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An immersive digital art gallery server with AI-powered virtual docent guidance, interactive canvas exploration, and curated masterpiece tours
Two tools with partial schemas and descriptions. health_check has a minimal description (67 chars) and no explicit input schema. chat has a detailed input schema but lacks output schema documentation and error handling guidance. Neither tool has descriptions meeting the 50-200 char LLM-optimized baseline. No parameter descriptions for chat's nested objects (e.g., what does 'role' accept? what are valid values for 'period'?). No error recovery guidance. Missing tool annotations (readOnlyHint, idempotentHint). Composition is reasonable (two distinct concerns), but schema completeness and description quality are below production baseline.
Chat endpoint that provides AI-powered docent responses about artwork, with support for coordinate-based queries and contextual artwork information
API Health Check endpoint that returns server status and AI configuration state
chat tool lacks documented output schema. LLMs cannot plan downstream calls or extract fields without knowing response structure.
Nested parameters in chat (currentArtwork.focalPoints[].properties) lack descriptions. LLMs cannot infer what 'zoom' means, valid range for 'x'/'y' (0-100?), or whether 'curatorInsight' is required.
No error handling guidance. chat endpoint returns generic 500 with fallback message but does not tell LLM whether to retry, ask user, or escalate.
Tool descriptions are too short (health_check: 67 chars, chat: ~150 chars). Baseline for LLM-optimized descriptions is 50-200 chars; these lack context on WHEN to use each tool and WHY.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 42 | 2026-07-28+ | v2 |