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Get Started Free →Generate several genuinely different throwaway variations (designs, approaches, drafts) for the user to react to. Use when the user can only recognize what they want by seeing it — visual design, UX flows, naming, tone — or asks to brainstorm or prototype before building.
.claude/skills/neeeophytee-brainstorm-prototypes/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | -21% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 84% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 181% | 0% |
| case-14 | ✗→✓ | ▲ Improved | -36% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 128% | 0% |
The user has unknown knowns: criteria they can't verbalize but will recognize on sight. Finding those during prototyping is cheap; finding them mid-implementation is expensive, because small spec changes can mean drastically different code. Give them things to react to.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 20,255 | 24,252 | +20% | 1 | 1 | 0% | 2,937 | 2,588 | -12% | 0 | 0 | — |
case-02 | fail→pass | 31,602 | 23,551 | -25% | 1 | 1 | 0% | 6,219 | 4,922 | -21% | 0 | 0 | — |
case-03 | pass→fail | 22,634 | 15,980 | -29% | 1 | 1 | 0% | 3,937 | 2,612 | -34% | 0 | 0 | — |
case-04 | fail→fail | 7,410 | 10,786 | +46% | 1 | 1 | 0% | 1,296 | 2,033 | +57% | 0 | 0 | — |
case-05 | pass→fail | 7,145 | 9,966 | +39% | 1 | 1 | 0% | 1,181 | 1,872 | +59% | 0 | 0 | — |
case-06 | fail→pass | 16,173 | 22,696 | +40% | 1 | 1 | 0% | 2,549 | 4,698 | +84% | 0 | 0 | — |
case-07 | pass→pass | 17,284 | 14,445 | -16% | 1 | 1 | 0% | 3,113 | 2,517 | -19% | 0 | 0 | — |
case-08 | fail→fail | 28,384 | 30,738 | +8% | 1 | 1 | 0% | 6,177 | 6,548 | +6% | 0 | 0 | — |
case-09 | pass→pass | 16,408 | 13,341 | -19% | 1 | 1 | 0% | 2,378 | 2,335 | -2% | 0 | 0 | — |
case-10 | fail→pass | 13,110 | 24,343 | +86% | 1 | 1 | 0% | 1,815 | 5,096 | +181% | 0 | 0 | — |
case-11 | fail→fail | 9,880 | 6,878 | -30% | 1 | 1 | 0% | 1,446 | 1,286 | -11% | 0 | 0 | — |
case-12 | fail→fail | 16,023 | 16,782 | +5% | 1 | 1 | 0% | 2,851 | 2,935 | +3% | 0 | 0 | — |
case-13 | pass→pass | 16,755 | 11,289 | -33% | 1 | 1 | 0% | 2,347 | 2,008 | -14% | 0 | 0 | — |
case-14 | fail→pass | 11,056 | 5,096 | -54% | 1 | 1 | 0% | 1,730 | 1,104 | -36% | 0 | 0 | — |
case-15 | fail→fail | 28,188 | 26,621 | -6% | 1 | 1 | 0% | 6,165 | 5,797 | -6% | 0 | 0 | — |
case-16 | pass→pass | 16,236 | 11,262 | -31% | 1 | 1 | 0% | 2,567 | 1,958 | -24% | 0 | 0 | — |
case-17 | fail→pass | 15,798 | 26,512 | +68% | 1 | 1 | 0% | 2,409 | 5,488 | +128% | 0 | 0 | — |
case-18 | fail→pass | 12,270 | 13,763 | +12% | 1 | 1 | 0% | 1,949 | 2,417 | +24% | 0 | 0 | — |
case-19 | pass→pass | 15,497 | 13,083 | -16% | 1 | 1 | 0% | 2,354 | 2,376 | +1% | 0 | 0 | — |
case-20 | fail→pass | 15,920 | 26,587 | +67% | 1 | 1 | 0% | 3,084 | 6,271 | +103% | 0 | 0 | — |
case-21 | fail→fail | 22,625 | 23,936 | +6% | 1 | 1 | 0% | 5,187 | 5,533 | +7% | 0 | 0 | — |
case-22 | fail→pass | 5,624 | 4,787 | -15% | 1 | 1 | 0% | 791 | 1,070 | +35% | 0 | 0 | — |
case-23 | fail→fail | 15,649 | 10,978 | -30% | 1 | 1 | 0% | 2,504 | 2,016 | -19% | 0 | 0 | — |
case-24 | fail→pass | 11,661 | 20,739 | +78% | 1 | 1 | 0% | 1,920 | 4,363 | +127% | 0 | 0 | — |
case-25 | fail→pass | 12,166 | 9,312 | -23% | 1 | 1 | 0% | 1,934 | 1,807 | -7% | 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. 25 cases were attempted. The headline lift of +32 percentage points is the difference between those two pass rates over the 25 comparable cases. 3 cases got worse with the skill loaded, and they are 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.