postmortem

A postmortem document generator based on an incident description. A postmortem is a record of what went wrong, who or what was affected, how the event unfolded, and what should change afterward.

In plain words
What is it for?
Use it to create incident reports with an executive summary, impact table, UTC timeline, causes, actions, and follow-up information.
Why use it?
It provides a consistent, blameless structure for documenting incidents instead of starting each report from scratch. It also prompts for missing details such as severity, duration, and impact.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/kid-sid/claude-spellbook/postmortem
Clone the repo
git clone --depth 1 https://github.com/kid-sid/claude-spellbook

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 971 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00971
Opus 5 $0.00000 $0.00485
Sonnet 5 $0.00000 $0.00194
Haiku 4.5 $0.00000 $0.00097

Measured 3d ago against content hash 6fd547b1284a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

postmortem 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 3d 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.

.claude/commands/postmortem.md · 118 lines

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.

Generate a postmortem document from an incident description.

Instructions

  1. Ask the user (if not already specified):

    • Incident title: brief description of what happened
    • Severity: SEV1 (critical) / SEV2 (major) / SEV3 (minor) / SEV4 (low)
    • Duration: when did it start and end?
    • Impact: what was affected? (users, services, revenue)
  2. Generate the postmortem using this blameless template:

# Postmortem: {Incident Title}

**Date:** {YYYY-MM-DD}
**Severity:** {SEV1/SEV2/SEV3/SEV4}
**Duration:** {start time} — {end time} ({total duration})
**Authors:** {names}
**Status:** Draft | In Review | Final

## Executive Summary

{2-3 sentence summary: what happened, what was the impact, and is it fully resolved?}

## Impact

| Metric | Value |
|--------|-------|
| Users affected | {number or percentage} |
| Duration of impact | {duration} |
| Revenue impact | {estimated $} |
| SLA impact | {e.g., dropped below 99.9%} |
| Support tickets | {count} |

## Timeline (all times in UTC)

| Time | Event |
|------|-------|
| {HH:MM} | {First signal: alert fired / user report / monitoring} |
| {HH:MM} | {Detection: who noticed and how} |
| {HH:MM} | {Escalation: who was paged} |
| {HH:MM} | {Investigation: what was checked first} |
| {HH:MM} | {Mitigation: what stopped the bleeding} |
| {HH:MM} | {Resolution: root cause fixed} |
| {HH:MM} | {All-clear: confirmed recovery} |

## Root Cause

{Detailed technical explanation of what went wrong and why. Be specific — name the exact component, config, or code path.}

## Detection

- **How was it detected?** {alert / user report / manual check}
- **Time to detect (TTD):** {duration from start to detection}
- **Could we have detected it sooner?** {yes/no and how}

## Mitigation & Resolution

### Immediate mitigation
{What was done to stop the impact? (rollback, feature flag, scaling, etc.)}

### Root cause fix
{What was done to permanently fix the underlying issue?}

## Contributing Factors

{What conditions allowed this to happen? Think systemic, not individual.}

- {factor 1: e.g., missing integration test for this code path}
- {factor 2: e.g., no alerting on this specific error class}
- {factor 3: e.g., deploy happened outside normal hours without extra review}

## Lessons Learned

### What went well
- {thing that worked: e.g., alerting fired within 2 minutes}
- {thing that worked: e.g., runbook was accurate and up-to-date}

### What went poorly
- {thing that failed: e.g., took 30 min to identify the failing service}
- {thing that failed: e.g., no rollback automation}

### Where we got lucky
- {thing that could have been worse: e.g., happened during low-traffic hours}

## Action Items

| Priority | Action | Owner | Due Date | Ticket |
|----------|--------|-------|----------|--------|
| P0 | {critical fix} | {name} | {date} | {link} |
| P1 | {important improvement} | {name} | {date} | {link} |
| P2 | {nice-to-have improvement} | {name} | {date} | {link} |

## Appendix

### Related Links
- {monitoring dashboard}
- {relevant PR or commit}
- {Slack thread}
- {alert configuration}

### Raw Data
{Any relevant logs, graphs, or metrics snapshots}
  1. Pre-fill the timeline by:

    • Checking git log for recent deploys around the incident time
    • Looking for relevant error patterns in the codebase
    • Suggesting contributing factors based on code review
  2. Save the file to docs/postmortems/{YYYY-MM-DD}-{kebab-case-title}.md (create directory if needed).

Read the full file on GitHub · 118 lines

Changes

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.

  1. 3d ago First seen · 118 lines · 0 tokens per session scan A 6fd547b1284a

Subscribe to this mod's changes

postmortem is a command published in the GitHub repository kid-sid/claude-spellbook (187 stars, last pushed 27d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 971 tokens. 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.