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Get Started Free →Custom training plans by goal (strength, cardio, flexibility). Progressive overload programming, rest day optimization, home vs gym adaptations, deload weeks.
.claude/skills/onewave-ai-workout-program-designer/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 0% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 48% | 0% |
| case-15 | ✗→✓ | ▲ Improved | 17% | 0% |
| case-16 | ✗→✓ | ▲ Improved | -28% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 30% | 0% |
Custom training plans by goal (strength, cardio, flexibility). Progressive overload programming, rest day optimization, home vs gym adaptations, deload weeks.
You are an expert fitness trainer and program designer. Create personalized workout programs with: goal-specific programming (strength/cardio/flexibility), progressive overload schedules, rest day optimization, equipment adaptations (home vs gym), deload week planning, injury prevention, and progress tracking metrics.
markdown# Workout Program Designer Output **Generated**: {timestamp} --- ## Results [Your formatted output here] --- ## Recommendations [Actionable next steps]
Trigger Phrases:
Example Request: > "Sample user request here]"
Response Approach:
Remember: Focus on delivering value quickly and clearly!
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-20 | pass→pass | 15,729 | 24,352 | +55% | 1 | 1 | 0% | 2,546 | 3,475 | +36% | 0 | 0 | — |
case-19 | pass→pass | 17,889 | 17,810 | -0% | 1 | 1 | 0% | 2,969 | 3,301 | +11% | 0 | 0 | — |
case-01 | fail→pass | 21,896 | 56,463 | +158% | 1 | 1 | 0% | 4,258 | 4,276 | +0% | 0 | 0 | — |
case-02 | fail→fail | 23,931 | 23,446 | -2% | 1 | 1 | 0% | 3,880 | 4,679 | +21% | 0 | 0 | — |
case-03 | pass→pass | 9,077 | 16,649 | +83% | 1 | 1 | 0% | 1,414 | 2,468 | +75% | 0 | 0 | — |
case-04 | fail→fail | 21,242 | 23,442 | +10% | 1 | 1 | 0% | 3,404 | 4,026 | +18% | 0 | 0 | — |
case-05 | pass→pass | 17,525 | 23,264 | +33% | 1 | 1 | 0% | 3,170 | 4,464 | +41% | 0 | 0 | — |
case-06 | fail→pass | 25,729 | 29,344 | +14% | 1 | 1 | 0% | 3,478 | 5,154 | +48% | 0 | 0 | — |
case-07 | pass→pass | 14,305 | 19,740 | +38% | 1 | 1 | 0% | 2,061 | 2,963 | +44% | 0 | 0 | — |
case-08 | pass→pass | 16,844 | 18,424 | +9% | 1 | 1 | 0% | 2,276 | 3,536 | +55% | 0 | 0 | — |
case-09 | pass→pass | 15,967 | 47,226 | +196% | 1 | 1 | 0% | 2,347 | 3,164 | +35% | 0 | 0 | — |
case-10 | pass→pass | 17,434 | 21,721 | +25% | 1 | 1 | 0% | 2,385 | 3,404 | +43% | 0 | 0 | — |
case-11 | pass→pass | 16,095 | 21,702 | +35% | 1 | 1 | 0% | 3,048 | 4,329 | +42% | 0 | 0 | — |
case-12 | pass→pass | 18,106 | 19,649 | +9% | 1 | 1 | 0% | 2,606 | 3,432 | +32% | 0 | 0 | — |
case-13 | pass→pass | 18,310 | 22,322 | +22% | 1 | 1 | 0% | 2,577 | 3,867 | +50% | 0 | 0 | — |
case-14 | pass→pass | 14,453 | 23,572 | +63% | 1 | 1 | 0% | 2,165 | 4,358 | +101% | 0 | 0 | — |
case-15 | fail→pass | 17,625 | 19,177 | +9% | 1 | 1 | 0% | 2,905 | 3,400 | +17% | 0 | 0 | — |
case-16 | fail→pass | 31,247 | 23,111 | -26% | 1 | 1 | 0% | 5,462 | 3,911 | -28% | 0 | 0 | — |
case-17 | fail→pass | 15,663 | 18,631 | +19% | 1 | 1 | 0% | 2,592 | 3,379 | +30% | 0 | 0 | — |
case-18 | pass→pass | 16,697 | 24,876 | +49% | 1 | 1 | 0% | 2,528 | 4,152 | +64% | 0 | 0 | — |
case-21 | pass→pass | 24,833 | 25,720 | +4% | 1 | 1 | 0% | 3,805 | 4,131 | +9% | 0 | 0 | — |
case-22 | pass→pass | 13,204 | 21,525 | +63% | 1 | 1 | 0% | 2,772 | 3,936 | +42% | 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. The headline lift of +23 percentage points is the difference between those two pass rates over the 22 comparable cases.
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.