Two tools with minimal documentation. get_tutorial_summary has no parameters but lacks depth in description (returns static text, not actionable). somar has proper parameter types and descriptions but both tools lack output schema documentation. No error handling, no composition guidance, no security considerations. Descriptions are present but generic. Parameter descriptions for somar are adequate (72 chars avg baseline met), but tool descriptions fall short of LLM-optimization standards (10-1024 char range; both are under 100 chars, losing context).

• Add output schema documentation to both tools. For somar, document: {"type": "object", "properties": {"result": {"type": "integer", "description": "Sum of a and b"}}}. For get_tutorial_summary, return structured JSON with title, steps array, and prerequisites.
• Expand get_tutorial_summary description to 100-200 chars explaining: what tutorial content it covers, when to call it (e.g., 'Call this to understand MCP server architecture before implementing'), and what structure it returns.
• Add input validation and error messages. E.g., if somar receives non-integers, return: 'Invalid input: a and b must be integers. Got a={type(a).__name__}, b={type(b).__name__}.'
• Declare tool annotations in schema. Add readOnlyHint: true to both tools' input schemas to signal they are safe to call without side effects.
• Restructure get_tutorial_summary response as JSON with fields: {"title": "MCP Server Tutorial", "steps": [...], "prerequisites": [...]} instead of unstructured text. This enables LLMs to extract and reuse individual steps.