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 agentmods add skills/hoavdc/codexkit/codexkit-churn-risk-analyzernpx skills add hoavdc/CodexKit --skill codexkit-churn-risk-analyzergit clone --depth 1 https://github.com/hoavdc/CodexKitWrote 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/hoavdc/codexkit/codexkit-churn-risk-analyzer)<a href="https://agentmods.dev/skills/hoavdc/codexkit/codexkit-churn-risk-analyzer"><img src="https://agentmods.dev/badge/skills/hoavdc/codexkit/codexkit-churn-risk-analyzer.svg" alt="Measured on agentmods" 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 | $0.00072 | $0.01416 |
| Opus 5 | $0.00036 | $0.00708 |
| Sonnet 5 | $0.00014 | $0.00283 |
| Haiku 4.5 | $0.00007 | $0.00142 |
Grade A, and why
codexkit-churn-risk-analyzer 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 4d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Churn Risk Analyzer
When to Use
- During monthly or quarterly customer health reviews
- When churn rate increases and root causes are unclear
- When building a customer health scoring model for the first time
- When preparing retention plays for at-risk accounts
Procedure
Step 1 — Define Health Dimensions
| Dimension | Weight | Indicators |
|---|---|---|
| Usage | 30% | Login frequency, feature adoption, DAU/MAU ratio |
| Engagement | 25% | Support ticket sentiment, NPS, event attendance |
| Support | 15% | Ticket volume, escalations, resolution time |
| Sentiment | 15% | NPS score, CSAT, qualitative feedback |
| Contract | 15% | Time to renewal, expansion signals, payment health |
Adjust weights by business model (self-serve vs enterprise).
Step 2 — Score Each Dimension
| Score | Level | Criteria |
|---|---|---|
| 5 | Healthy | Strong usage, positive sentiment, expanding |
| 4 | Good | Regular usage, neutral/positive feedback |
| 3 | Moderate | Declining trends, some concerns |
| 2 | At-Risk | Significant decline, negative signals |
| 1 | Critical | Minimal engagement, escalations, churn signals |
Step 3 — Calculate Health Score
Health Score = Σ (Dimension Score × Weight)
Step 4 — Segment Customers
| Health Score | Segment | Action |
|---|---|---|
| 4.0–5.0 | 🟢 Healthy | Expansion play, referral ask |
| 2.5–3.9 | 🟡 At-Risk | Proactive outreach, value reinforcement |
| 1.0–2.4 | 🔴 Red | Executive sponsor call, save plan |
Step 5 — Intervention Playbooks
🟢 Healthy:
- Identify expansion opportunities (upsell, cross-sell)
- Request referral or case study
- Invite to advisory board or beta programs
🟡 At-Risk:
- Schedule CSM check-in within 48 hours
- Re-onboard on underused features
- Share success stories from similar companies
- Offer training session or office hours
🔴 Red:
- Executive sponsor call within 24 hours
- Create 30-day save plan with specific milestones
- Offer concessions if justified (credit, extended trial)
- Prepare for graceful offboarding if save fails
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.
- 4d ago First seen · 163 lines · 72 tokens per session scan A 692bf6a96fc9
codexkit-churn-risk-analyzer is a skill published in the GitHub repository hoavdc/CodexKit (21 stars, last pushed 3mo ago), licensed MIT. It adds 72 tokens to every session and 1,416 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 2026-08-30.
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