Three tools with minimal definitions. All have basic schemas with required parameters and type declarations, but descriptions are extremely terse (10-30 chars, well below the 50-200 char baseline for LLM-optimized tools). Parameter descriptions are present but generic. No output schemas documented. No error handling guidance. Tools lack context about when to use them or what they return. This is a scaffolding/demo server, not production-grade.

• Expand tool descriptions to 80-150 chars. Example: 'hello' → 'Greet a person by name. Returns a friendly greeting message. Use this to personalize interactions or test basic tool invocation.'
• Document output schemas for each tool. E.g., hello returns {greeting: string, timestamp: string}; add returns {result: number, operands: [number, number]}; timestamp returns {iso8601: string, unix_ms: number}.
• Rename tools to verb_noun pattern: 'hello' → 'greet_user', 'timestamp' → 'get_current_timestamp'. This helps LLMs parse intent from the name alone.
• Add parameter constraints and formats. E.g., 'name' → 'Name of the person to greet (string, 1-100 chars, alphanumeric + spaces)'. For 'add', specify 'a' and 'b' as 'Number (integer or float, range -1e6 to 1e6)'.
• Add error handling examples in descriptions. E.g., 'add' → 'If inputs are non-numeric, returns error with message: Invalid input: expected numbers, got <type>. Retry with valid numeric values.'