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.
npx skills add woliveiras/geremmyas --skill premortemgit clone --depth 1 https://github.com/woliveiras/geremmyasWrote 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/skills/woliveiras/geremmyas/premortem)<a href="https://agentmods.dev/skills/woliveiras/geremmyas/premortem"><img src="https://agentmods.dev/badge/skills/woliveiras/geremmyas/premortem/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/skills/woliveiras/geremmyas/premortem"><img src="https://agentmods.dev/badge/skills/woliveiras/geremmyas/premortem.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 | $0.00061 | $0.00804 |
| Opus 5.5 | $0.00024 | $0.00322 |
| Sonnet 5.5 | $0.00012 | $0.00161 |
| Haiku 4.5 | $0.00006 | $0.00080 |
Grade A, and why
premortem 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Premortem
Assume the plan already failed 6 months from now. Work backward to find every reason why. Produce a revised plan with blind spots exposed.
Based on Gary Klein's prospective hindsight method. The frame shift from "what could go wrong?" to "this already failed, explain why" produces more specific and honest failure identification.
When to Use
- A product, feature, or architecture you're about to commit to
- A launch plan, pricing change, or strategy pivot
- Any decision where the cost of being wrong is high and you can still change course
When NOT to Use
- Vague ideas with no concrete plan (help them plan first)
- Decisions already made and irreversible
- Simple factual questions or routine code reviews
- Requests for creative feedback on a draft
Minimum Context Threshold
Before running the premortem, you need three things:
- What is it? — The thing being premortemed, describable in one sentence.
- Who is affected? — The audience, customer, team, or stakeholders.
- What does success look like? — The outcome the user hopes for.
Scan the conversation and workspace for existing context first. Only ask for what's genuinely missing. One question at a time, conversational, not a form.
Procedure
1. Set the frame
State the premise explicitly:
It's 6 months from now. [The plan] has failed. It's done. We're looking back to understand what went wrong.
This framing is the mechanism. Without it, analysis defaults to polite risk assessment.
2. Generate failure reasons
List every genuine reason the plan could have died. Each reason must be:
- Specific to this plan (not generic advice)
- Grounded in actual details provided
- A genuine threat (not a minor inconvenience or extremely unlikely edge case)
Find every real failure mode. Don't stop at 3 if there are 7. Don't pad to 7 if there are 3.
3. Synthesize
For each failure reason, state in 2-3 sentences: the underlying assumption it exploits and one early warning sign to watch for.
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 · 95 lines · 61 tokens per session scan A 9b2aa5017ae8
premortem is a skill published in the GitHub repository woliveiras/geremmyas (10 stars, last pushed 3mo ago), licensed MIT. It adds 61 tokens to every session and 804 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.
premortem compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| premortemwoliveiras/geremmyas | Skill | 10 | 3mo ago | MIT | A | 61 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |