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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and locality are covered. The description adds the data-domain scope but says nothing about data freshness, source coverage, or whether results are truncated across the six stores. Adequate but thin for a stats tool with no output schema.

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?

Two sentences, no filler, with the positive use case front-loaded before the exclusion. Every clause earns its place.

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?

With no output schema, the description is the only place the return shape can be sketched, and it does so only as a loose list of topics. It leaves open whether all categories are returned together, whether output differs by response_format, and how the optional parameters affect the result.

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 coverage is only 33% and the description explains none of the three parameters. It never says that `store` scopes results to a specific storefront (or what happens if omitted), nor what distinguishes `response_format: concise` from `detailed`. With low coverage the description was expected to compensate and does not.

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 names the concrete data categories the tool returns (store sizes, weekly launches, app kinds, MCP ecosystem statistics), which tells an agent what 'market' actually means. It stops short of a clean verb+resource statement, but the enumeration makes the resource identifiable.

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?

It gives an explicit use condition ('when you need store sizes, weekly launches...') and an explicit exclusion ('Do not use for app profiles or rankings'), which implicitly routes to listings_profile and leaderboards_get. The alternatives are not named directly, so the routing is slightly inferential.

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