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

With no annotations provided, the description carries the full burden, and it does an unusually strong job: it explains three distinct output states and warns against collapsing them, which is critical behavioral context for producing correct results. It does not cover every possible behavior like authentication or output shape, but the core interpretational trap is thoroughly disclosed.

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: the main purpose appears in the first sentence, and the second sentence explains the most important caveat. Every sentence earns its place, and there is no filler or repetition of schema details.

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 three-parameter tool with no output schema, the description covers the central non-obvious behavior that an agent must know: the difference between measured=false, rank=null, and rank=number. It is slightly light on the exact structure of the returned data, but the essential context needed to call and interpret the tool is present.

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 100%, so the schema already documents appId, country, and platform, including defaults. The description reinforces that the tool is scoped to one app and one country but does not add substantive parameter-level meaning beyond the schema.

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 identifies the resource as keyword ranks and states the precise scope: one app, one country, one platform. It distinguishes this from sibling tools like get_charts and get_reviews by using the specific term 'keyword ranks' and naming App Store / Google Play country scoping.

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 implies this is the tool to use for keyword rank data, but it never explicitly explains when to prefer it over siblings or when not to use it. No alternative tools are named, so the usage guidance is mostly inferred from the stated purpose.

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