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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains the output content and units but says nothing about response format, pagination, authentication, read-only safety, or behavior when slug is omitted. The read-only nature is only inferred from the tool name and domain, not disclosed.

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 a single, front-loaded sentence with no filler. Every clause adds concrete information about the data returned, target audience, and measurement units.

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 read endpoint with one optional parameter and 100% schema coverage, the description is nearly complete: it specifies the output fields and units, and the schema covers the slug behavior. Missing are explicit routing to alternatives and a light note on response packaging, but these are minor for this tool.

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?

There is only one optional parameter, and the schema description covers it fully, including the omit-for-full-lineup behavior. The tool description adds no parameter-specific semantics beyond what the schema already provides, so the baseline score of 3 applies.

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 what the tool returns: structured, machine-readable nutrition data per beer, and it enumerates the exact fields and units (per-can and per-100ml calories, carbs, protein, sugar, ABV, allergens, dietary flags). The health-platform framing also helps differentiate it from general beer-info siblings such as get_beer and list_beers.

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 description implies use when a caller needs nutrition data for health, fitness, or diet-tracking platforms, but it does not explicitly state when to prefer this tool over siblings like get_beer or list_beers, nor does it mention exclusions or alternatives. Usage context is present but left to inference.

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