motion, segment, cohort? |
| D | Drivers | Which 3-5 levers explain most of the variance in NRR and growth? |
| D | Diagnosis | What's broken or accelerating, and what's the named hypothesis? |
| E | Expansion Economics | What's the economics of expansion vs new logo by segment? |
| R | Retention Decomposition | What's GRR, contraction, churn - by cohort and reason code? |
ARR Waterfall
The minimum decomposition every leader should be able to recite:
| Component | Definition |
|---|---|
| Starting ARR | Beginning-of-period book |
| New Logo ARR | Net-new customer ARR added |
| Expansion ARR | Seat / module / price-up from existing customers |
| Contraction ARR | Seat / module / price-down from existing customers (not churn) |
| Churn ARR | Customers lost (logo or full) |
| Ending ARR | Computed from the above |
| NRR | (Ending − New Logo) / Starting |
| GRR | (Starting − Contraction − Churn) / Starting |
Leading Indicators
Lagging metrics (ARR, NRR) confirm what already happened. Leading metrics let you act:
| Metric | Leads What | Lead Time |
|---|---|---|
| Qualified pipeline coverage (3x) | Bookings | 1-2 quarters |
| Engagement score trajectory | Renewal / NRR | 2 quarters |
| Health score distribution | GRR | 1-2 quarters |
| MQL→SQL conversion | New logo bookings | 1 quarter |
| Expansion pipeline coverage | Expansion ARR | 1 quarter |
| Win-rate by segment | Booking productivity | 1 quarter |
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.
- 1mo ago First seen · 121 lines · 69 tokens per session scan A 04b3cfb2e58d
revenue-analytics is a skill published in the GitHub repository varunk130/ai-gtm-skill-library (7 stars, last pushed 10d ago), licensed MIT. It adds 69 tokens to every session and 1,390 once invoked, about $0.0003 per session on Opus 5.5. 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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