Server has 13 tools with consistent naming (verb_noun pattern: get_, search_, list_, add_, find_), clear descriptions (avg ~150 chars), and documented parameters. However, output schemas are not formally documented, responses are JSON strings without declared structure. Error handling is minimal (only ingest_text and find_paths catch exceptions). Parameters lack enums and range constraints. No tool annotations (readOnlyHint/destructiveHint). Descriptions are adequate but could be more LLM-optimized (e.g., 'when to use' guidance missing). Overall: solid foundation, but gaps in schema documentation and error guidance prevent higher scores.

• Add formal output schema documentation to all tools. E.g., get_profile returns {person: {id, name, properties}, connections: [{relation, direction, entity}], hint: string}. Use JSON Schema or OpenAPI format.
• Add tool annotations: mark add_entity, add_relation, ingest_text with destructiveHint=true; mark ingest_text with idempotentHint=true (dry_run=true is safe to retry).
• Convert free-form parameters to enums: list_entities.type → enum [Person, Skill, Project, Knowledge, Tool, Interest, Task, Goal]; add_entity.type → same enum; add_relation.type → enum of valid relation types.
• Add range constraints: get_neighbors.degree ∈ [1, 2]; find_paths.max_hops ∈ [1, 5]; find_paths.max_paths ∈ [1, 50]; list_entities.limit ∈ [1, 100]; search_entity.limit ∈ [1, 50].
• Wrap all tool implementations in try-catch blocks. Return structured errors: {error: string, code: string, hint: string}. E.g., 'Entity not found: xyz. Try search_entity("xyz") to find similar entities.'