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Use to stress-test predictions by assuming they failed and working backward to identify why.
Passed 18 of 22 test cases with the skill, and 8 of 22 without it.
and 10 more in the full report
10 fixed8 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
What two specific parameter thresholds define a risk as a 'tail risk' during systematic risk enumeration?
| Checked | Without skill | With skill |
|---|---|---|
| Defines tail risk probability threshold as under 5 percent. | Missed | Passed |
| Defines tail risk impact threshold as completely outcome-changing. | Missed | Passed |
The instructions your model reads when the skill loads.
A forecast pre-mortem is a stress-testing technique where you assume your prediction has already failed and work backward to construct the history of how it failed. This reveals blind spots, tail risks, and overconfidence.
Core Principle: Invert the problem. Don't ask "Will this succeed?" Ask "It has failed - why?"
Why It Matters:
Origin: Gary Klein's "premortem" technique, adapted for probabilistic forecasting
Use this skill when:
Do NOT use when:
test cases passed, vs 8 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.