Server has 5 tools with complete input schemas and descriptions. Naming follows verb_noun convention (list_, get_, load_, unload_, configure_). However, descriptions are generic and lack LLM-optimization guidance. Parameter descriptions are minimal (e.g., 'The ID of the model to load' lacks format/constraint details). No output schemas documented. Error handling is basic (generic try-catch). Missing tool annotations (readOnlyHint, destructiveHint). No pagination support despite potential for large model lists. Baseline: avg tool description ~194 chars; these average ~120 chars. Avg params per tool: 1.4 (below baseline 4), suggesting under-parameterization.

• Add output schema documentation to each tool. Example for list_models: 'Returns array of objects with fields: id (string), type (enum: llm|vlm|embeddings), state (enum: loaded|not-loaded), max_context_length (number), architecture (string).'
• Expand parameter descriptions with format and constraint details. Example: 'model_id (string, 1-255 alphanumeric chars + hyphens, e.g. 'llama-2-7b-chat')'.
• Add tool annotations to schema. Mark list_models and get_model_details with readOnlyHint: true. Mark load_model, unload_model, configure_model with destructiveHint: true.
• Implement pagination for list_models: add optional 'limit' (1-100, default 20) and 'offset' (default 0) parameters. Return total_count in response so LLM knows if more results exist.
• Enhance error messages with recovery guidance. Example: 'Model not found: llama-2-7b. Call list_models() to see available models.' Categorize errors: retryable (network timeout), user-fixable (invalid model_id), fatal (LM Studio unreachable).