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Get Started Free →Designs pricing strategies for products and services. Takes product/service, costs, target market, competitors. Analyzes cost-plus, value-based, competitor-based, penetration, premium models. Researches competitor pricing. Generates pricing-strategy.md with recommended model, price points, tier structure, discount policies, annual vs monthly analysis, sensitivity to churn, expansion revenue modeling.
.claude/skills/onewave-ai-pricing-strategy/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-12 | ✗→✓ | ▲ Improved | 39% | 0% |
| case-16 | ✗→✓ | ▲ Improved | 5% | 0% |
| case-19 | ✗→✓ | ▲ Improved | -32% | 0% |
| case-20 | ✗→✓ | ▲ Improved | -19% | 0% |
| case-21 | ✓→✗ | ▼ Worse | -29% | 0% |
Design data-driven pricing strategies that maximize revenue, align with market positioning, and scale with the business across B2B SaaS, consumer products, services, marketplaces, and physical goods.
references/required-inputs.md -- Inputs to gather before starting (product, market, competition, business context).references/analysis-framework.md -- The five pricing models to evaluate (cost-plus, value-based, competitor-based, penetration, premium).references/output-template.md -- Full pricing-strategy.md structure to populate.references/best-practices.md -- Best practices, trigger phrases, and a worked example.references/required-inputs.md. If anything is missing, ask before proceeding.references/analysis-framework.md. Do not skip a model; even when one is obviously wrong, explain why.pricing-strategy.md following references/output-template.md. Use real numbers from the research, not placeholders.For full best practices, trigger phrases, and a worked example, see references/best-practices.md.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-13 | fail→fail | 19,255 | 10,307 | -46% | 1 | 1 | 0% | 3,006 | 2,188 | -27% | 0 | 0 | — |
case-01 | fail→fail | 44,863 | 49,508 | +10% | 1 | 1 | 0% | 7,293 | 8,815 | +21% | 0 | 0 | — |
case-02 | fail→fail | 56,821 | 21,277 | -63% | 1 | 1 | 0% | 8,252 | 3,540 | -57% | 0 | 0 | — |
case-03 | fail→fail | 54,859 | 8,865 | -84% | 1 | 1 | 0% | 8,245 | 2,060 | -75% | 0 | 0 | — |
case-04 | pass→pass | 23,367 | 12,527 | -46% | 1 | 1 | 0% | 2,915 | 2,256 | -23% | 0 | 0 | — |
case-05 | pass→pass | 16,522 | 19,286 | +17% | 1 | 1 | 0% | 2,648 | 3,246 | +23% | 0 | 0 | — |
case-06 | pass→pass | 20,529 | 22,777 | +11% | 1 | 1 | 0% | 2,788 | 3,501 | +26% | 0 | 0 | — |
case-07 | pass→pass | 14,173 | 18,981 | +34% | 1 | 1 | 0% | 2,068 | 3,251 | +57% | 0 | 0 | — |
case-08 | pass→pass | 20,773 | 29,874 | +44% | 1 | 1 | 0% | 3,368 | 5,985 | +78% | 0 | 0 | — |
case-09 | pass→pass | 19,646 | 17,061 | -13% | 1 | 1 | 0% | 2,963 | 2,986 | +1% | 0 | 0 | — |
case-10 | pass→pass | 12,100 | 9,899 | -18% | 1 | 1 | 0% | 1,914 | 1,998 | +4% | 0 | 0 | — |
case-11 | pass→pass | 9,996 | 9,063 | -9% | 1 | 1 | 0% | 1,514 | 1,721 | +14% | 0 | 0 | — |
case-12 | fail→pass | 22,376 | 26,791 | +20% | 1 | 1 | 0% | 3,454 | 4,784 | +39% | 0 | 0 | — |
case-14 | pass→pass | 19,561 | 18,925 | -3% | 1 | 1 | 0% | 2,494 | 3,464 | +39% | 0 | 0 | — |
case-15 | pass→pass | 18,074 | 13,992 | -23% | 1 | 1 | 0% | 2,573 | 2,755 | +7% | 0 | 0 | — |
case-16 | fail→pass | 19,196 | 14,555 | -24% | 1 | 1 | 0% | 2,673 | 2,811 | +5% | 0 | 0 | — |
case-17 | pass→pass | 17,122 | 12,328 | -28% | 1 | 1 | 0% | 2,421 | 2,222 | -8% | 0 | 0 | — |
case-18 | fail→fail | 21,904 | 21,804 | -0% | 1 | 1 | 0% | 3,160 | 4,022 | +27% | 0 | 0 | — |
case-19 | fail→pass | 8,006 | 1,596 | -80% | 1 | 1 | 0% | 1,136 | 772 | -32% | 0 | 0 | — |
case-20 | fail→pass | 18,768 | 14,572 | -22% | 1 | 1 | 0% | 3,075 | 2,483 | -19% | 0 | 0 | — |
case-21 | pass→fail | 20,693 | 10,314 | -50% | 1 | 1 | 0% | 3,262 | 2,302 | -29% | 0 | 0 | — |
case-22 | pass→pass | 18,418 | 15,294 | -17% | 1 | 1 | 0% | 2,475 | 2,764 | +12% | 0 | 0 | — |
case-23 | pass→pass | 19,183 | 35,079 | +83% | 1 | 1 | 0% | 3,618 | 6,313 | +74% | 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. 23 cases were attempted. The headline lift of +13 percentage points is the difference between those two pass rates over the 23 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.