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.
git clone --depth 1 https://github.com/Amey-Thakur/AI-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/commands/amey-thakur/ai-skills/pre-mortem)<a href="https://agentmods.dev/commands/amey-thakur/ai-skills/pre-mortem"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/pre-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/amey-thakur/ai-skills/pre-mortem"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/pre-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 | $0.00024 | $0.00385 |
| Opus 5 | $0.00012 | $0.00192 |
| Sonnet 5 | $0.00005 | $0.00077 |
| Haiku 4.5 | $0.00002 | $0.00038 |
Grade A, and why
pre-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 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.
What it actually says
You were invoked as a slash command. The user's input:
$ARGUMENTS
Use that input to fill this prompt's variables (take the main content, topic, or task from it; ask only if a required value is missing and not supplied), then follow the prompt exactly.
Run a pre-mortem for: {project}
Context: {context}
The exercise: imagine it is some months from now and this project has FAILED, clearly and badly. Do not ask "what might go wrong" (that gets cautious, safe answers): assume failure as a fact and explain it.
- Tell the failure story: it is done, it failed. What happened? Write the most likely failure narrative concretely.
- List the causes: what led to that failure. Push for the uncomfortable ones, not just the obvious risks: the assumption that was wrong, the dependency that slipped, the thing everyone worried about but nobody said, the way people actually behave versus the plan.
- Rank the causes by likelihood and impact: which failures are both probable and damaging.
- For the top causes, give a concrete preventive action to take NOW, while there is still time, and an early warning sign that would show it starting.
Rules: the pre-mortem's power is that imagining a certain failure surfaces risks that "what could go wrong" politely hides (people voice concerns more freely about a fait accompli). Be specific and honest, including risks that implicate the plan or the people. Prioritize: not every risk is worth mitigating. End with the 2-3 highest-value preventive actions.
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.
- 3d ago First seen · 40 lines · 24 tokens per session scan A 33ba35897773
pre-mortem is a command published in the GitHub repository Amey-Thakur/AI-SKILLS (7 stars, last pushed 3d ago), licensed MIT. It adds 24 tokens to every session and 385 once invoked, about $0.0001 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 2026-09-06.
Other commands, from other repositories
close
They operate it without you.
burndown-full
Drive a partially-executed plan to 100% coverage across the whole repo — enumerate, batch-execute, prove completeness.
create-ticket
Create a work-item ticket (GitHub issue / Jira) from an existing requirements.md, then promote its draft spec folder to docs/specs/ /.
work-status
Report the current status of a work item by reading its spec files (requirements/design/tasks) and execution log. Read-only.
/opsx-apply
Implement tasks from an OpenSpec change (Experimental).
align
Align cross-functional stakeholders.