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Get Started Free →Use when auditing slow page loads, heavy assets, or rendering delays related to Keep page load time under 3 seconds. Verify the actual bottleneck in DevTools, Lighthouse, or field data before recommending changes.
.claude/skills/thedaviddias-page-load-time/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -11% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 0% | 0% |
| case-08 | ✗→✓ | ▲ Improved | -14% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 44% | 0% |
| case-18 | ✗→✓ | ▲ Improved | -17% | 0% |
Studies show 53% of mobile users abandon sites that take longer than 3 seconds to load—slow pages directly hurt conversions, engagement, and SEO rankings.
Measure the page load time and verify it's under 3 seconds on a standard connection.
Optimize page load time through lazy loading, CDN usage, caching strategies, and resource optimization.
Explain how page load time affects bounce rate, SEO rankings, and user satisfaction.
Review the routes, assets, and loading behavior that affect Keep page load time under 3 seconds. 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/page-load-time
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 21,330 | 16,768 | -21% | 1 | 1 | 0% | 3,604 | 3,192 | -11% | 0 | 0 | — |
case-02 | fail→fail | 16,383 | 14,996 | -8% | 1 | 1 | 0% | 2,923 | 3,139 | +7% | 0 | 0 | — |
case-03 | pass→pass | 11,189 | 7,130 | -36% | 1 | 1 | 0% | 2,141 | 1,782 | -17% | 0 | 0 | — |
case-04 | fail→pass | 18,067 | 13,595 | -25% | 1 | 1 | 0% | 2,846 | 2,859 | +0% | 0 | 0 | — |
case-05 | pass→pass | 13,838 | 9,847 | -29% | 1 | 1 | 0% | 2,208 | 1,966 | -11% | 0 | 0 | — |
case-06 | pass→pass | 15,567 | 15,868 | +2% | 1 | 1 | 0% | 2,848 | 3,183 | +12% | 0 | 0 | — |
case-07 | pass→pass | 17,163 | 12,192 | -29% | 1 | 1 | 0% | 2,804 | 2,405 | -14% | 0 | 0 | — |
case-08 | fail→pass | 19,761 | 14,137 | -28% | 1 | 1 | 0% | 3,515 | 3,017 | -14% | 0 | 0 | — |
case-09 | pass→pass | 11,170 | 8,794 | -21% | 1 | 1 | 0% | 1,976 | 1,753 | -11% | 0 | 0 | — |
case-10 | fail→pass | 4,005 | 4,128 | +3% | 1 | 1 | 0% | 700 | 1,007 | +44% | 0 | 0 | — |
case-11 | pass→pass | 12,113 | 12,209 | +1% | 1 | 1 | 0% | 2,001 | 2,170 | +8% | 0 | 0 | — |
case-12 | pass→pass | 6,301 | 1,694 | -73% | 1 | 1 | 0% | 1,187 | 577 | -51% | 0 | 0 | — |
case-13 | pass→pass | 16,071 | 13,902 | -13% | 1 | 1 | 0% | 3,158 | 2,893 | -8% | 0 | 0 | — |
case-14 | pass→pass | 14,583 | 10,548 | -28% | 1 | 1 | 0% | 2,431 | 2,035 | -16% | 0 | 0 | — |
case-15 | pass→pass | 6,893 | 4,439 | -36% | 1 | 1 | 0% | 1,286 | 1,165 | -9% | 0 | 0 | — |
case-16 | pass→pass | 18,288 | 13,466 | -26% | 1 | 1 | 0% | 3,063 | 2,602 | -15% | 0 | 0 | — |
case-17 | pass→pass | 5,446 | 1,617 | -70% | 1 | 1 | 0% | 1,006 | 481 | -52% | 0 | 0 | — |
case-18 | fail→pass | 15,500 | 11,097 | -28% | 1 | 1 | 0% | 2,749 | 2,278 | -17% | 0 | 0 | — |
case-19 | pass→pass | 9,286 | 6,296 | -32% | 1 | 1 | 0% | 1,674 | 1,530 | -9% | 0 | 0 | — |
case-20 | pass→pass | 17,255 | 19,306 | +12% | 1 | 1 | 0% | 3,195 | 3,879 | +21% | 0 | 0 | — |
case-21 | pass→pass | 18,245 | 16,435 | -10% | 1 | 1 | 0% | 3,338 | 3,424 | +3% | 0 | 0 | — |
case-22 | pass→pass | 6,318 | 4,986 | -21% | 1 | 1 | 0% | 1,250 | 1,308 | +5% | 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 +23 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.