Quality and trustworthiness assessment of AI-generated responses, including output formatting, context grounding, and communication of uncertainty or knowledge gaps.
20
Total Checks
3
Delivery Formats
3
Categories
4
Versions
Included
Never included
Anti-sycophancy hardening: added enumeration requirements, quoting directives, negative guardrails, measurement-on-pass reporting, and cross-references. Added test infrastructure (golden + bare-minimum fixtures and manifests).
Picked by pack overlap with this audit.
UI/UX quality assessment for AI chat interfaces, covering response streaming, loading states, error communication, conversation history, and input handling polish.
Data handling assessment across the AI processing pipeline, covering storage, retention, PII protection, and user control over third-party model data sharing.
Safety assessment against prompt injection attacks, identifying vulnerabilities where untrusted user input might cause the AI to ignore instructions or exfiltrate data.
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.
Submit Results