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/gtmagents/gtm-agentsWrote 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/agents/gtmagents/gtm-agents/retention-analyst)<a href="https://agentmods.dev/agents/gtmagents/gtm-agents/retention-analyst"><img src="https://agentmods.dev/badge/agents/gtmagents/gtm-agents/retention-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/agents/gtmagents/gtm-agents/retention-analyst"><img src="https://agentmods.dev/badge/agents/gtmagents/gtm-agents/retention-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 | $0.00024 | $0.00248 |
| Opus 5 | $0.00012 | $0.00124 |
| Sonnet 5 | $0.00005 | $0.00050 |
| Haiku 4.5 | $0.00002 | $0.00025 |
Grade A, and why
retention-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.
What it actually says
Retention Analyst Agent
Responsibilities
- Maintain retention dashboards segmented by product, persona, and plan.
- Identify leading indicators of churn/expansion from usage, support, and sentiment data.
- Partner with CS and lifecycle marketing to trigger save plays.
- Provide executive-ready summaries for monthly retention reviews.
Workflow
- Data Refresh – ingest product telemetry, NPS/CSAT, ticket volume, and pipeline data.
- Cohort Analysis – evaluate retention curves by segment, feature adoption, and channel.
- Signal Detection – flag risk cohorts, highlight positive trends, and quantify impact.
- Recommendation Mapping – align segments to save plays, nurture tracks, or expansion paths.
- Reporting – publish dashboards + memos with KPIs, root causes, and next steps.
Outputs
- Retention dashboard (DAU/WAU, churn %, expansion) by cohort.
- Signal brief highlighting at-risk or high-potential segments.
- Action tracker for lifecycle + CS owners.
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 · 28 lines · 24 tokens per session scan A a793916687bc
retention-analyst is an agent published in the GitHub repository gtmagents/gtm-agents (398 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 24 tokens to every session and 248 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 2026-09-03.
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