get_calories

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only states the verb and resource. It omits details about authentication requirements, data freshness, or whether the request is idempotent. The return line merely references an endpoint without explaining the response structure.

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 concise and front-loaded with the purpose. The parameter list is clearly structured, though it could be more integrated into a flowing sentence. The inclusion of the return line adds value without excessive length.

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?

Given the tool's simplicity and the presence of an output schema, the description provides basic completeness. However, it lacks context about the scope of data (e.g., whether it includes all users or a specific user) and does not explain the significance of the granularity parameter or the default date behavior in practical terms.

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?

Although the input schema has no descriptions, the description adds meaning by specifying the date format (YYYY-MM-DD), the default time zone (SENSR_TZ or America/Chicago), and the valid granularity values (day|week|month|year). This compensates for the 0% schema description coverage and clarifies usage for the optional parameters.

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's action: 'Get calorie details for a user.' The verb 'get' and resource 'calorie details' are specific and distinct from sibling tools like get_sleep or get_scores, which target different health metrics.

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 provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as whether the user must have data for the specified date, nor does it indicate when another tool like get_activities would be more appropriate.

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