Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description is consistent, describing plan generation rather than data mutation. It adds context about optional snacks and combined nutrition totals, but does not describe edge cases like conflicting targets or precision limitations, providing only partial additional transparency beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with the core purpose first, then output details, and a TRIGGERS list. The trigger examples are somewhat redundant but useful for usage guidance; overall the text is front-loaded and each section serves a purpose, though it is slightly long.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and four optional parameters, the description covers the essential output composition (meals and totals) and usage triggers. It could be more explicit about the return format or how to handle competing constraints, but the annotations and schema fill safety and parameter gaps, making it reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for all four parameters, so the schema fully defines their semantics. The description only generically references 'calorie and macro goals' without adding interaction details, format specifics, or additional parameter context, warranting the baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool builds a single-day meal plan with specific calorie and macro goals, and specifies the output structure (breakfast, lunch, dinner, optional snack, and combined nutrition totals). This distinguishes it from sibling tools like 'meals_plan' by emphasizing optimization for nutritional targets.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The TRIGGERS section provides explicit example phrases for when to use this tool, such as 'meal plan for 2000 calories' and 'high protein meal plan'. However, it does not state when not to use it or mention alternative tools, so it lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.