Get Carbohydrates

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

Annotations already declare readOnlyHint and idempotentHint. The description adds that the tool returns a single value per 100 g, clarifying output cardinality and unit, which is useful behavioral context beyond the structured annotations. No contradiction exists.

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 two sentences with front-loaded purpose: the first sentence states what it does, the second explains the output format and rationale. No wasted words.

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 simple tool with one parameter and an output schema present, the description covers the essential behavior: returns a single carbohydrate value per 100 g. It could mention error cases, but the tool is so focused that the current level is sufficient.

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 schema defines fdcId as a positive integer but provides no description (0% coverage). The description says 'for a FoodData Central entry', implicitly identifying fdcId as the entry identifier, but it doesn't explicitly map the parameter name to the concept. This is adequate but minimal.

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 returns per 100 g carbohydrates for a FoodData Central entry. The verb 'Return' and specific resource 'carbohydrates' distinguish it from sibling tools like get_macros or get_protein, especially with the per-100g qualification.

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 phrase 'Returns a single value per 100 g to minimize context usage' implies when to use this tool: when only carbohydrate data is needed and minimal output is desired. It doesn't explicitly name alternatives, but the context is clear enough for an agent to select this over broader nutrient tools.

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