PM Skills is a collection of plain-Markdown instructions that teach AI assistants structured methods for handling professional, personal, and life-admin tasks. People use it with Claude, ChatGPT, Gemini, Cursor, Codex, and other supported agents for work such as writing product requirements, reviewing documents, or planning difficult situations.
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/mohitagw15856/pm-claude-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/rules/mohitagw15856/pm-claude-skills/life-premortem)<a href="https://agentmods.dev/rules/mohitagw15856/pm-claude-skills/life-premortem"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/life-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/rules/mohitagw15856/pm-claude-skills/life-premortem"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/life-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 | $0.00121 | $0.01391 |
| Opus 5 | $0.00060 | $0.00696 |
| Sonnet 5 | $0.00024 | $0.00278 |
| Haiku 4.5 | $0.00012 | $0.00139 |
Grade A, and why
life-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 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Life Premortem Skill
Optimism is required to start big things and dangerous once you've started — because a mind committed to a plan goes blind to how it fails. The premortem flips that: instead of asking "what might go wrong?" (which the committed brain swats away), it says "it's a year from now and this failed — tell me the story of how." That small framing change unlocks honesty the forward-looking question can't. This skill runs it at life scale — the move abroad, the marriage, the career pivot, the sabbatical, the year's resolutions — turning a vivid failure story into a short list of real risks and the often-cheap things that would prevent them.
What This Skill Produces
- A failure narrative: a specific, vivid story told from one year (or the relevant horizon) in the future, in which the thing went wrong — concrete, not a risk list in disguise
- An extracted risk list: the real failure modes the story reveals, sorted by likelihood × how much they'd hurt
- Cheap preventatives: for each real risk, the small thing available now that would defuse it (most disasters have a five-dollar prevention that feels stupid to do and obvious in hindsight)
- Early-warning signs: the specific things that, if you notice them in month 3, mean the failure story is starting — so you can course-correct instead of discovering it at the end
Required Inputs
Ask for (if not already provided):
- The big thing being committed to, and the horizon that matters (a year? the end of the sabbatical? the first year of the marriage?)
- Why it matters and what "success" would look like — you can't fail a goal you haven't named
- What the user is quietly worried about but talking themselves out of (this is often the real risk, pre-rationalized away)
- What's reversible vs not, and what's already committed
Framework
- Tell the failure as a story, not a list. The magic is in the narrative frame: "It's a year later. The move to Lisbon fell apart. Walk me through how it went." A story recruits honesty and detail that "list your risks" never does — the committed brain will defend a plan but will happily narrate a hypothetical failure. Make it vivid and specific.
- Mine the story for the real risks. The narrative will surface failure modes the user actually believes in (the isolation, the money running out faster than planned, the relationship not surviving the stress) as opposed to the generic risks they'd list defensively. Extract those, rank by likelihood × pain.
- Find the stupidly-cheap preventative for each. Most real risks have a small, almost embarrassing prevention: the friend you'd have called before it got bad, the three-months-more savings, the conversation you'd have had, the trial run. The gap between the cheap prevention and the expensive failure is the whole ROI of this exercise.
- Name the early-warning signs. For each risk, the observable tell that the failure story is beginning — the month-3 signal (the loneliness that isn't lifting, the burn rate that's off, the resentment building). Catching the story early is how you rewrite it; the premortem hands you the alarms.
- Keep it a bet, not a veto. The premortem de-risks; it doesn't talk the user out of brave things. The output ends by weighing the (now-mitigated) risks against the reason for doing it — because the point is to go in clear-eyed, not to not go.
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 First seen · 114 lines · 121 tokens per session scan A a180add32ad1
life-premortem is a cursor rule published in the GitHub repository mohitagw15856/pm-claude-skills (1,352 stars, last pushed 3d ago), licensed MIT. It adds 121 tokens to every session and 1,391 once invoked, about $0.0006 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 2026-08-30.
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