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

With no annotations, the description carries the full burden of behavioral disclosure. It clarifies a key nuance: `measured=false` means the page was never read, not that it is empty, which prevents misinterpretation. It also implicitly indicates read-only behavior by describing the data retrieved. However, it does not disclose error handling, rate limits, or authorization requirements, which are common behavioral aspects. The `measured` clarification is a significant positive.

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 well-structured, starting with the main content list, then the timeline explanation, and finally the `measured` flag clarification. Each sentence adds value and is not redundant. It is concise enough for the amount of information conveyed, and the most critical usage hint (timeline for rank moves) is placed in the second sentence, which is acceptable.

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 no output schema and no annotations, the description is fairly complete. It enumerates the expected data fields, explains the `timeline` and `measured` semantics, and implies both iOS and Google Play data. It does not specify default behavior for the optional `country` parameter or error cases, but these are minor gaps. An agent has enough context to call the tool correctly.

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 input schema already describes both parameters with 100% coverage (appId from list_apps, country code example). The description adds the context that the tool retrieves signals 'for one country', reinforcing the purpose of the country parameter, but provides no additional semantic detail beyond the schema. Since the schema covers the parameters well, a baseline 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 tool retrieves the app's own store listing signals for a country, enumerating specific data points (name, subtitle, version, in-app events, editorial placements, similar-apps shelves, screenshot set, Google Play page details). This distinguishes it from siblings like get_charts, get_reviews, and get_history, which focus on different data domains. The verb 'get' and resource 'store page' are specific and unambiguous.

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 offers a contextual hint by noting that `timeline` lists dated changes as 'the cheapest explanation for a rank move', implying the tool is useful for investigating rank changes. However, it does not explicitly state when to use this tool over alternatives like get_history or get_charts, nor does it mention exclusions or when not to use it. The 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.