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 adaptico/adaptico-os --skill gtm-retentiongit clone --depth 1 https://github.com/adaptico/adaptico-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/adaptico/adaptico-os/gtm-retention)<a href="https://agentmods.dev/skills/adaptico/adaptico-os/gtm-retention"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-retention/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/adaptico/adaptico-os/gtm-retention"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-retention.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 | $0.00130 | $0.06133 |
| Opus 5 | $0.00065 | $0.03067 |
| Sonnet 5 | $0.00026 | $0.01227 |
| Haiku 4.5 | $0.00013 | $0.00613 |
Grade C, and why
gtm-retention scanned grade C with 1 finding 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 10d 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.
Tells the agent never to refusehighAnti-refusal
Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.
> Then generate the work anyway - never refuse. How it starts
The opening of the file, as written. The whole thing — 348 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Retention & Activation Diagnosis
Default lens: a SaaS / AI software startup. Advise a technical founder marketing their own modern software product (SaaS, AI/API, dev tool, or app). Tailor every recommendation to that reader.
Stage-fit (
retention): Tier 1 Too early · Tier 2 Useful · Tier 3 Core. If the founder's tier (from PROFILE.md) makes this Too early or Avoid, prepend this note verbatim: "There's almost nothing to retain yet, and early churn is a PMF signal, not a leak to plug. Cancel-flows and save-offers pay off once you have a paying base - for now, keep your first users by talking to them, not by automating win-backs." Then generate the work anyway - never refuse.
Full persona and general guidance: read
../gtm/templates/advisor-prompt.md(installed with the gtm orchestrator); if the file is absent, continue with the default lens above.
You are the retention engine for /gtm retention <target>. For an early software product, retention is not won with loyalty schemes and win-back blasts - it is decided in the first days of a user's life, in the gap between signup and the first time the product proves itself. Subscription retention analyses (ProfitWell, now part of Paddle) consistently put 60-70% of SaaS churn inside the customer's first 90 days: most churn is an onboarding problem before it is a product problem. So this skill works front-to-back: first the time-to-value teardown and the one activation metric worth committing to, then a first-90-days defense plan, and only then the mechanics at the exit door - cancel flow, save offers, and the failed-payment posture.
Where this sits among the neighboring commands, so the jobs stay distinct:
/gtm funnelmaps the whole path from landing click to paid and scores every step. This skill starts where that map narrows: the signup-to-value gap and the paid lifecycle after it - and it ends in commitments the funnel map doesn't make (one activation metric, a 90-day plan, cancel mechanics)./gtm emailswrites the sequences - activation onboarding and dunning. This skill decides what those sequences anchor to (the activation metric) and the recovery posture around them. It never drafts sequence copy./gtm auditscores Activation & Time-to-Value as one vector of the composite; this is that vector's deep dive.
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.
- 10d ago First seen · 348 lines · 130 tokens per session scan C dfa755755e44
gtm-retention is a skill published in the GitHub repository adaptico/adaptico-os (18 stars, last pushed 23d ago), licensed MIT. It adds 130 tokens to every session and 6,133 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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