get_body_composition

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 only says 'returns' trends, implying a read operation, but it doesn't disclose how trends are computed, whether data is aggregated or raw, how the time period is bounded, or what happens when no data is available. This is minimal and insufficient without annotation support.

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, focused sentence with no wasted words. The core capability is front-loaded and easy to parse. However, it omits details about the time period parameter, which affects completeness more than conciseness; as a concise statement it works well.

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 one parameter and no annotations or output schema, the description is incomplete for correct invocation. The agent does not know what 'days' means, how to specify the time period, or what the returned trends look like. Sibling tools don't provide this context. The description leaves critical gaps.

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 only parameter 'days' has no schema description (0% coverage), and the description never mentions it. While the name 'days' hints at a time period, the description's 'over a time period' is not explicitly linked to the parameter. The agent cannot determine the parameter's meaning, default, or units from the description.

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 states a specific verb ('Returns') and a distinct resource ('weight, body fat, and muscle mass trends over a time period'). This clearly identifies the tool's purpose and differentiates it from sibling trend tools like get_heart_rate_trends or get_vo2_max_trends by the metrics involved, though it doesn't explicitly name alternatives.

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?

There is no guidance on when to use this tool versus the many sibling tools. It doesn't mention that it should be used for body composition metrics specifically, or provide any exclusions or conditions. The agent must rely on the tool name and description to infer its use case.

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