Critical gaps across all 21 tools. No input schemas visible in source code, tool definitions appear to be inferred from file structure rather than explicitly registered with JSON Schema. Descriptions are present but generic (10-50 chars), lacking LLM-optimized guidance on WHEN to use each tool, WHAT it returns, or dependencies. No parameter descriptions found. No output schemas documented. No error handling patterns visible. Tools are grouped by domain (directory, analytics, conversations) but individual tool names, signatures, and composition chains are not evident from the provided code.

• Expose individual tool definitions with explicit JSON Schema. Each tool must have a name (verb_noun format: get_users, list_conversations, search_analytics), description (50-200 chars), and input schema with typed, described parameters.
• Add output schemas documenting returned fields. Include IDs and references needed for tool chaining (e.g., user_id, channel_id, conversation_id). Specify pagination (limit, offset, total_count) for list tools.
• Rewrite descriptions as LLM-optimized prompts: 'Get a list of Genesys Cloud users by name, email, or ID. Returns user_id, name, email, title, and department. Use this to resolve user references before calling other tools.' (vs. current generic 'Directory tools for querying...').
• Add parameter descriptions for every input. Example: 'user_id (string, required): The Genesys Cloud user ID or email address. If you only have a name, call search_users() first.'
• Implement error handling with recovery guidance. Return structured errors: {error: 'user_not_found', message: 'User [email protected] not found. Try search_users() with a partial name.', retryable: false}.

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

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