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Get Started Free →Use when reviewing stylesheets, component styles, and responsive behavior related to Use container queries for component-level responsiveness. Check the rendered layout across breakpoints and interaction states before proposing a fix.
.claude/skills/thedaviddias-container-queries/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-17 | ✗→✓ | ▲ Improved | 11% | 0% |
| case-09 | ✓→✗ | ▼ Worse | 26% | 0% |
| case-01 | ✓→✓ | ＝ Same ✓ | 28% | 0% |
| case-02 | ✓→✓ | ＝ Same ✓ | 24% | 0% |
| case-03 | ✓→✓ | ＝ Same ✓ | 4% | 0% |
Media queries respond to viewport width, which makes components context-dependent — a card designed for a 3-column grid might break when placed in a 2-column grid or a sidebar. Container queries solve this: a card can layout itself based on how much space its container gives it, making the component genuinely reusable in any layout context.
Look for components in this CSS that have media query breakpoints — consider whether container queries would make them more reusable in different layout contexts.
Convert this component from media query-based to container query-based responsiveness using container-type and @container.
Explain how container queries differ from media queries, why they enable better component reuse, and how to set up the container/query relationship.
Review stylesheets, component styles, and responsive states related to Use container queries for component-level responsiveness. Flag exact selectors, declarations, or breakpoints that violate the rule in the rendered UI.
For full implementation details, code examples, and framework-specific guidance, see references/rule.md.
Rule page: https://frontendchecklist.io/en/rules/css/container-queries
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | pass→pass | 4,737 | 5,150 | +9% | 1 | 1 | 0% | 1,112 | 1,419 | +28% | 0 | 0 | — |
case-02 | pass→pass | 7,332 | 7,379 | +1% | 1 | 1 | 0% | 1,511 | 1,870 | +24% | 0 | 0 | — |
case-03 | pass→pass | 9,133 | 8,119 | -11% | 1 | 1 | 0% | 1,766 | 1,834 | +4% | 0 | 0 | — |
case-04 | pass→pass | 6,454 | 7,567 | +17% | 1 | 1 | 0% | 1,393 | 1,773 | +27% | 0 | 0 | — |
case-05 | pass→pass | 5,065 | 5,732 | +13% | 1 | 1 | 0% | 1,204 | 1,651 | +37% | 0 | 0 | — |
case-06 | pass→pass | 12,157 | 8,337 | -31% | 1 | 1 | 0% | 2,449 | 1,988 | -19% | 0 | 0 | — |
case-07 | pass→pass | 9,994 | 4,859 | -51% | 1 | 1 | 0% | 1,810 | 1,524 | -16% | 0 | 0 | — |
case-08 | pass→pass | 6,959 | 5,112 | -27% | 1 | 1 | 0% | 1,562 | 1,439 | -8% | 0 | 0 | — |
case-09 | pass→fail | 8,684 | 9,268 | +7% | 1 | 1 | 0% | 1,761 | 2,212 | +26% | 0 | 0 | — |
case-10 | pass→pass | 8,612 | 8,145 | -5% | 1 | 1 | 0% | 1,771 | 1,995 | +13% | 0 | 0 | — |
case-11 | pass→pass | 7,841 | 7,825 | -0% | 1 | 1 | 0% | 1,622 | 2,050 | +26% | 0 | 0 | — |
case-12 | pass→pass | 6,625 | 7,193 | +9% | 1 | 1 | 0% | 1,509 | 1,703 | +13% | 0 | 0 | — |
case-13 | pass→pass | 10,563 | 6,921 | -34% | 1 | 1 | 0% | 2,191 | 1,815 | -17% | 0 | 0 | — |
case-14 | pass→pass | 4,587 | 3,569 | -22% | 1 | 1 | 0% | 812 | 921 | +13% | 0 | 0 | — |
case-15 | fail→fail | 7,103 | 6,194 | -13% | 1 | 1 | 0% | 1,435 | 1,878 | +31% | 0 | 0 | — |
case-16 | pass→pass | 5,361 | 3,553 | -34% | 1 | 1 | 0% | 1,039 | 1,134 | +9% | 0 | 0 | — |
case-17 | fail→pass | 6,056 | 4,915 | -19% | 1 | 1 | 0% | 1,211 | 1,341 | +11% | 0 | 0 | — |
case-18 | pass→pass | 9,502 | 8,037 | -15% | 1 | 1 | 0% | 2,529 | 2,449 | -3% | 0 | 0 | — |
case-19 | pass→pass | 7,296 | 7,091 | -3% | 1 | 1 | 0% | 1,802 | 1,852 | +3% | 0 | 0 | — |
case-20 | pass→pass | 11,828 | 10,713 | -9% | 1 | 1 | 0% | 2,667 | 2,679 | +0% | 0 | 0 | — |
case-21 | pass→pass | 3,609 | 3,498 | -3% | 1 | 1 | 0% | 680 | 969 | +43% | 0 | 0 | — |
case-22 | fail→fail | 7,002 | 6,212 | -11% | 1 | 1 | 0% | 1,612 | 1,493 | -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. 22 cases were attempted. The headline lift of 0 percentage points is the difference between those two pass rates over the 22 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.