get_wellness_data

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

With no annotations provided, the description carries the full burden and does so thoroughly: it explains inclusive/exclusive date semantics, the possible response shapes, valid empty results, error shapes, field preservation including null/zero values, unknown source completeness, and specific metric interpretation caveats like hrv being rMSSD.

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 dense but every sentence carries meaningful information, from core behavior to edge-case shapes to field-interpretation guidance. It is front-loaded with the main purpose and date semantics before diving into detailed return-shape nuances.

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 complexity, the description covers return shapes, error conditions, field semantics, and a pointer to get_metric_definitions. It is missing explicit documentation for several parameters and does not discuss prerequisites or authentication, but the presence of an output schema reduces the need to explain return values. Overall, it is well above minimum viability but has clear 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?

Parameter schema coverage is 0%, so the description must compensate. It explains start_date, end_date_exclusive, and end_date as a deprecated alias, and touches on field preservation relevant to include_all_fields. However, it leaves athlete_id, timezone, api_key, and the exact meaning of include_all_fields undocumented, which is a notable gap given seven 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 states a specific verb and resource: 'Return raw wellness records' with a half-open local-date range. It clearly distinguishes itself from the many activity, event, and custom-item siblings by targeting wellness data.

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 clearly explains the date-range semantics and advises consulting get_metric_definitions before interpreting fields, giving practical usage context. However, it does not explicitly contrast this tool with siblings like get_activities or get_events, so the when-not-to-use guidance is implicit rather than explicit.

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