This MCP server has fundamental gaps across all dimensions of the definition quality rubric. The two tools ('triage' and 'batch_triage') have adequate names but are severely underspecified in their schemas, parameter descriptions, and output documentation. The server appears to be a Python SDK wrapper without proper MCP tool registration. Critical issues: (1) Input schemas visible in the assessment show only parameter names and loose type hints ('message': string, 'customer_context': object, 'available_teams': array) but lack detailed JSON Schema with proper constraints, enums, or validation rules. (2) Parameter descriptions are minimal ('Raw customer message text', 'Optional context with order_id, past_tickets, is_vip'), falling well below the 50-200 character target for LLM-optimized descriptions. (3) Output schemas are entirely undocumented, the triage() method returns a dict with fields like 'intent', 'urgency', 'sentiment', 'routed_to', 'suggested_response', 'escalate', 'escalate_reason', 'message_length', but the return type and field descriptions are absent from any MCP tool definition context. (4) No error handling guidance, the code has no try-catch blocks, no validation of enum values, and no structured error responses. (5) The tool definitions appear inferred from Python method signatures rather than explicitly registered with proper MCP tool metadata.

• Define input schema as proper JSON Schema. For 'triage': customer_context should be an object with properties: {order_id: string, past_tickets: integer (min 0), is_vip: boolean}, all optional. available_teams should be an array of strings with enum constraint or pattern (must match deployed team names).
• Document the output schema for both tools. triage() returns {intent: enum(order_status|return_refund|billing_payment|product_question|complaint|compliment|account|discount_promo|general), urgency: enum(critical|high|medium|low), sentiment: enum(positive|negative|neutral), routed_to: string, suggested_response: string, escalate: boolean, escalate_reason: string|null, message_length: integer}.
• Expand parameter descriptions to 50-150 characters each with formatting constraints. E.g., 'customer_context: Optional dict with order_id (order number as string), past_tickets (count of prior tickets, 0-100), is_vip (boolean). Include known customer history to improve routing and escalation decisions.'
• Add a description to the 'message' parameter explaining expected format and any size limits. E.g., 'Raw customer message text (1-5000 characters). Include the full message as written by the customer, not a summary.'
• Add error handling with structured responses. If message is empty, return {error: 'message_required', guidance: 'Provide the customer message text.'}. If available_teams is empty, return {error: 'no_teams_available', guidance: 'Pass at least one team name in available_teams.'}.
• Split 'batch_triage' into two tools: 'triage_batch' (triages multiple messages without sorting) and optionally a separate 'sort_triage_results' (sorts an array of triage results by urgency). This improves composability, agents can triage and optionally sort.