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Get Started Free →Use when auditing robots meta tags. Applies to any important landing page, article, or product page that should appear with a description in search results.
.claude/skills/thedaviddias-nosnippet/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-15 | ✗→✓ | ▲ Improved | -35% | 0% |
| case-01 | ✓→✓ | ＝ Same ✓ | -8% | 0% |
| case-02 | ✓→✓ | ＝ Same ✓ | 1% | 0% |
| case-03 | ✓→✓ | ＝ Same ✓ | 1% | 0% |
| case-04 | ✓→✓ | ＝ Same ✓ | 5% | 0% |
Pages with nosnippet display without a description in search results, reducing click-through rates and making it harder for users to understand whether the result is relevant to their query.
Check the <meta name='robots'> tag and X-Robots-Tag response header for each important page. Flag any that contain 'nosnippet' or 'max-snippet:0'. Confirm these pages intentionally suppress snippets.
Remove 'nosnippet' from the <meta name='robots'> content attribute on important pages. Replace with 'max-snippet:-1' to explicitly allow full-length snippets, or simply omit snippet directives to use the default (allowed).
The nosnippet directive tells Google not to display a text snippet (description) for your page in search results. Without a snippet, users see only the page title and URL—this reduces click-through rates and is rarely the intended behaviour for content pages.
Check all pages for <meta name='robots' content='...'> tags. Parse the content value and flag any that include 'nosnippet' or 'max-snippet:0'. Generate a report of affected URLs, their page type, and whether the nosnippet directive is intentional. Also check X-Robots-Tag response headers.
For full implementation details, code examples, and framework-specific guidance, see references/rule.md.
Rule page: https://frontendchecklist.io/en/rules/seo/nosnippet
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | pass→pass | 6,221 | 3,530 | -43% | 1 | 1 | 0% | 1,145 | 1,050 | -8% | 0 | 0 | — |
case-02 | pass→pass | 11,102 | 8,260 | -26% | 1 | 1 | 0% | 1,856 | 1,866 | +1% | 0 | 0 | — |
case-03 | pass→pass | 8,373 | 6,519 | -22% | 1 | 1 | 0% | 1,654 | 1,671 | +1% | 0 | 0 | — |
case-04 | pass→pass | 4,067 | 2,186 | -46% | 1 | 1 | 0% | 748 | 787 | +5% | 0 | 0 | — |
case-05 | pass→pass | 11,313 | 6,517 | -42% | 1 | 1 | 0% | 1,804 | 1,473 | -18% | 0 | 0 | — |
case-06 | pass→pass | 9,598 | 7,082 | -26% | 1 | 1 | 0% | 1,603 | 1,563 | -2% | 0 | 0 | — |
case-07 | pass→pass | 7,799 | 5,117 | -34% | 1 | 1 | 0% | 1,481 | 1,523 | +3% | 0 | 0 | — |
case-08 | pass→pass | 6,131 | 3,903 | -36% | 1 | 1 | 0% | 1,058 | 1,069 | +1% | 0 | 0 | — |
case-09 | pass→pass | 13,656 | 7,033 | -48% | 1 | 1 | 0% | 2,279 | 1,577 | -31% | 0 | 0 | — |
case-10 | pass→pass | 8,047 | 5,813 | -28% | 1 | 1 | 0% | 1,582 | 1,625 | +3% | 0 | 0 | — |
case-11 | pass→pass | 8,989 | 5,804 | -35% | 1 | 1 | 0% | 1,563 | 1,374 | -12% | 0 | 0 | — |
case-12 | pass→pass | 3,375 | 2,301 | -32% | 1 | 1 | 0% | 554 | 774 | +40% | 0 | 0 | — |
case-13 | pass→pass | 5,322 | 3,216 | -40% | 1 | 1 | 0% | 965 | 847 | -12% | 0 | 0 | — |
case-14 | pass→pass | 4,609 | 3,098 | -33% | 1 | 1 | 0% | 886 | 963 | +9% | 0 | 0 | — |
case-15 | fail→pass | 14,542 | 5,973 | -59% | 1 | 1 | 0% | 2,432 | 1,580 | -35% | 0 | 0 | — |
case-16 | pass→pass | 2,538 | 2,579 | +2% | 1 | 1 | 0% | 435 | 842 | +94% | 0 | 0 | — |
case-17 | pass→pass | 5,708 | 2,932 | -49% | 1 | 1 | 0% | 1,018 | 986 | -3% | 0 | 0 | — |
case-18 | pass→pass | 10,623 | 9,083 | -14% | 1 | 1 | 0% | 1,798 | 2,103 | +17% | 0 | 0 | — |
case-19 | pass→pass | 6,792 | 4,382 | -35% | 1 | 1 | 0% | 1,263 | 1,147 | -9% | 0 | 0 | — |
case-20 | pass→pass | 7,317 | 5,362 | -27% | 1 | 1 | 0% | 1,460 | 1,342 | -8% | 0 | 0 | — |
case-21 | pass→pass | 6,875 | 3,606 | -48% | 1 | 1 | 0% | 1,234 | 1,082 | -12% | 0 | 0 | — |
case-22 | fail→fail | 7,643 | 5,058 | -34% | 1 | 1 | 0% | 1,325 | 1,223 | -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 +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.