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

Adds real context beyond the annotations: the sort is hard-fixed to trending_desc, search filters still apply, and there is a concrete cost model (1 credit per record, minimum 2) with an optimization hint for page_size. Annotations already cover read-only/open-world, so this cost and sort behavior is the value-add; return format is left to the 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, front-loaded with the core operation, then alternatives and cost. Every clause is actionable and nothing is repeated from the schema.

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 an output schema present, return values need not be explained, and the description covers the operation, routing, fixed sort, and cost. It is nearly complete, though it could note whether filters combine or how paging interacts with the credit cost.

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 all 16 filters. The description only adds behavioral guidance about page_size (cost) and the fixed sort; it does not clarify filter syntax or enum semantics beyond what the schema provides. Baseline 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?

States a specific verb+resource ('Fetch stored Chrome Web Store item records ranked by recent user and rating-count movement'), which pins down both the entity and the ranking dimension. It differentiates itself from siblings by naming datasets_chrome_extensions_changes and datasets_chrome_extensions_search as the alternatives for different needs.

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?

Gives clear routing: use datasets_chrome_extensions_changes to inspect changes for one item, and datasets_chrome_extensions_search when a different sort order is needed. It stops short of an explicit when-not statement (e.g., pure keyword lookup without trend ranking), so it is strong but not exhaustive.

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