agent-incident-postmortem
Run a blameless postmortem for an incident caused by an AI agent or LLM feature — hallucinated facts shipped to users, runaway tool use, prompt injection, cost blowouts, or wrong actions taken autonomously. Use when asked to write up an AI incident, analyse why an agent did something wrong, or produce corrective actions after an LLM failure. Produces a structured postmortem with trace reconstruction, a root-cause layer analysis, and corrective actions including a permanent regression case. For non-AI production incidents use incident-postmortem.
npx skills add mohitagw15856/pm-claude-skills --skill agent-incident-postmortem --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Agent Incident Postmortem Skill AI incidents differ from outages: the system didn't go down — it did something wrong, confidently, and maybe only once. This skill adapts blameless postmortem practice to nondeterministic systems, where "can we reproduce it?" needs traces, not just steps. ## What This Skill Produces - A **blameless postmortem document** with timeline and user/business impact - A **trace reconstruction** of what the agent saw, decided, and did - A **root-cause analysis across the AI failure layers** (not "the model hallucinated" as a conclusion) - **Corrective actions** — always including a new permanent case in the regression suite ## Required Inputs Ask for (if not already provided): - **What the agent did** and what it should have done - **The trace** — the full request: system prompt, context, tool calls and results, output. If no trace exists, that absence is itself a finding - **Blast radius** — how many users/requests, over what window, and whether it's ongoing - **Detection** — how it was noticed (user report? monitor? luck?) and how long after it started ## Root-Cause Layers Walk the layers in order; the root cause is usually the *earliest* layer that could
- What This Skill Produces
- Required Inputs
- Root-Cause Layers
- Nondeterminism Discipline
- Output Format
- AI Incident Postmortem: [title] — [date]
- Quality Checks
- Anti-Patterns
What does the agent-incident-postmortem skill do?
Run a blameless postmortem for an incident caused by an AI agent or LLM feature — hallucinated facts shipped to users, runaway tool use, prompt injection, cost blowouts, or wrong actions taken autonomously. Use when asked to write up an AI incident, analyse why an agent did something wrong, or produce corrective actions after an LLM failure. Produces a structured postmortem with trace reconstruction, a root-cause layer analysis, and corrective actions including a permanent regression case. For non-AI production incidents use incident-postmortem.
How do I install it?
Run `npx skills add mohitagw15856/pm-claude-skills --skill agent-incident-postmortem --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.