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One-at-a-time assumption perturbation — extract assumptions, define negations, re-derive conclusions under each negation, measure sensitivity. Identifies which assumptions are load-bearing.
Passed 17 of 21 test cases with the skill, and 10 of 21 without it.
and 6 more in the full report
8 fixed10 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
In evaluating a published epidemiological model predicting outbreak peaks, the authors assume uniform population mixing across all demographic groups. Perform an assumption perturbation analysis on this claim.
| Checked | Without skill | With skill |
|---|---|---|
| The response negates the uniform mixing assumption by specifying a realistic heterogeneous structured network alternative rather than simple non-uniformity. | Passed | Passed |
| The response tracks where the mathematical outbreak peak re-derivation diverges from the baseline. | Missed | Passed |
The instructions your model reads when the skill loads.
Systematically perturb assumptions to identify which are load-bearing.
assumption-extraction → negation-definition → re-derivation → conclusion-sensitivity-measurement
Subagent: assumption-extraction, negation-definition, re-derivation, conclusion-sensitivity-measurement Shared: assumption-surfacing Import: paper-research
Extract all assumptions (use shared SOP for initial surfacing), define weakest plausible alternative for each, re-derive the conclusion under each alternative, measure change magnitude and direction. Rank by sensitivity.
Key principle: negation is not logical NOT — it is the strongest plausible alternative. "Data is normally distributed" negates to "data follows a heavy-tailed distribution" not "data is not normally distributed."
<HARD-GATE>
- Assumptions extracted: >= 5
- Negations defined: >= 5
- Re-derivations completed: >= 4
- Sensitivity rankings produced: >= 1 complete ranking
</HARD-GATE>
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| conclusion-sensitivity-measurement | Quantify how much conclusions change across all assumption negations and produce a sensitivity ranking. |
test cases passed, vs 10 / 21 without
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