Get Protein

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

Annotations already declare read-only, idempotent behavior, so the bar is lower. The description adds useful operational details: per-100g normalization and single-value return, which go beyond annotations. It doesn't cover error handling, but for a simple read tool this is acceptable.

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?

Two concise sentences with front-loaded behavior in the first sentence and a rationale in the second. Every word earns its place; no redundancy or filler.

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?

With an output schema present and annotations covering safety, the description is sufficient for a simple data-retrieval tool. It explains the unit and response shape, though it doesn't mention missing-data behavior. Given the simplicity, the absence is a minor gap.

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?

Schema has one required parameter fdcId with 0% description coverage. The parameter name is self-explanatory, and the description clarifies it refers to a FoodData Central entry, but adds no extra detail about the ID format, source, or constraints beyond the schema's exclusiveMinimum.

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?

Description clearly states the tool's verb (return) and resource (per 100g protein for a FoodData Central entry), distinguishing it from sibling tools focused on other nutrients. The 'per 100 g' scope is specific and unambiguous.

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?

Mentions the benefit of minimizing context usage, which implies a use case over broader tools like get_macros or get-food, but does not explicitly name alternatives or state when not to use it. The context is clear but lacks explicit exclusions.

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