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Get Started Free →Apply Jakob's Law — users expect your product to work like the others they already use. Use when deciding whether to innovate on a familiar pattern. For OS-mandated conventions specifically, use `platform-conventions` (ui-design).
.claude/skills/owl-listener-jakobs-law/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 41% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 12% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 36% | 0% |
| case-15 | ✓→✗ | ▼ Worse | 44% | 0% |
| case-22 | ✓→✗ | ▼ Worse | 50% | 0% |
You are an expert in mental models, user expectations, and the role of convention in interface design.
You apply Jakob's Law to identify which design conventions carry strong user expectations, evaluate the cost of departing from them, and make deliberate decisions about when to follow and when to innovate.
Users spend most of their time on other products. They arrive at yours with pre-built expectations about where navigation lives, what a cart icon means, how a toggle behaves, and where to look for settings. Jakob's Law, articulated by Jakob Nielsen, states:
Users prefer your site to work the same way as all the other sites they already know.
This is not an argument for copying competitors. It is an argument for understanding which conventions carry strong enough expectations that departing from them imposes a real learning cost — and being deliberate when you do.
Some patterns are so universal that users rely on them unconsciously:
Every time you deviate, users must:
This cost is paid on every visit until the pattern is learned — which requires repetition and motivation. The benefit of the new approach must outweigh this cumulative cost across your entire user base.
Departure from convention is justified when:
Departure is not justified by:
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 15,731 | 19,856 | +26% | 1 | 1 | 0% | 2,301 | 3,236 | +41% | 0 | 0 | — |
case-02 | pass→pass | 15,844 | 14,110 | -11% | 1 | 1 | 0% | 2,349 | 2,670 | +14% | 0 | 0 | — |
case-03 | pass→pass | 13,348 | 14,614 | +9% | 1 | 1 | 0% | 2,036 | 2,887 | +42% | 0 | 0 | — |
case-04 | pass→pass | 13,126 | 13,973 | +6% | 1 | 1 | 0% | 2,032 | 2,763 | +36% | 0 | 0 | — |
case-05 | pass→pass | 15,150 | 13,673 | -10% | 1 | 1 | 0% | 2,333 | 2,588 | +11% | 0 | 0 | — |
case-06 | pass→pass | 16,479 | 15,597 | -5% | 1 | 1 | 0% | 2,358 | 2,963 | +26% | 0 | 0 | — |
case-07 | pass→pass | 17,548 | 15,535 | -11% | 1 | 1 | 0% | 2,688 | 3,051 | +14% | 0 | 0 | — |
case-08 | pass→pass | 15,131 | 13,964 | -8% | 1 | 1 | 0% | 2,182 | 2,739 | +26% | 0 | 0 | — |
case-09 | fail→pass | 12,917 | 10,352 | -20% | 1 | 1 | 0% | 2,039 | 2,275 | +12% | 0 | 0 | — |
case-10 | fail→fail | 11,039 | 21,090 | +91% | 1 | 1 | 0% | 1,636 | 3,659 | +124% | 0 | 0 | — |
case-11 | pass→pass | 16,266 | 16,891 | +4% | 1 | 1 | 0% | 2,376 | 2,820 | +19% | 0 | 0 | — |
case-12 | fail→pass | 11,971 | 12,093 | +1% | 1 | 1 | 0% | 1,815 | 2,460 | +36% | 0 | 0 | — |
case-13 | pass→pass | 15,188 | 15,575 | +3% | 1 | 1 | 0% | 2,178 | 2,920 | +34% | 0 | 0 | — |
case-14 | pass→pass | 11,806 | 10,349 | -12% | 1 | 1 | 0% | 1,684 | 2,221 | +32% | 0 | 0 | — |
case-15 | pass→fail | 15,366 | 16,954 | +10% | 1 | 1 | 0% | 2,197 | 3,174 | +44% | 0 | 0 | — |
case-16 | fail→fail | 16,831 | 19,396 | +15% | 1 | 1 | 0% | 2,507 | 3,433 | +37% | 0 | 0 | — |
case-17 | pass→pass | 13,868 | 12,859 | -7% | 1 | 1 | 0% | 2,080 | 2,548 | +23% | 0 | 0 | — |
case-18 | fail→fail | 11,149 | 10,409 | -7% | 1 | 1 | 0% | 1,620 | 2,218 | +37% | 0 | 0 | — |
case-19 | pass→pass | 15,087 | 14,135 | -6% | 1 | 1 | 0% | 2,141 | 2,643 | +23% | 0 | 0 | — |
case-20 | pass→pass | 5,014 | 5,275 | +5% | 1 | 1 | 0% | 852 | 1,555 | +83% | 0 | 0 | — |
case-21 | fail→fail | 16,910 | 13,520 | -20% | 1 | 1 | 0% | 2,745 | 2,910 | +6% | 0 | 0 | — |
case-22 | pass→fail | 9,302 | 10,185 | +9% | 1 | 1 | 0% | 1,438 | 2,158 | +50% | 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 +5 percentage points is the difference between those two pass rates over the 22 comparable cases. 2 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.