Two tools with basic schemas and Japanese descriptions. Both tools have input schemas with type definitions and required flags, but descriptions are in Japanese (non-standard for LLM-optimized English tooling) and lack actionable context. Parameter descriptions exist but are minimal. No output schemas documented. Error handling returns JSON errors but lacks recovery guidance. Tool names follow verb_noun pattern (get_, create_) which is positive. However, schema completeness is partial, attendees parameter uses string instead of array, and output structure is not formally specified.

• Translate all tool and parameter descriptions to English. Provide concise, LLM-optimized descriptions (50 - 200 chars) explaining WHAT the tool does, WHEN to use it, and any prerequisites.
• Document output schemas formally. For get_user_outlook_events, specify: {user: {userPrincipalName: string}, value: [{subject: string, start: ISO8601, end: ISO8601, isAllDay: boolean}]}. For create_simple_event, specify success response structure and error cases.
• Change attendees parameter from string to array of email strings. Update description: 'Array of attendee email addresses (all marked as required). E.g. ["[email protected]", "[email protected]"]'.
• Add tool annotations: readOnlyHint=true for get_user_outlook_events; destructiveHint=true for create_simple_event. This signals to agents which tools have side effects.
• Enhance error responses with recovery guidance. E.g., 'Invalid userPrincipalName format. Expected email ([email protected]). Call search_users() to find the correct UPN.' Categorize errors as retryable vs fatal.

Inferred effective spec: <=2025-11-25.

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