Server defines 4 tools with complete JSON schemas and descriptions. Two primary tools (get_customer_record, trigger_refund) have excellent input validation using Pydantic with strict type constraints, pattern matching, and field descriptions. However, two mock tools (public_echo, admin_reset_key) lack parameter descriptions and have minimal descriptions. Output schemas are not documented. Error handling is present but generic. Naming follows verb_noun convention well. Overall solid for a reference implementation but gaps in documentation and output schema definition prevent higher scores.

• Add parameter descriptions to mock tools: public_echo.text should describe what text is echoed and any constraints; admin_reset_key should document what 'key rotation' means and side effects.
• Document output schemas for all tools. Define the structure of customer records (fields: customer_id, name, status, account_tier) and refund responses (fields: refund_id, customer_id, amount, reason, status) in tool descriptions or as a separate schema reference.
• Expand tool descriptions for mock tools to 50-150 chars. Example: 'public_echo: Returns the supplied text unchanged. Useful for testing tool invocation and response handling.' and 'admin_reset_key: Simulates privileged key rotation. Requires admin authorization. Returns new key metadata.'
• Enhance error messages with recovery guidance. When validation fails, include the constraint that was violated and suggest corrective action: 'Invalid amount: must be > 0. Received: -50. Please provide a positive refund amount.'
• Remove or document the purpose of public_echo and admin_reset_key. If these are test fixtures, move them to a separate mock server or clearly mark them as non-production. If they are intentional, add business context to their descriptions.

Inferred effective spec: 2025-06-18+.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry