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 UnitOneAI/SecuritySkills --skill post-incident-reviewgit clone --depth 1 https://github.com/UnitOneAI/SecuritySkillsWrote 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/unitoneai/securityskills/post-incident-review)<a href="https://agentmods.dev/skills/unitoneai/securityskills/post-incident-review"><img src="https://agentmods.dev/badge/skills/unitoneai/securityskills/post-incident-review/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/unitoneai/securityskills/post-incident-review"><img src="https://agentmods.dev/badge/skills/unitoneai/securityskills/post-incident-review.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 | $0.00096 | $0.06307 |
| Opus 5 | $0.00048 | $0.03154 |
| Sonnet 5 | $0.00019 | $0.01261 |
| Haiku 4.5 | $0.00010 | $0.00631 |
Grade A, and why
post-incident-review 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 — 458 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Post-Incident Review -- NIST SP 800-61 Rev 2
Framework: NIST SP 800-61 Rev 2 (Section 3.4: Post-Incident Activity) Role: SOC Analyst, Security Engineer, vCISO Time: 30-60 min Output: Post-incident review report with blameless retrospective, root cause analysis, control failure mapping, metrics (MTTD, MTTR, MTTC), lessons learned, and remediation tracking plan
1. When to Use
If a target is provided via arguments, focus the review on: $ARGUMENTS
Invoke this skill when any of the following conditions are met:
- Incident resolved -- An incident has been contained, eradicated, and recovery is complete or substantially complete. The PIR should be conducted within 5 business days of incident closure (NIST recommendation: "within several days of the end of the incident").
- Scheduled retrospective -- The organization's IR process mandates a post-incident review for all incidents above a severity threshold (typically SEV-1 and SEV-2, optionally SEV-3).
- Pattern identification -- Multiple similar incidents have occurred and the team needs to identify systemic root causes and recurring control failures.
- Compliance requirement -- Regulatory frameworks (SOC 2, ISO 27001, PCI DSS) or cyber insurance policies require documented post-incident analysis and lessons learned.
- Near-miss analysis -- A security event that could have been a significant incident was detected and contained early, and the team wants to extract preventive lessons.
Do not use when: The incident is still active and in the containment or eradication phase (use ir-playbook or containment). This skill is for post-resolution analysis only.
2. Context the Agent Needs
Before conducting the PIR, gather or confirm:
- Incident report -- The completed incident response report from the ir-playbook (incident ID, classification, severity, timeline, IOCs, actions taken).
- Timeline of events -- Chronological record of all significant events from initial compromise through detection, containment, eradication, and recovery.
- Team participants -- Names and roles of all personnel involved in the response (IR team, management, legal, communications, external responders).
- Communication logs -- Records of notifications, escalations, and status updates sent during the incident.
- Evidence and forensic findings -- Summary of forensic analysis results, root cause indicators, and attacker TTPs identified.
- Existing controls -- Documentation of security controls that were in place at the time of the incident (detection rules, access controls, network segmentation, patching cadence).
- Previous PIR reports -- Any prior post-incident reviews for similar incident types, to identify recurring patterns.
- Metrics data -- Timestamps needed to compute MTTD, MTTR, and MTTC (see Step 4).
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 · 458 lines · 96 tokens per session scan A 404a6bfdd265
post-incident-review is a skill published in the GitHub repository UnitOneAI/SecuritySkills (61 stars, last pushed 2mo ago), licensed MIT. It adds 96 tokens to every session and 6,307 once invoked, about $0.0005 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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