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Get Started Free →Create a comprehensive product strategy using the 9-section Product Strategy Canvas — vision, segments, costs, value propositions, trade-offs, metrics, growth, capabilities, and defensibility. Use when building a product strategy, creating a strategic plan, or defining product direction.
.claude/skills/phuryn-product-strategy/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 5% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 20% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 76% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 62% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 57% | 0% |
You are an experienced product strategist developing a comprehensive product strategy for $ARGUMENTS.
Your task is to create a detailed Product Strategy Canvas that outlines how the product will compete, win, and grow in the market.
For each target segment:
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 35,170 | 35,620 | +1% | 1 | 1 | 0% | 5,428 | 6,994 | +29% | 0 | 0 | — |
case-02 | fail→pass | 36,722 | 40,918 | +11% | 1 | 1 | 0% | 6,166 | 6,480 | +5% | 0 | 0 | — |
case-03 | fail→pass | 40,159 | 34,877 | -13% | 1 | 1 | 0% | 5,861 | 7,023 | +20% | 0 | 0 | — |
case-04 | fail→pass | 21,538 | 31,864 | +48% | 1 | 1 | 0% | 3,519 | 6,182 | +76% | 0 | 0 | — |
case-05 | pass→pass | 26,463 | 28,049 | +6% | 1 | 1 | 0% | 3,659 | 5,621 | +54% | 0 | 0 | — |
case-06 | fail→pass | 21,704 | 32,670 | +51% | 1 | 1 | 0% | 3,573 | 5,785 | +62% | 0 | 0 | — |
case-07 | fail→pass | 22,492 | 23,542 | +5% | 1 | 1 | 0% | 3,871 | 6,082 | +57% | 0 | 0 | — |
case-08 | fail→pass | 36,248 | 29,792 | -18% | 1 | 1 | 0% | 4,661 | 4,578 | -2% | 0 | 0 | — |
case-09 | fail→pass | 23,450 | 33,360 | +42% | 1 | 1 | 0% | 4,033 | 5,694 | +41% | 0 | 0 | — |
case-10 | fail→pass | 29,168 | 30,548 | +5% | 1 | 1 | 0% | 3,650 | 6,224 | +71% | 0 | 0 | — |
case-11 | fail→pass | 21,463 | 22,594 | +5% | 1 | 1 | 0% | 3,263 | 4,982 | +53% | 0 | 0 | — |
case-12 | fail→fail | 20,886 | 24,762 | +19% | 1 | 1 | 0% | 3,370 | 5,085 | +51% | 0 | 0 | — |
case-13 | fail→pass | 18,162 | 30,364 | +67% | 1 | 1 | 0% | 3,037 | 6,183 | +104% | 0 | 0 | — |
case-14 | fail→pass | 19,184 | 24,685 | +29% | 1 | 1 | 0% | 3,198 | 4,940 | +54% | 0 | 0 | — |
case-15 | fail→pass | 26,401 | 36,743 | +39% | 1 | 1 | 0% | 4,406 | 6,330 | +44% | 0 | 0 | — |
case-16 | fail→pass | 23,329 | 28,155 | +21% | 1 | 1 | 0% | 3,080 | 5,709 | +85% | 0 | 0 | — |
case-17 | fail→pass | 23,580 | 37,328 | +58% | 1 | 1 | 0% | 3,994 | 6,801 | +70% | 0 | 0 | — |
case-18 | fail→pass | 18,481 | 23,375 | +26% | 1 | 1 | 0% | 2,881 | 5,095 | +77% | 0 | 0 | — |
case-19 | fail→pass | 27,021 | 29,734 | +10% | 1 | 1 | 0% | 4,218 | 5,912 | +40% | 0 | 0 | — |
case-20 | pass→pass | 24,623 | 29,420 | +19% | 1 | 1 | 0% | 4,099 | 5,259 | +28% | 0 | 0 | — |
case-21 | pass→pass | 14,070 | 10,754 | -24% | 1 | 1 | 0% | 1,754 | 2,814 | +60% | 0 | 0 | — |
case-22 | pass→pass | 14,075 | 16,820 | +20% | 1 | 1 | 0% | 3,004 | 4,607 | +53% | 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 +73 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.