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 etrebels/claude-code-growth-os --skill retention-feedbackgit 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/skills/etrebels/claude-code-growth-os/retention-feedback)<a href="https://agentmods.dev/skills/etrebels/claude-code-growth-os/retention-feedback"><img src="https://agentmods.dev/badge/skills/etrebels/claude-code-growth-os/retention-feedback/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/etrebels/claude-code-growth-os/retention-feedback"><img src="https://agentmods.dev/badge/skills/etrebels/claude-code-growth-os/retention-feedback.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 | $0.00086 | $0.00704 |
| Opus 5.5 | $0.00034 | $0.00282 |
| Sonnet 5.5 | $0.00017 | $0.00141 |
| Haiku 4.5 | $0.00009 | $0.00070 |
Grade A, and why
retention-feedback 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 — 28 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Retention Feedback
The loop that keeps the post-sale half of the motion connected to product — the half the funnel forgets. Sales→marketing is the loop everyone can see; this is its mirror on the right side of the bowtie. Field intelligence from onboarding, adoption, and renewal flows back to product and CS on a cadence, instead of dying in a QBR. This is the four-function version of the alignment thesis in docs/why-align.md — made concrete as a tagged line in the same shared log the marketing-feedback skill writes to.
From a source — an onboarding note, a usage review, a support thread, a renewal call, a deal update:
- Scan for the four signal types:
- Adoption friction — where customers stall between signing and getting value (the workflow they never turned on, the setup step that blocks them).
- Churn risk — the real leading indicator: usage trending down, a champion gone quiet, a single-threaded account after a reorg.
- Expansion blocker / signal — a missing feature that's holding back a renewal or a second department; or, the opposite, a customer asking for more unprompted.
- Renewal-loss reason — the real one, logged, not remembered (people misdiagnose why accounts leave as often as why deals are lost).
- Log each as a tagged line in
ops/feedback-log.md— the same single home marketing's tags use — so product and CS can act without a meeting:RETENTION-RISK: [account] — [the adoption/churn/blocker signal] → [product or CS action]EXPANSION-SIGNAL:when a healthy account is ready to grow (hand to sales with the CS context attached).
- Route, don't dump. A feature request that blocks adoption goes to the roadmap, not the backlog void. A churn signal triggers the renewal motion early — day 60, not day 85. Don't tag every quiet week as a risk; tag it when usage, the champion, or the value story is actually slipping.
The tag is the hand-off. One file — the same one marketing reads — now carries both loops, so a post-sale signal can't quietly die any more than a field objection can. Product's job is to clear the RETENTION-RISK lines that are really roadmap; CS's job is to keep them honest and act on the renewal clock.
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 · 28 lines · 86 tokens per session scan A b1c176b4bc6a
retention-feedback is a skill published in the GitHub repository etrebels/claude-code-growth-os (21 stars, last pushed today), licensed MIT. It adds 86 tokens to every session and 704 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 2026-08-30.
Other skills, from other repositories
startup-launch-playbook
A step-by-step playbook for early-stage startups going from pre-seed to their first 1000 users. Covers MVP validation, initial traction channels, and founder-led growth tactics. By @WeiYipei — follow on X for more startup growth insights.
a-b-testing
Design statistically sound GTM experiments for copy, channels, landing pages, sequencing, pricing, and funnel conversion. Produces hypothesis, sample-size logic, success metrics, test plan, analysis method, and scale/stop/kill recommendation. Use when planning A/B tests, split tests, or experiment roadmaps.
attribution
Build practical B2B attribution models across first touch, lead creation, opportunity creation, multi-touch, account-based influence, and sales-sourced revenue. Produces model comparison, UTM governance, source-of-truth rules, and channel ROI view. Use when marketing and sales disagree on source or ROI.
campaign-analytics
Analyze campaign performance from deliverability through revenue: delivery, engagement, replies, meetings, SQOs, pipeline, CAC, and payback. Produces diagnostic scorecard, root-cause analysis, benchmark comparison, and next-action plan. Use when deciding whether to scale, fix, or kill campaigns.
deliverability-monitoring
Monitor outbound deliverability health across domains, inboxes, DNS, bounces, spam placement, reply rates, and reputation signals. Produces alert thresholds, dashboard spec, weekly QA checklist, and remediation playbook. Use when inboxing drops, bounce rates rise, campaigns underperform, or new infrastructure launches.
gtm-metrics
Build a GTM metrics system for SaaS: funnel conversion, pipeline velocity, win rates, CAC, payback, NRR, sales efficiency, growth accounting, and executive dashboards. Use when creating metrics dashboards, board reports, revenue reviews, operating cadence, or diagnosing growth constraints.