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 ClarentCinematics/Codex-Skills-for-Enterprise --skill incident-postmortem-assistantgit clone --depth 1 https://github.com/ClarentCinematics/Codex-Skills-for-EnterpriseWrote 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/clarentcinematics/codex-skills-for-enterprise/incident-postmortem-assistant)<a href="https://agentmods.dev/skills/clarentcinematics/codex-skills-for-enterprise/incident-postmortem-assistant"><img src="https://agentmods.dev/badge/skills/clarentcinematics/codex-skills-for-enterprise/incident-postmortem-assistant/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/clarentcinematics/codex-skills-for-enterprise/incident-postmortem-assistant"><img src="https://agentmods.dev/badge/skills/clarentcinematics/codex-skills-for-enterprise/incident-postmortem-assistant.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 | $0.00079 | $0.00521 |
| Opus 5 | $0.00039 | $0.00260 |
| Sonnet 5 | $0.00016 | $0.00104 |
| Haiku 4.5 | $0.00008 | $0.00052 |
Grade A, and why
incident-postmortem-assistant 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.
How it starts
The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incident Postmortem Assistant
Workflow
- Identify incident scope, affected systems, customer or business impact, timeline, responders, and available evidence.
- Separate observed facts from hypotheses, assumptions, downstream symptoms, and missing context.
- Build a blameless narrative with impact, detection, mitigation, resolution, and learning points.
- Convert lessons into corrective actions with owners and due dates only when stated.
- Flag unresolved questions, evidence gaps, repeated timestamps, ambiguous ownership, and follow-up needs.
Script-Assisted Workflow
When given a timeline or incident notes file, run scripts/check_incident_timeline.py --input <path> before drafting the postmortem. Use --json when structured evidence is needed. Treat the script output as deterministic evidence about timeline quality, not as the final root cause.
Output Standard
Use this structure by default:
- Incident Summary: scope, status, impact, and confidence.
- Timeline: observed events with timestamps, owners, and actions when stated.
- Impact: affected users, services, duration, and business effect; use
Not statedwhen absent. - Root-Cause Hypotheses: ranked hypotheses with evidence and uncertainty.
- Contributing Factors: process, system, monitoring, release, dependency, or handoff factors.
- Corrective Actions: action, owner, due date, and validation method when stated.
- Open Questions: missing facts needed before publication.
- Caveats: source limitations and non-inferred fields.
Rules
- Keep the postmortem blameless and evidence-grounded.
- Do not invent severity, customer impact, owners, dates, root cause, or corrective action commitments.
- Label hypotheses as hypotheses until supported by source evidence.
- Treat unresolved timeline gaps, repeated timestamps, and missing owners as review risks.
- Escalate legal, customer-notification, or compliance conclusions to human review.
References
Read references/postmortem-rubric.md when preparing a formal postmortem, executive incident recap, or corrective-action review.
What ships with it
3 files 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.
- 10d ago First seen · 44 lines · 79 tokens per session scan A f548e2dcaee8
incident-postmortem-assistant is a skill published in the GitHub repository ClarentCinematics/Codex-Skills-for-Enterprise (2 stars, last pushed 2mo ago), licensed MIT. It adds 79 tokens to every session and 521 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 2026-08-31.
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