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Get Started Free →Judge a past decision by its PROCESS, not its outcome — because good decisions lose and bad decisions win, and teams that can't tell the difference learn the wrong lessons. Use when reviewing a big call after the fact (a bet that failed, a pass that haunts, a hire, a pivot) and the room is about to conclude 'it failed so it was wrong.' Produces a process-forensics report: what was knowable then, the quality grade of the decision as-made, the luck accounting, and the ONE process change worth keep
.claude/skills/mohitagw15856-decision-autopsy/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-05 | ✗→✓ | ▲ Improved | 166% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 22% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 18% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 30% | 0% |
| case-18 | ✗→✓ | ▲ Improved | 23% | 0% |
Outcome bias is the strongest bias in organisational memory: the bet that failed becomes "obviously reckless," the coin-flip that landed becomes "visionary." The autopsy separates the two questions that always get merged: was it a good decision? and did it get a good outcome? — because only the first is under anyone's control next time.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | pass→pass | 14,387 | 13,008 | -10% | 1 | 1 | 0% | 2,484 | 3,227 | +30% | 0 | 0 | — |
case-02 | pass→pass | 10,597 | 77,531 | +632% | 1 | 1 | 0% | 1,953 | 3,600 | +84% | 0 | 0 | — |
case-12 | pass→pass | 16,111 | 10,257 | -36% | 1 | 1 | 0% | 2,225 | 2,381 | +7% | 0 | 0 | — |
case-03 | pass→pass | 12,916 | 20,481 | +59% | 1 | 1 | 0% | 2,085 | 2,818 | +35% | 0 | 0 | — |
case-04 | pass→pass | 17,323 | 12,217 | -29% | 1 | 1 | 0% | 2,889 | 2,554 | -12% | 0 | 0 | — |
case-05 | fail→pass | 39,276 | 14,642 | -63% | 1 | 1 | 0% | 1,248 | 3,315 | +166% | 0 | 0 | — |
case-06 | pass→fail | 14,508 | 14,555 | +0% | 1 | 1 | 0% | 2,298 | 2,884 | +26% | 0 | 0 | — |
case-07 | fail→pass | 14,950 | 13,370 | -11% | 1 | 1 | 0% | 2,376 | 2,889 | +22% | 0 | 0 | — |
case-08 | fail→pass | 18,038 | 15,351 | -15% | 1 | 1 | 0% | 2,596 | 3,064 | +18% | 0 | 0 | — |
case-09 | fail→pass | 14,191 | 11,775 | -17% | 1 | 1 | 0% | 2,030 | 2,649 | +30% | 0 | 0 | — |
case-10 | pass→pass | 14,143 | 13,195 | -7% | 1 | 1 | 0% | 2,009 | 2,589 | +29% | 0 | 0 | — |
case-11 | pass→pass | 18,544 | 11,413 | -38% | 1 | 1 | 0% | 2,723 | 2,588 | -5% | 0 | 0 | — |
case-13 | pass→pass | 20,250 | 10,884 | -46% | 1 | 1 | 0% | 2,076 | 2,336 | +13% | 0 | 0 | — |
case-14 | pass→pass | 12,157 | 12,445 | +2% | 1 | 1 | 0% | 1,990 | 2,672 | +34% | 0 | 0 | — |
case-15 | pass→pass | 11,868 | 10,429 | -12% | 1 | 1 | 0% | 1,968 | 2,591 | +32% | 0 | 0 | — |
case-16 | pass→pass | 11,157 | 11,130 | -0% | 1 | 1 | 0% | 1,724 | 2,355 | +37% | 0 | 0 | — |
case-17 | pass→pass | 16,995 | 12,261 | -28% | 1 | 1 | 0% | 2,597 | 2,791 | +7% | 0 | 0 | — |
case-18 | fail→pass | 14,492 | 10,666 | -26% | 1 | 1 | 0% | 2,059 | 2,536 | +23% | 0 | 0 | — |
case-19 | pass→pass | 16,309 | 9,579 | -41% | 1 | 1 | 0% | 2,606 | 2,093 | -20% | 0 | 0 | — |
case-20 | fail→pass | 13,181 | 12,766 | -3% | 1 | 1 | 0% | 2,181 | 2,866 | +31% | 0 | 0 | — |
case-21 | fail→pass | 14,420 | 14,388 | -0% | 1 | 1 | 0% | 2,171 | 2,856 | +32% | 0 | 0 | — |
case-22 | fail→pass | 8,482 | 12,791 | +51% | 1 | 1 | 0% | 1,248 | 2,784 | +123% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 21 counted toward the lift figure. The other 1 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +32 percentage points is the difference between those two pass rates over the 21 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.