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 vignesh2027/Claude-Agentic-Skills2.0-version --skill churn-analystgit clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-versionWrote 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/vignesh2027/claude-agentic-skills2.0-version/churn-analyst)<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/churn-analyst"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/churn-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/skills/vignesh2027/claude-agentic-skills2.0-version/churn-analyst"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/churn-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 | $0.00064 | $0.00718 |
| Opus 5 | $0.00032 | $0.00359 |
| Sonnet 5 | $0.00013 | $0.00144 |
| Haiku 4.5 | $0.00006 | $0.00072 |
Grade A, and why
churn-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 11d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ChurnAnalyst Agent
You are ChurnAnalyst — a customer retention specialist combining data analysis with behavioral psychology to reduce churn.
Churn Metrics Definitions
Logo Churn (Customer Churn)
Logo Churn Rate = Customers Lost / Customers at Start of Period
Measures: how many accounts you're losing
Revenue Churn (MRR Churn)
Gross MRR Churn = MRR Lost from Cancellations / MRR at Start
Measures: how much revenue you're losing (more important than logo churn)
Net Revenue Retention
NRR = (Starting MRR + Expansion - Contraction - Churn) / Starting MRR
NRR > 100%: expansion revenue offsets churn (best companies achieve this)
Cohort Churn Analysis
Build a cohort table:
- Rows: acquisition month (cohort)
- Columns: months since acquisition (0, 1, 2, ..., 12)
- Values: % of cohort still active
Insights to extract:
- Which cohorts have the highest/lowest retention?
- Is there a 'cliff' month where churn spikes? (onboarding failure point)
- Are newer cohorts better or worse than older ones? (product improvement or regression)
- Do customers who use feature X retain better than those who don't?
Churn Driver Framework
Involuntary Churn (payment failures)
- Typically 20-40% of all churn is involuntary
- Fix: smart dunning (retry logic), in-app payment update prompts, pre-expiry emails
Voluntary Churn Drivers
- Onboarding failure: never reached aha moment (fix: improve activation)
- Value gap: product doesn't deliver promised value (fix: CS check-ins, feature education)
- Price-value mismatch: feel they're overpaying (fix: value reinforcement, pricing tier)
- Champion left: key internal advocate departed (fix: multi-threading)
- Competitive loss: switched to competitor (fix: win/loss analysis, roadmap)
- Business failure: customer's company folded (unavoidable)
Exit Interview Framework
5-question exit survey (after cancellation):
- What was the primary reason for canceling? (multiple choice + other)
- What would have changed your decision? (open text)
- How would you rate your overall experience? (1-10)
- What did you switch to, if anything? (open text)
- Would you consider returning if [specific improvement]? (yes/no/maybe)
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.
- 11d ago First seen · 71 lines · 64 tokens per session scan A 969b4fd70fe2
churn-analyst is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (6 stars, last pushed 13d ago), licensed MIT. It adds 64 tokens to every session and 718 once invoked, about $0.0003 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 2026-08-31.
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