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 ricmmartins/azure-sre-agent-skills --skill 05-incident-postmortemgit clone --depth 1 https://github.com/ricmmartins/azure-sre-agent-skillsWrote 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/ricmmartins/azure-sre-agent-skills/05-incident-postmortem)<a href="https://agentmods.dev/skills/ricmmartins/azure-sre-agent-skills/05-incident-postmortem"><img src="https://agentmods.dev/badge/skills/ricmmartins/azure-sre-agent-skills/05-incident-postmortem/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/ricmmartins/azure-sre-agent-skills/05-incident-postmortem"><img src="https://agentmods.dev/badge/skills/ricmmartins/azure-sre-agent-skills/05-incident-postmortem.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 | $0.00051 | $0.02153 |
| Opus 5 | $0.00026 | $0.01077 |
| Sonnet 5 | $0.00010 | $0.00431 |
| Haiku 4.5 | $0.00005 | $0.00215 |
Grade A, and why
incident-postmortem-generator 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 12d 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 — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incident Postmortem Generator
Purpose
Automatically generate a structured, blameless postmortem document from the context of a resolved incident investigation. Leverages the timeline, root cause analysis, and mitigations already gathered by the SRE Agent.
When to use this skill
- User asks for a postmortem after an incident is resolved
- User asks for an RCA report, incident review, or lessons learned
- Automated trigger after incident resolution (via agent hook)
- User asks "write up what just happened"
Postmortem principles
- Blameless: Focus on systems and processes, never individuals
- Evidence-based: Every claim backed by data (logs, metrics, timeline)
- Action-oriented: Every finding leads to a concrete action item
- Learning-focused: What can we improve systemically?
Generation procedure
Step 1: Gather incident context
From the current conversation and agent memory, extract:
-
Incident metadata:
- Incident ID (from PagerDuty/ServiceNow if connected)
- Severity level
- Duration (detection to resolution)
- Affected services and resources
- Impacted users/customers (if known)
-
Timeline: Reconstruct from the investigation:
- When did the issue start? (first anomaly in metrics)
- When was it detected? (alert fired)
- When was it acknowledged? (engineer engaged)
- Key investigation milestones
- When was mitigation applied?
- When was full resolution confirmed?
-
Root cause: From the agent's RCA:
- What failed?
- Why did it fail?
- Contributing factors
-
Mitigation applied: What was done to resolve it?
Step 2: Assess detection and response
Analyze the incident response quality:
-
Time to detect (TTD): From issue start to alert firing
- Was this acceptable? Could monitoring have caught it earlier?
-
Time to acknowledge (TTA): From alert to human engagement
- Were on-call rotations effective?
-
Time to mitigate (TTM): From engagement to mitigation
- Was the runbook adequate? Did the team have the right access?
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.
- 12d ago First seen · 246 lines · 51 tokens per session scan A ce63feec2530
incident-postmortem-generator is a skill published in the GitHub repository ricmmartins/azure-sre-agent-skills (70 stars, last pushed 18d ago), licensed MIT. It adds 51 tokens to every session and 2,153 once invoked, about $0.0003 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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