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 stefanoskarakasis/Product-Marketing-Skills --skill pre-mortemgit clone --depth 1 https://github.com/stefanoskarakasis/Product-Marketing-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/skills/stefanoskarakasis/product-marketing-skills/pre-mortem)<a href="https://agentmods.dev/skills/stefanoskarakasis/product-marketing-skills/pre-mortem"><img src="https://agentmods.dev/badge/skills/stefanoskarakasis/product-marketing-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/skills/stefanoskarakasis/product-marketing-skills/pre-mortem"><img src="https://agentmods.dev/badge/skills/stefanoskarakasis/product-marketing-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 | $0.00072 | $0.03556 |
| Opus 5.5 | $0.00029 | $0.01422 |
| Sonnet 5.5 | $0.00014 | $0.00711 |
| Haiku 4.5 | $0.00007 | $0.00356 |
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 12d 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 — 342 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pre-Mortem — Skill
How This Works
A pre-mortem flips the question from "what could go wrong?" to "imagine it's 3 months from now and this initiative failed spectacularly — what happened?" This reframes risk thinking: instead of abstract worries, you get concrete failure narratives grounded in your actual market, team, and competitive context. Your job is to facilitate, not fear-monger.
The skill runs in 7 steps:
Step 0 — Load guardrails from /context/meta-patterns.md, if it exists (e.g., "pricing changes without competitive posture cost prior launches" — an example pattern shape) and surface them before intake.
Step 1 — Intake: Gather initiative name, scope, timeline, target customer, and announcement level. Brain-load ICP and positioning to ground discussion.
Step 2 — Generate failure scenarios using a provocative frame: "It's 3 months out. Revenue missed, team demoralized, customers churned. Why?"
Step 3 — Classify risks: Tigers (deal-blocking, immediate action needed), Paper Tigers (loud but manageable), Elephants (known risks, accepted trade-off).
Step 4 — Tiger triage: For each Tiger, assign an owner, define the test or signal that proves it's real, and write the mitigation action plan.
Step 5 — PMM recommendation: Is the go/no-go decision clear? If Tigers remain unmitigated, flag for leadership.
Step 6 — Output structure: Deliver a one-page Tiger summary + 2-3 page full risk table + action register.
Step 7 — Learning Close: log the session to /context/skill-sessions.md.
Trigger
- When: Any strategic initiative that needs cross-functional risk analysis before committing resources — a product launch, pricing change, GTM pivot, new market entry, or feature rollout.
- Not for: Post-launch diagnosis of what actually happened → use
retro. Stakeholder alignment planning → usestakeholder-maps. Prioritization or tier scoring → useprioritization-frameworksorgo-to-market-strategy. - Example prompts:
- "Run a pre-mortem on our Q3 pricing change"
- "What could go wrong with this launch?"
- "Stress-test our market entry plan before we commit"
- "I need a risk analysis before this goes to leadership"
- "Pressure-test this GTM pivot"
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago Changed · +3 lines · -10 tokens per session c0c45d60577d
- 20d ago Changed e572d5281091
- 25d ago Changed · +13 lines 16bb34f93c44
- 1mo ago Changed 6ea323d52366
- 1mo ago Changed · +2 lines f45e83d9da1d
- 2mo ago First seen · 324 lines · 82 tokens per session scan A 96e409e00e0c
pre-mortem is a skill published in the GitHub repository stefanoskarakasis/Product-Marketing-Skills (8 stars, last pushed 4d ago), licensed MIT. It adds 72 tokens to every session and 3,556 once invoked, about $0.0003 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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