Borrowing it
Nothing to install: this file belongs to heznpc/PLOIDY. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/heznpc/PLOIDY/main/.claude/commands/post-mortem.mdgit clone --depth 1 https://github.com/heznpc/PLOIDYWrote 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/commands/heznpc/ploidy/post-mortem)<a href="https://agentmods.dev/commands/heznpc/ploidy/post-mortem"><img src="https://agentmods.dev/badge/commands/heznpc/ploidy/post-mortem/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/commands/heznpc/ploidy/post-mortem"><img src="https://agentmods.dev/badge/commands/heznpc/ploidy/post-mortem.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 | $0.00043 | $0.00944 |
| Opus 5.5 | $0.00017 | $0.00378 |
| Sonnet 5.5 | $0.00009 | $0.00189 |
| Haiku 4.5 | $0.00004 | $0.00094 |
Grade A, and why
post-mortem 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 2mo 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The user wants a second pass on an incident analysis:
$ARGUMENTS
You hold the context: who was on-call, what the team already blamed, how similar incidents played out, which systems had prior issues. That context is how blame-anchoring creeps in — once "ah, it was the retry storm again" becomes the narrative, reviewers stop looking. Run the four-step pass without asking.
1 · Write the Deep-context take
If $ARGUMENTS is a path (ends in .md / contains /), read the
file first. Otherwise treat it as the incident summary.
In ~300 words:
- Proximate cause — the one-step-back trigger, stated plainly.
- Root causes (candidates) — list every plausible contributing factor. For each: technical / process / organisational.
- Blame anchoring check — list who or what in this incident the team is already converging on as responsible. For each, state whether the convergence is (a) backed by the timeline or (b) convenient because the target has a track record.
- Unasked questions — three questions the post-mortem has not asked but probably should.
Tag every candidate cause HIGH / MEDIUM / LOW confidence.
2 · Spawn a Fresh sub-agent
Use the Agent tool (subagent_type="general-purpose"). It must see
only the timeline of events, no names of teams, no history of prior
incidents.
Sanitise the input: strip team / person names, prior-incident references, and any "as usual / again / typical" phrases. Replace names with roles ("on-call engineer", "service owner"). Keep technical facts intact.
Prompt the subagent with:
You are reading the timeline of an incident in a system you have never seen. Only the sanitised timeline is available:
Answer in under 250 words:
- What is the most likely proximate cause, stated as one sentence?
- List every plausible root cause you can infer from the timeline alone. For each, say what the timeline would need to show to confirm or refute it.
- What information is missing from the timeline that, if present, would change your assessment?
- What recurring failure patterns in generic distributed systems does this timeline match (retry storm, thundering herd, partial deployment, clock skew, quota exhaustion, …)?
Do not ask for context. Do not guess at team / org details.
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.
- 2mo ago First seen · 108 lines · 43 tokens per session scan A a2d6c33ef27b
post-mortem is a command published in the GitHub repository heznpc/PLOIDY (0 stars, last pushed 2d ago), licensed MIT. It adds 43 tokens to every session and 944 once invoked, about $0.0002 per session on Opus 5.5. 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.
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