Five tools with complete schemas and descriptions, but quality is uneven. Tool names lack action verbs (ai-memory-* prefix is generic). Descriptions are adequate (60-120 chars) but lack WHEN/WHY guidance. Parameters have types and descriptions, but no enums for constrained values (e.g., 'role' should be enum: [user, assistant]). Output schemas are not documented. Error handling is absent, no recovery guidance or actionable error messages visible in source. Composition is reasonable (single responsibility per tool), but missing pagination details and chaining IDs in responses.

• Rename tools to verb_noun pattern: search_conversations, list_conversations, get_conversation, update_conversation_summary, get_system_status. This enables LLMs to infer intent from names.
• Add output schema documentation for each tool. Example: 'Returns array of {id, query, workspace, date_from, date_to, role, limit, offset, results: [{id, text, role, timestamp}], total_count}'. Include all fields the agent needs for chaining.
• Convert 'role' parameter to enum: {type: string, enum: [user, assistant], description: 'Filter by message role'}. Apply same pattern to any other constrained values.
• Enhance descriptions with WHEN/WHY. Example: 'Search conversations by query text. Use this to find specific discussions; use list_conversations to browse all conversations in a workspace.'
• Implement structured error responses with recovery hints. Example: {error: 'Conversation not found', suggestion: 'Try list_conversations() to see available IDs', retryable: false}.