Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Use when auditing slow page loads, heavy assets, or rendering delays related to Reduce DOM size and complexity. Verify the actual bottleneck in DevTools, Lighthouse, or field data before recommending changes.
.claude/skills/thedaviddias-dom-size/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-08 | ✗→✓ | ▲ Improved | -35% | 0% |
| case-18 | ✓→✓ | ＝ Same ✓ | -15% | 0% |
| case-19 | ✓→✓ | ＝ Same ✓ | -17% | 0% |
| case-01 | ✓→✓ | ＝ Same ✓ | -22% | 0% |
| case-02 | ✓→✓ | ＝ Same ✓ | -14% | 0% |
An excessive DOM size increases memory usage, slows down style calculations, and makes layout reflows more expensive, leading to poor interaction performance.
Check the total number of DOM nodes and the maximum DOM depth using Lighthouse or Chrome DevTools.
Simplify the HTML structure, remove unnecessary wrapper elements, and implement virtualization for large lists.
Explain the performance impact of a large DOM tree on memory and rendering speed.
Review the routes, assets, and loading behavior that affect Reduce DOM size and complexity. Flag exact files, requests, or rendering steps that add unnecessary network, CPU, or layout cost, and describe the measurement method used to confirm the issue.
For full implementation details, code examples, and framework-specific guidance, see references/rule.md.
Rule page: https://frontendchecklist.io/en/rules/performance/dom-size
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-18 | pass→pass | 14,405 | 9,735 | -32% | 1 | 1 | 0% | 2,561 | 2,165 | -15% | 0 | 0 | — |
case-19 | pass→pass | 9,179 | 6,906 | -25% | 1 | 1 | 0% | 1,790 | 1,477 | -17% | 0 | 0 | — |
case-01 | pass→pass | 22,767 | 8,298 | -64% | 1 | 1 | 0% | 2,279 | 1,780 | -22% | 0 | 0 | — |
case-02 | pass→pass | 13,140 | 8,384 | -36% | 1 | 1 | 0% | 2,161 | 1,868 | -14% | 0 | 0 | — |
case-03 | pass→pass | 11,609 | 12,177 | +5% | 1 | 1 | 0% | 2,033 | 2,528 | +24% | 0 | 0 | — |
case-04 | pass→pass | 15,811 | 11,259 | -29% | 1 | 1 | 0% | 2,809 | 2,557 | -9% | 0 | 0 | — |
case-05 | pass→pass | 10,736 | 6,302 | -41% | 1 | 1 | 0% | 1,889 | 1,410 | -25% | 0 | 0 | — |
case-06 | pass→pass | 17,670 | 11,720 | -34% | 1 | 1 | 0% | 2,691 | 2,508 | -7% | 0 | 0 | — |
case-07 | fail→fail | 16,847 | 17,512 | +4% | 1 | 1 | 0% | 2,841 | 3,400 | +20% | 0 | 0 | — |
case-08 | fail→pass | 10,952 | 5,426 | -50% | 1 | 1 | 0% | 1,900 | 1,244 | -35% | 0 | 0 | — |
case-20 | pass→pass | 11,999 | 8,082 | -33% | 1 | 1 | 0% | 2,374 | 1,946 | -18% | 0 | 0 | — |
case-09 | pass→pass | 10,972 | 7,650 | -30% | 1 | 1 | 0% | 2,047 | 1,825 | -11% | 0 | 0 | — |
case-10 | pass→pass | 13,145 | 8,040 | -39% | 1 | 1 | 0% | 2,228 | 1,590 | -29% | 0 | 0 | — |
case-11 | pass→pass | 12,786 | 12,265 | -4% | 1 | 1 | 0% | 2,248 | 2,563 | +14% | 0 | 0 | — |
case-12 | pass→pass | 12,643 | 6,812 | -46% | 1 | 1 | 0% | 2,002 | 1,313 | -34% | 0 | 0 | — |
case-13 | pass→pass | 7,611 | 3,873 | -49% | 1 | 1 | 0% | 1,013 | 838 | -17% | 0 | 0 | — |
case-14 | pass→pass | 11,674 | 9,185 | -21% | 1 | 1 | 0% | 2,013 | 1,939 | -4% | 0 | 0 | — |
case-15 | pass→pass | 3,987 | 3,015 | -24% | 1 | 1 | 0% | 687 | 778 | +13% | 0 | 0 | — |
case-16 | pass→pass | 9,481 | 5,716 | -40% | 1 | 1 | 0% | 1,786 | 1,326 | -26% | 0 | 0 | — |
case-17 | fail→fail | 17,104 | 14,462 | -15% | 1 | 1 | 0% | 2,982 | 3,094 | +4% | 0 | 0 | — |
case-21 | pass→pass | 16,906 | 11,425 | -32% | 1 | 1 | 0% | 2,875 | 2,755 | -4% | 0 | 0 | — |
case-22 | pass→pass | 13,239 | 9,880 | -25% | 1 | 1 | 0% | 2,490 | 1,998 | -20% | 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.
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.