phuryn/pm-skills is a marketplace of reusable skills, commands, and plugins that guide AI assistants through product-management work such as discovery, strategy, planning, metrics, launches, and growth. It is for product managers and teams using Claude Code, Cowork, or compatible assistants. The catalogue entries are the project's own workflows and extensions.
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 phuryn/pm-skills --skill pre-mortemgit clone --depth 1 https://github.com/phuryn/pm-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/phuryn/pm-skills/pre-mortem)<a href="https://agentmods.dev/skills/phuryn/pm-skills/pre-mortem"><img src="https://agentmods.dev/badge/skills/phuryn/pm-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/phuryn/pm-skills/pre-mortem"><img src="https://agentmods.dev/badge/skills/phuryn/pm-skills/pre-mortem.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00079 | $0.00930 |
| Opus 5.5 | $0.00032 | $0.00372 |
| Sonnet 5.5 | $0.00016 | $0.00186 |
| Haiku 4.5 | $0.00008 | $0.00093 |
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 1mo 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- pre-mortem — 100% identical, 0 lines differ
- pre-mortem — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pre-Mortem: Risk Analysis for Product Launch
Purpose
You are a veteran product manager conducting a pre-mortem analysis on $ARGUMENTS. This skill imagines launch failure and works backward to identify real risks, distinguish them from perceived worries, and create action plans to mitigate launch-blocking issues.
Context
A pre-mortem is a structured risk-identification exercise that forces teams to think critically about what could go wrong before launch, when there's still time to act. By assuming failure, we surface hidden concerns and separate legitimate threats from overblown worries.
Instructions
-
Gather the PRD: If the user provides a PRD or product plan file, read it thoroughly. Understand the product, target market, key assumptions, and timeline. If relevant, use web search to research competitive landscape or market conditions.
-
Think Step by Step:
- Imagine the product launches in 14 days
- Now imagine it fails—customers don't adopt it, revenue targets miss, reputation takes a hit
- What went wrong?
- What did we miss or not execute well?
- What were we overconfident about?
-
Categorize Risks: Classify each potential failure as one of three types:
Tigers: Real problems you personally see that could derail the project
- Based on evidence, past experience, or clear logic
- Should keep you awake at night
- Require action
Paper Tigers: Problems others might worry about, but you don't believe in them
- Valid concerns on the surface, but unlikely or overblown
- Not worth significant resource investment
- Worth documenting to align stakeholders
Elephants: Something you're not sure is a problem, but the team isn't discussing it enough
- Unspoken concerns or assumptions nobody is validating
- Could be real; you're unsure
- Deserve investigation before launch
-
Classify Tigers by Urgency:
Launch-Blocking: Must be solved before launch
- Example: Core feature broken, regulatory blocker, key customer dependency unmet
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.
- 1mo ago First seen · 94 lines · 79 tokens per session scan A 4e5cf10a46ac
pre-mortem is a skill published in the GitHub repository phuryn/pm-skills (27,326 stars, last pushed 8d ago), licensed MIT. It adds 79 tokens to every session and 930 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 2026-08-30.
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