Both tools have minimal descriptions (10-25 chars, well below the 50-200 char baseline for LLM-optimized descriptions). Parameter descriptions are completely absent (null values in schema). No output schemas documented. No error handling guidance. Tools lack context for when/why to use them. Naming is acceptable (verb_noun: add, mul) but descriptions fail to explain what the tools do beyond a bare statement.

• Expand tool descriptions to 50-150 chars. Example: 'add: Adds two integers and returns their sum. Use when you need basic arithmetic. Parameters: a (first number), b (second number). Returns: integer result.'
• Add descriptions to all parameters. Example: 'a: The first integer to add (range: -2147483648 to 2147483647)' and 'b: The second integer to add (same range)'.
• Document output schemas explicitly. Example: 'Returns: {"type": "integer", "description": "The sum of a and b"}'.
• Add input validation with clear error messages. Example: 'if not isinstance(a, int): raise ValueError("Parameter a must be an integer, got {type(a).__name__}")'.
• Consider adding optional parameters like 'precision' or 'mode' (e.g., 'saturating' vs 'wrapping' for overflow) to make tools more flexible for agent composition.