List Google Health Data Points

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

Annotations already indicate readOnly, idempotent, and non-destructive. The description adds context about kebab-case data types but does not elaborate on pagination, filtering behavior, or response details. Minimal added value beyond annotations.

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 extremely concise (two sentences) and front-loaded with the key action and resource. Every word adds value, with no redundancy.

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 presence of a full output schema and comprehensive annotations, the description sufficiently covers the tool's purpose and key usage detail (kebab-case). The minimal description is complete enough for an experienced user.

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 description coverage is 50%, and the description provides minimal additional meaning (e.g., emphasizing kebab-case). The schema itself describes most parameters adequately. The description does not significantly compensate for the uncovered 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 uses a specific verb 'Query' and resource 'data points for a Google Health data type', clearly distinguishing it from siblings like 'get_data_point' (single) and 'list_data_types' (types only). Examples (e.g., 'steps') further clarify.

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?

While the description implies usage for querying data points of a given type, it lacks explicit guidance on when to use this vs. alternatives like 'get_data_point' or 'daily_summary'. No when-not-to-use or alternative recommendations are provided.

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