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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skillsnpx agentmods add rules/mohitagw15856/pm-claude-skills/exit-waterfallWrote 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/exit-waterfall)<a href="https://agentmods.dev/rules/mohitagw15856/pm-claude-skills/exit-waterfall"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/exit-waterfall/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/exit-waterfall"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/exit-waterfall.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 | $0.00093 | $0.00903 |
| Opus 5 | $0.00046 | $0.00451 |
| Sonnet 5 | $0.00019 | $0.00181 |
| Haiku 4.5 | $0.00009 | $0.00090 |
Grade A, and why
exit-waterfall 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 7d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exit Waterfall Skill
A cap table is a promise about percentages; an exit waterfall is what actually happens to the money. The difference — liquidation preferences, participation, option strikes — routinely stuns founders at the worst possible moment. This skill computes the waterfall across exit prices and, more importantly, translates it: the price below which your shares are worth nothing, and the price where everyone finally converts.
What This Skill Produces
- The payout table — every stakeholder's dollars at each exit price, with conversion decisions shown
- The cliff points — where preferences stop dominating, where options come into the money
- The plain-English reading — "you need a $X exit for your common to mean anything" stated as a sentence
Required Inputs
Ask for these if not provided:
- Share classes — for each: name, share count, type (common / preferred / options); for preferred: amount invested, preference multiple, participating or not; for options: strike
- Exit prices to test — or default to a spread around the last round's valuation (label it as a default)
Programmatic Helper
The math ships as a deterministic script — run it rather than arithmetic-by-hand:
python3 scripts/exit_waterfall.py cap.json
python3 scripts/exit_waterfall.py cap.json --exit 50000000 --json
Input shape and worked example are in the script docstring. It brute-forces the conversion equilibrium (each non-participating preferred converts only when as-converted beats its preference) and applies the treasury method to options. Stated simplifications: preferences are pari passu (no seniority stacking) and participation is uncapped — flag both when the real cap table differs, and say the numbers shift accordingly.
Formula (readable form)
- Non-participating preferred takes max(preference, as-converted value) — preference = invested × multiple
- Participating preferred takes preference + pro-rata of the remainder (why "participating" is the term sheet word worth fighting)
- Options exercise only when per-share common value > strike; strike proceeds join the pool
- Remainder splits pro-rata among common + converted + participating shares
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.
- 7d ago First seen · 76 lines · 93 tokens per session scan A 9bacff812d51
exit-waterfall is a cursor rule published in the GitHub repository mohitagw15856/pm-claude-skills (1,352 stars, last pushed 3d ago), licensed MIT. It adds 93 tokens to every session and 903 once invoked, about $0.0005 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 2026-09-03.
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