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Get Started Free →Optimize e-commerce product pages for search engine visibility. On-page SEO, structured data, page speed, mobile optimization, and content strategy for Google, Bing, and platform-specific search.
.claude/skills/nexscope-ai-product-page-seo/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -53% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -39% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 37% | 0% |
| case-18 | ✗→✓ | ▲ Improved | 32% | 0% |
| case-04 | ✓→✓ | ＝ Same ✓ | -2% | 0% |
Optimize e-commerce product pages for search engine visibility. On-page SEO, structured data, page speed, mobile optimization, and content strategy for Google, Bing, and platform-specific search.
Supported platforms: Amazon, Shopify, WooCommerce, Walmart, TikTok Shop, Etsy, eBay, BigCommerce.
Built by Nexscope — your AI assistant for smarter e-commerce decisions.
bashnpx skills add nexscope-ai/eCommerce-Skills --skill product-page-seo -g
Audit the SEO of my Shopify product page for a yoga mat. URL: [paste URL]. I'm getting zero organic traffic from Google.Step 1: Collect information from the user's message — product, platform, current situation, and goals.
Step 2: Ask one follow-up with all remaining questions using multiple-choice format. Allow shorthand answers (e.g., "1b 2c 3a").
Step 3: Research and analyze using the frameworks and methodology below.
Step 4: Deliver structured, actionable output with specific recommendations, not vague advice.
More e-commerce skills: nexscope-ai/eCommerce-Skills
Amazon-specific skills: nexscope-ai/Amazon-Skills
Built by Nexscope — your AI assistant for smarter e-commerce decisions.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-10 | fail→fail | 17,157 | 24,464 | +43% | 1 | 1 | 0% | 2,584 | 4,078 | +58% | 0 | 0 | — |
case-01 | fail→pass | 21,882 | 6,653 | -70% | 1 | 1 | 0% | 3,115 | 1,454 | -53% | 0 | 0 | — |
case-02 | fail→pass | 17,978 | 7,939 | -56% | 1 | 1 | 0% | 2,788 | 1,714 | -39% | 0 | 0 | — |
case-03 | fail→fail | 26,944 | 8,456 | -69% | 1 | 1 | 0% | 4,066 | 1,641 | -60% | 0 | 0 | — |
case-04 | pass→pass | 10,149 | 6,527 | -36% | 1 | 1 | 0% | 1,505 | 1,476 | -2% | 0 | 0 | — |
case-05 | pass→pass | 11,996 | 15,003 | +25% | 1 | 1 | 0% | 1,870 | 2,711 | +45% | 0 | 0 | — |
case-06 | pass→pass | 10,773 | 15,728 | +46% | 1 | 1 | 0% | 1,847 | 3,052 | +65% | 0 | 0 | — |
case-07 | pass→pass | 13,404 | 15,577 | +16% | 1 | 1 | 0% | 2,023 | 3,099 | +53% | 0 | 0 | — |
case-08 | pass→pass | 18,976 | 20,250 | +7% | 1 | 1 | 0% | 2,889 | 3,636 | +26% | 0 | 0 | — |
case-09 | fail→pass | 11,210 | 11,740 | +5% | 1 | 1 | 0% | 1,613 | 2,217 | +37% | 0 | 0 | — |
case-11 | pass→pass | 13,023 | 14,539 | +12% | 1 | 1 | 0% | 2,005 | 2,751 | +37% | 0 | 0 | — |
case-12 | pass→pass | 14,569 | 13,972 | -4% | 1 | 1 | 0% | 2,300 | 2,720 | +18% | 0 | 0 | — |
case-13 | pass→pass | 4,539 | 6,411 | +41% | 1 | 1 | 0% | 663 | 1,485 | +124% | 0 | 0 | — |
case-14 | pass→pass | 14,244 | 11,983 | -16% | 1 | 1 | 0% | 2,146 | 2,501 | +17% | 0 | 0 | — |
case-15 | pass→pass | 12,518 | 14,363 | +15% | 1 | 1 | 0% | 2,060 | 2,749 | +33% | 0 | 0 | — |
case-16 | pass→pass | 15,677 | 15,727 | +0% | 1 | 1 | 0% | 2,342 | 2,868 | +22% | 0 | 0 | — |
case-17 | pass→pass | 14,319 | 16,187 | +13% | 1 | 1 | 0% | 2,325 | 2,912 | +25% | 0 | 0 | — |
case-18 | fail→pass | 12,863 | 12,867 | +0% | 1 | 1 | 0% | 1,913 | 2,530 | +32% | 0 | 0 | — |
case-19 | pass→pass | 4,869 | 6,278 | +29% | 1 | 1 | 0% | 736 | 1,433 | +95% | 0 | 0 | — |
case-20 | pass→pass | 12,361 | 9,461 | -23% | 1 | 1 | 0% | 1,989 | 2,040 | +3% | 0 | 0 | — |
case-21 | pass→pass | 15,396 | 17,018 | +11% | 1 | 1 | 0% | 2,480 | 3,224 | +30% | 0 | 0 | — |
case-22 | pass→pass | 13,349 | 11,107 | -17% | 1 | 1 | 0% | 2,166 | 2,345 | +8% | 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 +18 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.