Three tools with basic schemas and descriptions, but significant gaps in parameter documentation and output schema clarity. execute_tool accepts generic 'arguments' object with no structure guidance. Descriptions are present but minimal (50-80 chars, below the 194-char baseline). No error handling guidance, no parameter constraints (enums, ranges), and no output schema documentation. Tool names are action-verb based (execute_, read_) which is good, but the proxy pattern obscures what each tool actually does on the target server.

• Define a structured schema for the 'arguments' parameter. Instead of a bare object, specify required/optional keys, types, and constraints. E.g., for execute_tool: {"type": "object", "properties": {"param_name": {"type": "string", "description": "..."}}, "required": []}.
• Document output schemas for each tool. Add to descriptions: 'Returns: {result: any, status: string, error?: string, execution_time_ms: number}' or equivalent. This lets LLMs know what to expect.
• Expand descriptions to 100-200 chars. Include: what the tool does, when to use it (vs alternatives), what it returns, and any prerequisites. E.g., 'Execute a tool registered on a remote MCP server. Use this to invoke tools discovered via list_tools. Returns the tool result or an error message.'
• Add error handling guidance. Specify common errors (server_id not found, tool_name not found, timeout, permission denied) and recovery steps. E.g., 'If server_id is invalid, call list_servers() to find the correct ID.'
• Constrain resource_uri format. Add to description: 'Format: scheme://path (e.g., tavily://search-results/AI). Call list_resources() to discover valid URIs for a server.'

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

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