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 rules/jkudjo/oh-my-cursor/incidentgit clone --depth 1 https://github.com/Jkudjo/oh-my-cursorWrote 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/rules/jkudjo/oh-my-cursor/incident)<a href="https://agentmods.dev/rules/jkudjo/oh-my-cursor/incident"><img src="https://agentmods.dev/badge/rules/jkudjo/oh-my-cursor/incident.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 | $0.00016 | $0.00979 |
| Opus 5 | $0.00008 | $0.00490 |
| Sonnet 5 | $0.00003 | $0.00196 |
| Haiku 4.5 | $0.00002 | $0.00098 |
Grade A, and why
incident 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@incident
Trigger: Live production issue — errors, outages, degradation, customer impact.
Posture
- Read-only first. No changes until the cause is understood.
- Separate confirmed facts from hypotheses. Always.
- Green metrics do not mean no incident. Metrics lie via wrong thresholds, aggregation, wrong user segment, or synthetic blindspots.
- Do not assume the most recent deploy is the cause — it is a hypothesis, not a fact.
Phase 1 — Impact triage (first 2 minutes)
Answer these before anything else:
Impact scope: all users / region / segment / endpoint / feature
Symptom: exact error, latency, behavior
Start time: when did it begin?
Blast radius: who and what is affected right now
Is it worsening, stable, or recovering?
Call start_mode mode=autopilot task=incident: {description}.
Phase 2 — Evidence gathering (read-only)
Collect in this order (fastest signal first):
- Recent changes — deploys, config changes, migrations, feature flag changes in the last 2 hours
- Error logs — actual error messages, stack traces, not just counts
- Traces — request path for a failing vs passing request
- Infra health — pod status, restart count, events, readiness probes, node pressure
- Dependencies — downstream service health, DB connectivity, queue depth, third-party status pages
- Regional scope — is it one region/AZ/CDN edge or global?
After collecting: list confirmed facts vs unconfirmed hypotheses explicitly.
Phase 3 — Hypothesis tree
Generate the full hypothesis tree before investigating any branch:
Category: App
H1: Deploy introduced regression — [evidence needed]
H2: Config drift between env — [evidence needed]
H3: Dependency timeout — [evidence needed]
Category: Infra
H4: Pod selector mismatch / no ready endpoints — [evidence needed]
H5: Readiness probe rejecting healthy pods — [evidence needed]
H6: Network policy blocking traffic — [evidence needed]
H7: Ingress/ALB misconfiguration — [evidence needed]
Category: Data
H8: DB connection pool exhausted — [evidence needed]
H9: Slow query causing cascading timeout — [evidence needed]
H10: Migration left partial state — [evidence needed]
Category: Client/Observability
H11: Narrow user segment not covered by monitoring — [evidence needed]
H12: CDN caching stale error response — [evidence needed]
H13: Stale client session / auth token — [evidence needed]
H14: Feature flag targeting mismatch — [evidence needed]
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 · 118 lines · 16 tokens per session scan A 2b1b06b2be13
incident is a cursor rule published in the GitHub repository Jkudjo/oh-my-cursor (1 stars, last pushed 5mo ago), licensed MIT. It adds 16 tokens to every session and 979 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 2026-08-31.
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