Data handling assessment across the AI processing pipeline, covering storage, retention, PII protection, and user control over third-party model data sharing.
20
Total Checks
3
Delivery Formats
3
Categories
4
Versions
Included
Never included
Quality hardening: added counting/enumeration, numeric thresholds, anti-sycophancy patterns, cross-references to all checks. Manifests tightened to exact tolerances.
Picked by pack overlap with this audit.
Safety assessment against prompt injection attacks, identifying vulnerabilities where untrusted user input might cause the AI to ignore instructions or exfiltrate data.
UI/UX quality assessment for AI chat interfaces, covering response streaming, loading states, error communication, conversation history, and input handling polish.
Quality and trustworthiness assessment of AI-generated responses, including output formatting, context grounding, and communication of uncertainty or knowledge gaps.
Token management and cost-efficiency patterns to prevent unexpected API bills, covering context growth, token limits, and efficient streaming and caching implementation.
AI-specific interaction conventions assessment covering regeneration controls, feedback mechanisms, and advanced patterns that distinguish polished AI interfaces from basic API wrappers.