Open Brain provides 8 memory-management tools with complete JSON schemas and reasonable descriptions. All tools have input schemas with typed parameters and descriptions. However, descriptions are generic and lack LLM-optimized guidance on WHEN to use each tool vs. alternatives. Parameter descriptions are minimal (e.g., 'Max results' without explaining why limit matters). No output schemas documented. Error handling is absent, no guidance on recovery paths. Tool naming is clear (memory_* prefix) but lacks verb-first convention (search, store, get are present but inconsistent). No tool annotations (readOnlyHint/destructiveHint) despite clear read/write distinction in metadata.

• Add output schemas for all tools. Document return fields (e.g., memory_search returns [{id, content, tags, created_at, importance, entities}]). Enable LLMs to chain tools without guessing field names.
• Enhance tool descriptions with WHEN guidance. E.g., 'Use memory_search for keyword/semantic queries; use memory_get_entity to find all memories mentioning a specific person or technology; use memory_get_related to discover contextually similar memories.'
• Add tool annotations: set destructiveHint=true for memory_store and memory_regenerate_embedding; set readOnlyHint=true for all GET tools. Enables agents to reason about side effects.
• Expand parameter descriptions with constraints and semantics. E.g., 'limit: Max results returned (1-100, default 5). Higher limits increase latency; use pagination for large result sets.' 'tags: Filter by tags (AND logic, memory must have ALL tags).'
• Add error handling guidance to tool descriptions. E.g., 'If memory_id not found, returns 404 with available memory IDs. Try memory_search() to locate the memory first.' Implement per-tool error recovery paths.