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 Infinite-Labs-AI/infinite-skills --skill retentiongit clone --depth 1 https://github.com/Infinite-Labs-AI/infinite-skillsWrote 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/infinite-labs-ai/infinite-skills/retention)<a href="https://agentmods.dev/skills/infinite-labs-ai/infinite-skills/retention"><img src="https://agentmods.dev/badge/skills/infinite-labs-ai/infinite-skills/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/infinite-labs-ai/infinite-skills/retention"><img src="https://agentmods.dev/badge/skills/infinite-labs-ai/infinite-skills/retention.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 | $0.00031 | $0.00501 |
| Opus 5.5 | $0.00012 | $0.00200 |
| Sonnet 5.5 | $0.00006 | $0.00100 |
| Haiku 4.5 | $0.00003 | $0.00050 |
Grade A, and why
retention 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Retention
Find where customers lose momentum and choose practical ways to improve activation, renewal, expansion, or winback.
Map The Customer State
Use product analytics, billing data, CRM notes, cancellation reasons, support tickets, interviews, or lifecycle performance. If unavailable, ask for:
- Customer lifecycle stages.
- Activation milestone.
- Churn or cancellation point.
- Plan, pricing, and renewal model.
- Common objections or complaints.
- Existing save, winback, and dunning flows.
Identify Retention Leaks
Classify by cause:
- Setup failure: customer never reaches the first useful outcome.
- Value gap: product works but not enough to justify cost.
- Habit gap: value exists but usage does not become routine.
- Champion loss: buyer or user changes.
- Expectation mismatch: marketing or sales promised the wrong thing.
- Payment failure: billing breaks an otherwise healthy account.
- Expansion ceiling: customer cannot grow into the next plan.
Choose Interventions
Match intervention to cause:
- Activation checklist or concierge setup.
- Use-case education.
- Health alerts.
- Save offer or plan downgrade.
- Pause option.
- Failed payment recovery.
- Renewal proof recap.
- Expansion trigger.
- Winback based on prior use case.
Do not use discounts as the default save tactic. If value is unclear, discounting only delays churn.
Choose Retention Plays
Order interventions from least invasive to most commercial:
- Product fix or setup improvement.
- Education or lifecycle guidance.
- Human support or concierge save.
- Billing repair or dunning.
- Plan change, pause, or downgrade.
- Commercial save offer.
- Winback after exit.
Use discounts only when the evidence suggests price or timing is the real barrier.
Output
Retention map:
Lifecycle stages:
Activation milestone:
Main leak:
Leak diagnosis:
| Stage | Symptom | Evidence | Root cause confidence | First intervention |
Intervention ladder:
1. Product:
2. Education:
3. Human support:
4. Billing:
5. Commercial:
Cancellation flow:
- Ask:
- Route:
- Save option:
- Exit if:
Winback segment:
- Who:
- Why now:
- Message:
Metrics:
- Leading:
- Lagging:
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 96 lines · 31 tokens per session scan A a930e43c5920
retention is a skill published in the GitHub repository Infinite-Labs-AI/infinite-skills (44 stars, last pushed 2mo ago), licensed MIT. It adds 31 tokens to every session and 501 once invoked, about $0.0001 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.
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