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

Annotations already mark it read-only, idempotent, and non-destructive. The description adds useful behavioral context by disclosing the dataset domain and that the response includes caveats and per-tool examples; the output schema handles return shape, so omission of return format is minor.

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?

It is front-loaded with 'Start here' and then a compact enumeration of returned content. There is no filler, although the long list makes the sentence dense.

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 read-only documentation tool with an output schema and a fully documented single parameter, the description is complete enough: it tells the agent this is the starting point and what topics the response covers. No call-critical detail is missing.

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 sole parameter is fully documented in the schema, including that purpose is logged and never returned. The description adds no parameter guidance, so baseline 3 is appropriate when schema coverage is 100%.

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 identifies a documentation/overview tool and enumerates exactly what it returns: dataset scope, currency, fields, stats metrics and dimensions, caveats, and example calls. 'Start here' differentiates it from sibling get/search/stats tools as the orientation resource.

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?

'Start here' gives explicit sequencing guidance: call this before other tools. It does not state when not to use it or name alternatives, but its orientation role is clear.

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