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 Optimize first contentful paint. Verify the actual bottleneck in DevTools, Lighthouse, or field data before recommending changes.
.claude/skills/thedaviddias-first-contentful-paint/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -9% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 25% | 0% |
| case-04 | ✓→✗ | ▼ Worse | -6% | 0% |
| case-03 | ✓→✓ | ＝ Same ✓ | -15% | 0% |
| case-05 | ✓→✓ | ＝ Same ✓ | 9% | 0% |
FCP is the first visual signal that a page is loading—fast FCP reassures users that the site is responding, reducing perceived wait time and bounce rates.
Measure FCP using Lighthouse or PageSpeed Insights. Verify first content appears within 1.8 seconds.
Optimize FCP by eliminating render-blocking resources, inlining critical CSS, and reducing server response time.
Explain how FCP measures the time until the first text or image is painted, indicating page load has begun.
Review the routes, assets, and loading behavior that affect Optimize first contentful paint. 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/first-contentful-paint
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-03 | pass→pass | 15,381 | 10,875 | -29% | 1 | 1 | 0% | 2,896 | 2,467 | -15% | 0 | 0 | — |
case-01 | fail→pass | 18,822 | 13,747 | -27% | 1 | 1 | 0% | 3,367 | 3,059 | -9% | 0 | 0 | — |
case-02 | fail→fail | 15,274 | 13,361 | -13% | 1 | 1 | 0% | 2,759 | 2,843 | +3% | 0 | 0 | — |
case-04 | pass→fail | 15,260 | 9,954 | -35% | 1 | 1 | 0% | 2,788 | 2,627 | -6% | 0 | 0 | — |
case-05 | pass→pass | 11,151 | 12,899 | +16% | 1 | 1 | 0% | 2,503 | 2,740 | +9% | 0 | 0 | — |
case-06 | pass→pass | 7,985 | 4,528 | -43% | 1 | 1 | 0% | 1,492 | 1,163 | -22% | 0 | 0 | — |
case-07 | pass→pass | 14,575 | 11,415 | -22% | 1 | 1 | 0% | 2,507 | 2,497 | -0% | 0 | 0 | — |
case-08 | pass→pass | 10,911 | 8,127 | -26% | 1 | 1 | 0% | 1,929 | 1,683 | -13% | 0 | 0 | — |
case-09 | pass→pass | 10,790 | 8,520 | -21% | 1 | 1 | 0% | 1,910 | 1,752 | -8% | 0 | 0 | — |
case-10 | pass→pass | 12,917 | 10,351 | -20% | 1 | 1 | 0% | 2,095 | 1,971 | -6% | 0 | 0 | — |
case-11 | fail→pass | 18,225 | 19,780 | +9% | 1 | 1 | 0% | 2,791 | 3,495 | +25% | 0 | 0 | — |
case-12 | pass→pass | 11,460 | 9,613 | -16% | 1 | 1 | 0% | 1,774 | 2,048 | +15% | 0 | 0 | — |
case-13 | pass→pass | 11,737 | 8,227 | -30% | 1 | 1 | 0% | 1,944 | 1,729 | -11% | 0 | 0 | — |
case-14 | pass→pass | 12,757 | 9,826 | -23% | 1 | 1 | 0% | 2,060 | 1,771 | -14% | 0 | 0 | — |
case-15 | pass→pass | 10,726 | 9,874 | -8% | 1 | 1 | 0% | 2,004 | 2,066 | +3% | 0 | 0 | — |
case-16 | pass→pass | 16,545 | 13,095 | -21% | 1 | 1 | 0% | 2,666 | 2,410 | -10% | 0 | 0 | — |
case-17 | pass→pass | 12,080 | 7,947 | -34% | 1 | 1 | 0% | 2,038 | 1,633 | -20% | 0 | 0 | — |
case-18 | pass→pass | 12,359 | 7,329 | -41% | 1 | 1 | 0% | 2,088 | 2,011 | -4% | 0 | 0 | — |
case-19 | pass→pass | 9,053 | 6,041 | -33% | 1 | 1 | 0% | 1,851 | 1,531 | -17% | 0 | 0 | — |
case-20 | pass→pass | 11,270 | 6,495 | -42% | 1 | 1 | 0% | 1,841 | 1,439 | -22% | 0 | 0 | — |
case-21 | pass→pass | 11,616 | 9,905 | -15% | 1 | 1 | 0% | 1,951 | 1,572 | -19% | 0 | 0 | — |
case-22 | pass→pass | 15,099 | 11,679 | -23% | 1 | 1 | 0% | 2,388 | 2,240 | -6% | 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. 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.