Evaluates structured data markup, data model quality, image handling, data freshness signals, and content completeness.
20
Total Checks
3
Delivery Formats
3
Categories
9
Versions
Quality hardening: enumeration language, numeric thresholds, cross-references, negative guardrails, measurement-on-pass, and quoting patterns across all 20 checks. Manifest tolerances tightened to exact.
2026-04-02
Added chunked format for browser-based tools
2026-03-01
Improved json-ld-valid check definition: explicitly documents that JSON-LD must be in script text content (not HTML data attributes like data-json/data-schema), adds the correct Next.js script injection pattern, and adds data-attribute-only storage as a fail criterion.
2026-03-01
Fixed severity_band_critical violation (51.3% > 50%): downgraded verification-timestamp from critical to high, downgraded opening-hours from high to low. Critical band now 43.5%, warning 47.8%, info 8.7%.
2026-03-01
Hardened curl commands with -sS -L flags for redirect following and error visibility. Added response validation guidance to Step 3.
2026-02-23
Fixed data-freshness checks_total (3→2), updated prompt_hash, URL canonicalization
2026-02-23
Fixed invalid prompt_hash — replaced placeholder/non-hex value with actual SHA-256 digest of prompt content
2026-02-23
Fixed severity band violations: downgraded image-optimization from critical to high; downgraded description-rendering, multi-value-arrays, closed-listing-handling from medium to low. Added missing opening-hours check to telemetry template.
2026-02-21
Initial release
2026-02-21
Copy the prompt in your preferred format above.
Paste into your AI coding tool (Claude Code, Cursor, Bolt, etc.).
Let the AI run all checks. Review the structured JSON output it produces.
Submit the JSON telemetry block to AuditBuffet for scoring and benchmarks.
Paste your JSON telemetry to get scores and benchmarks.
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