tornado-sensitivity
Which assumption actually moves the answer — one-at-a-time sensitivity, ranked into a tornado. Use when a model's output is being argued about (LTV, ROI, forecast) and the room is debating drivers that don't matter, or before spending diligence effort: swing every driver low→high and see which one owns the outcome. Produces the ranked tornado table, share-of-swing per driver, and a real .xlsx — via the bundled zero-dependency script with a safely restricted formula evaluator.
npx skills add mohitagw15856/pm-claude-skills --skill tornado-sensitivity --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Tornado Sensitivity Every model has four drivers people argue about and one that actually controls the answer — usually not the same one. The tornado ranks them: hold everything at base, swing one driver to its low and high, measure the output range, sort. Diligence goes to the top bar; the bottom bars stop hijacking meetings. ## Required Inputs - **The model** — output name, a formula over named drivers (arithmetic + min/max/abs/sqrt/log/exp only), and per-driver low/base/high. The lows and highs should be *defensible bounds* ("the worst quarter we've seen", "the vendor's contractual ceiling"), not ±10% ritual. - If the requester has a spreadsheet instead of a formula: extract the output cell's driver chain into a formula first, and show it for confirmation. ## Output Format 1. **The tornado table** — drivers sorted by output swing, with input range, output at each end, and **share of total swing**. The top driver's share is the headline ("lifetime owns 33% of the uncertainty"). 2. **The meeting verdict** — one paragraph: what deserves diligence, what deserves a decision-and-move-on, and any driver whose *bounds* are the real problem (huge swing because nobody actually knows the
- Required Inputs
- Output Format
- Programmatic Helper
- Quality Checks
- Anti-Patterns
python3 scripts/tornado.py run tornado.xlsx --model model.json
What does the tornado-sensitivity skill do?
Which assumption actually moves the answer — one-at-a-time sensitivity, ranked into a tornado. Use when a model's output is being argued about (LTV, ROI, forecast) and the room is debating drivers that don't matter, or before spending diligence effort: swing every driver low→high and see which one owns the outcome. Produces the ranked tornado table, share-of-swing per driver, and a real .xlsx — via the bundled zero-dependency script with a safely restricted formula evaluator.
How do I install it?
Run `npx skills add mohitagw15856/pm-claude-skills --skill tornado-sensitivity --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.