Search the App Store

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

Beyond the annotations (readOnlyHint, openWorldHint), the description explains the return format (markdown tables), handling of missing fields ("N/A"), no-match behavior (header only), performance (no browser, ~1 second), and data limitations (no downloads/revenue). No contradiction with annotations.

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 with a clear opening, bullet points for usage, and separate paragraphs. It is slightly long but every sentence adds value, making it efficient for its purpose.

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 has three parameters, no output schema, and annotations present, the description covers all necessary aspects: return format, error behavior, data limitations, and sibling tool references. It is fully adequate for an agent to understand when and how to use the tool.

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 baseline is 3. The description does not reiterate parameter details, but the schema already thoroughly documents limit (with defaults and clamping), country (pattern), and keyword (minLength). No additional meaning is needed.

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 searches the App Store for a keyword and returns a ranked table. It identifies the specific verb (search), resource (App Store), and output (ranked table), and distinguishes it from siblings by noting iOS-only coverage and the absence of downloads/revenue figures.

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?

Explicit guidance is provided: use this to discover rankings before deep analysis, follow up with get_app_details, or use research_rivals for a combined call. It also warns against using for Google Play/Android, which effectively sets exclusion criteria.

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