get_structured_export

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

With no annotations provided, the description carries the full burden. It discloses pagination behavior: 'the result carries `nextCursor` when more metrics remain — pass it back as `cursor` for the next page,' and warns about data volume: 'calling it bare over a full history is a lot of data.' These are valuable behavioral insights beyond the schema. Missing details like auth/rate limits, but still strong for a read-like export tool.

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 compact and front-loaded: it opens with the core purpose, follows with pagination behavior, and ends with a usage tip. Every sentence adds distinct value with no redundancy or unnecessary detail.

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 6 parameters, no annotations, and no output schema, the description covers purpose, pagination, and usage but does not describe the shape of the returned JSON beyond 'clean structured JSON.' Since there is no output schema, the description should ideally clarify the return structure, but the pagination and metric/date range guidance make it reasonably usable. It is minimally complete but has a clear gap in return format details.

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 83%, so the schema already explains most parameters (start/end format, limit roll-up, granularity auto behavior, cursor). The description adds little new parameter semantics—it reiterates cursor usage and encourages specifying metrics/date range. According to the baseline rule for high schema coverage, a score of 3 is appropriate.

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 verb and resource: 'Return clean structured JSON for the chosen metrics/date range.' It is specific, but does not explicitly differentiate from sibling tools like get_trends or query_health_data, though the pagination and raw data focus imply an export tool. Thus it is clear but lacks explicit sibling distinction.

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?

Provides concrete usage guidance: 'Prefer naming the metrics you need and a date range; calling it bare over a full history is a lot of data.' This tells the agent when to call it (with metrics/date range) and warns against bare calls, offering clear context. However, it does not mention when this tool should be used over alternatives or exclusions, so it stops short of the highest rating.

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