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 cnfeat/top-pm-skills --skill churn-analysisgit clone --depth 1 https://github.com/cnfeat/top-pm-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/cnfeat/top-pm-skills/churn-analysis)<a href="https://agentmods.dev/skills/cnfeat/top-pm-skills/churn-analysis"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/churn-analysis/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/cnfeat/top-pm-skills/churn-analysis"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/churn-analysis.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 | $0.00077 | $0.02007 |
| Opus 5 | $0.00039 | $0.01004 |
| Sonnet 5 | $0.00015 | $0.00401 |
| Haiku 4.5 | $0.00008 | $0.00201 |
Grade A, and why
churn-analysis 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 9d 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Churn Analysis Skill
Produce a structured churn analysis that goes beyond the headline rate — identifying why customers leave, which segments are most at risk, and what interventions will have the highest impact on retention.
Required Inputs
Ask for these if not already provided:
- Time period being analysed (e.g. Q1, last 12 months)
- Total customers at start of period and customers churned
- ARR or revenue lost to churn
- Churn reasons data — exit survey results, CSM notes, support data, or sales loss reasons
- Customer segments — by tier, industry, cohort, or product line
- Current retention rate if known
- Any recent changes — pricing, product, support model — that may have affected churn
Churn Categories
Always classify churn before analysing it:
| Category | Definition |
|---|---|
| Voluntary — avoidable | Customer left due to a problem we could have addressed (product gaps, poor onboarding, relationship failures) |
| Voluntary — unavoidable | Customer left for reasons outside our control (budget cuts, acquisition, company shutdown) |
| Involuntary | Payment failure, contract non-renewal by mistake, admin error |
The interventions for each category are different. Conflating them leads to wrong conclusions.
Output Format
Churn Analysis: [Product / Segment / Company]
Period: [Start date] — [End date] Prepared by: [Name] | Date: [Date]
Headline Numbers
| Metric | Value |
|---|---|
| Customers at start of period | [N] |
| Customers churned | [N] |
| Customer churn rate | [X]% |
| ARR at start of period | £/$/€[X] |
| ARR lost to churn | £/$/€[X] |
| Revenue churn rate (gross) | [X]% |
| ARR from expansions (same period) | £/$/€[X] |
| Net revenue retention (NRR) | [X]% |
Benchmark context:
- Customer churn rate: [X]% vs. industry benchmark [Y]% — [above / below / in line]
- NRR: [X]% — [What this means: above 100% = expansion offsets churn; below 100% = shrinking base]
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.
- 9d ago First seen · 188 lines · 77 tokens per session scan A 9904a4dc1742
churn-analysis is a skill published in the GitHub repository cnfeat/top-pm-skills (48 stars, last pushed 3mo ago), licensed MIT. It adds 77 tokens to every session and 2,007 once invoked, about $0.0004 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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