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.
git clone --depth 1 https://github.com/etrebels/claude-code-growth-osWrote 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/commands/etrebels/claude-code-growth-os/retention-report)<a href="https://agentmods.dev/commands/etrebels/claude-code-growth-os/retention-report"><img src="https://agentmods.dev/badge/commands/etrebels/claude-code-growth-os/retention-report.svg" alt="Measured on agentmods" 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 | $0.00026 | $0.00753 |
| Opus 5 | $0.00013 | $0.00377 |
| Sonnet 5 | $0.00005 | $0.00151 |
| Haiku 4.5 | $0.00003 | $0.00075 |
Grade A, and why
retention-report 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 6d 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 — 29 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Retention Report
Generic chassis variant. If a private operating repo (e.g. your own growth-os) defines a command with this name, that version is canonical for that repo's data.
The monthly readout for the right side of the bowtie. /weekly-review reads the direction; this puts a number on it: are you keeping and growing the revenue you've already won, or filling a leaking bucket? It rolls the account book up to the one number the whole motion answers to — net revenue retention.
From ops/customers.md (the account book, with its ARR column) and its git history over the period:
- Set the period and the starting base. Default to the trailing month (or quarter). The cohort is the accounts you held at the start of the period — reconstruct their starting ARR from the book's git history (
git show <commit-as-of-period-start>:ops/customers.md). New logos signed mid-period don't count toward retention. - Compute GRR and NRR — from the numbers, never eyeballed. Name the formula, then compute:
- GRR (gross revenue retention) = (starting ARR − downgrades − churn) ÷ starting ARR. Caps at 100% — it's the floor, what you keep before any expansion.
- NRR (net revenue retention) = (starting ARR + expansion − downgrades − churn) ÷ starting ARR. Above 100% means the base grew without a single new logo.
- If the book doesn't carry
ARRyet, say so and report the count-based picture instead (logos retained / at-risk / churned / expanded) — and add the column so next month computes.
- Churn by reason. Group the accounts lost or downgraded this period by the real reason — value miss, champion exit, budget, product gap, fit. Use the same reasons
churn-savelogs. The reason column is the roadmap for retention; counts without reasons can't be acted on. - Expansion. Which accounts grew, by how much, and off what trigger — the
EXPANSION-SIGNALsexpansion-signalworked. Net expansion is what carries NRR above 100%. - The one read. State it plainly: is the base net-expanding or net-leaking? Below 100% NRR means acquisition spend is filling a leaking bucket (
docs/operating-model.md— the one number). One line. - Next month's two bets. The single biggest retention risk to clear and the single biggest expansion to chase. Write them to the top of
ops/priorities.md.
Lead with the two numbers and the one read. Don't pad it, and don't invent a number the book can't support — an honest count beats a confident guess. If a CRM is your system of record for ARR, reconcile against it per .claude/rules/crm-usage.md — read-only beyond what the daily rituals already persisted.
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.
- 6d ago First seen · 29 lines · 26 tokens per session scan A 7cd7cc1f6290
retention-report is a command published in the GitHub repository etrebels/claude-code-growth-os (20 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 753 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
go-to-market
Build a complete go-to-market strategy based on the requirements found in files.requirements.
doctor
Use when the user invokes /goal-flight doctor to check Goal Flight host and project readiness.
export-clean
Strip internal-only elements (version drawer, review notes) from a staging HTML file to produce a clean export ready for CMS upload or public sharing.
interactive-dev
Start a persistent interactive development session with natural language browser control, auto-error monitoring, and full dev tool access.
pre-ship
Run the pre-ship quality gate checklist before publishing your agent.
growth-plan
Turn diagnosis into a sized greenfield opportunity map + a sequenced, mechanism-driven capture plan to overtake competitors.