A blameless report about a service failure or other incident, explaining what happened, why it happened, and how to prevent it happening again.

Use it to build an evidence-based timeline, analyze contributing factors, and define preventive actions after an incident.

It focuses on weaknesses in systems and processes instead of blaming individuals, while keeping follow-up work suited to the affected system's deployment level.

postmortem — Skill for Claude Code and Codex by MotWakorb: A blameless report about a service failure or other…

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 skills/motwakorb/ai-agent-dev-team/postmortem

Any agent

npx skills add MotWakorb/ai-agent-dev-team --skill postmortem

Clone the repo

git clone --depth 1 https://github.com/MotWakorb/ai-agent-dev-team

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/motwakorb/ai-agent-dev-team/postmortem.svg)](https://agentmods.dev/skills/motwakorb/ai-agent-dev-team/postmortem)

Your own site

<a href="https://agentmods.dev/skills/motwakorb/ai-agent-dev-team/postmortem"><img src="https://agentmods.dev/badge/skills/motwakorb/ai-agent-dev-team/postmortem.svg" alt="Measured on agentmods" height="20"></a>

Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,961 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.

Model	Per session	Once invoked
Fable 5	$0.00048	$0.02961
Opus 5	$0.00024	$0.01481
Sonnet 5	$0.00010	$0.00592
Haiku 4.5	$0.00005	$0.00296

Measured 4d ago against content hash d56fe8cede61, 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 4d 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.

postmortem/SKILL.md · 265 lines

How it starts

The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Incident Postmortem

Blameless. The question is "what failed?" not "who failed?" If a human error caused the incident, the system that allowed the human error is the root cause. We fix systems, not blame people.

Preflight: Verify Onboarding & Effective Tier

Before any other step, verify deployment-tier setup. Action items from a postmortem should match the affected component's tier — recommending on-call rotations and chaos game days for a home-lab service is not a useful follow-up.

Check COMPONENTS.md exists at the repo root. If missing, refuse to run and tell the PO:

This project hasn't been onboarded yet. Run /onboard first — it produces COMPONENTS.md, which records each component's deployment tier. Postmortem action items need to match component tiers. See _shared/deployment-tier.md for the tier model.

Do not proceed.
Identify the affected component(s) from the incident.
Look up tiers in COMPONENTS.md. If the affected component is missing, ask the PO to add it (with reasoning) before proceeding.
Resolve cross-tier impact using strictest-wins by default — if the incident affected a startup-tier component, action items align to startup-tier even if the failure originated in a home-lab dependency.

Inject tier context into every agent prompt. Every prompt below must additionally include:

Read ~/.claude/skills/_shared/deployment-tier.md.
Affected components and tiers: [component] ([tier]), ...
Effective tier for action items: [tier]
Generate action items at the effective tier. Do not recommend enterprise practices (on-call rotations, formal chaos schedules, audit logging) on home-lab components unless the postmortem itself shows the home-lab framing was the root cause.

Model Selection

When spawning agents, pass model: explicitly per _shared/orchestration.md (Agent Model Selection). For this skill:

Fact-gathering and timeline construction: sonnet
Root cause analysis (SRE + relevant personas): opus — getting the root cause right matters more than getting it cheap

Read the full file on GitHub · 265 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.

4d ago First seen · 265 lines · 48 tokens per session scan A d56fe8cede61

Subscribe to this mod's changes

postmortem is a skill published in the GitHub repository MotWakorb/ai-agent-dev-team (2 stars, last pushed 22d ago), licensed MIT. It adds 48 tokens to every session and 2,961 once invoked, about $0.0002 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.

Debugging

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens