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 schmitech/orbit --skill churn-risk-playbookgit clone --depth 1 https://github.com/schmitech/orbitWrote 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/schmitech/orbit/churn-risk-playbook)<a href="https://agentmods.dev/skills/schmitech/orbit/churn-risk-playbook"><img src="https://agentmods.dev/badge/skills/schmitech/orbit/churn-risk-playbook/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/schmitech/orbit/churn-risk-playbook"><img src="https://agentmods.dev/badge/skills/schmitech/orbit/churn-risk-playbook.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 | $0.00019 | $0.00276 |
| Opus 5 | $0.00010 | $0.00138 |
| Sonnet 5 | $0.00004 | $0.00055 |
| Haiku 4.5 | $0.00002 | $0.00028 |
Grade A, and why
churn-risk-playbook 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 10d 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
Order of calls
Call get_product_telemetry for the customer before
simulate_churn_risk_scenario. Both tools use the server's current customer
data; the telemetry result supplies the adoption context needed to explain the
simulation rather than relying on model assumptions.
Presenting results
Never present a bare churn probability. Always pair it with the simulation's key drivers and the telemetry's utilization or adoption alerts, so the number is explainable rather than a black box. The simulation itself accounts for open P1/P2 support escalations; telemetry does not return ticket volume.
Render a concise risk summary with Current ARR, Health Score, Seat
Utilization, Churn Probability, ARR at Risk, and Risk Category. Follow it with
the simulation's keyDrivers and the telemetry's telemetryAlerts. Do not
infer support-ticket volume beyond the simulation's openEscalationsCount, or
invent a trend or risk driver that neither result returns.
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.
- 10d ago First seen · 31 lines · 19 tokens per session scan A b2af43447a68
churn-risk-playbook is a skill published in the GitHub repository schmitech/orbit (344 stars, last pushed today), licensed Apache-2.0. It adds 19 tokens to every session and 276 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 2026-08-30.
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