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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds the nature of the computation (per-dimension counts) but says nothing about rate limits, auth, cost, or whether counts are exhaustive versus sampled, which would be useful for an open-world scrape.

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?

A single front-loaded sentence that names the return shape and the scoping input with zero filler. Nothing to trim.

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 one-parameter, read-only facets tool with an output schema (so return values need no prose), the description covers purpose and output granularity adequately. Only the lack of explicit sibling routing and any facet-dimension caveats keep it from being fully complete.

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 0% for the single 'query' parameter, so the description is the only source of meaning. 'for a Depop search query' implies the parameter is a free-text search string, but it adds no syntax, format, or example guidance beyond that implication.

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 states a concrete output (result-count breakdowns) and its grouping dimensions (department/category/subcategory) tied to a Depop search query, which clearly distinguishes it from depop_search (which returns listings) and depop_categories (static taxonomy). It does not name any sibling explicitly, so it lands at 4 rather than 5.

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?

Usage is only implied: an agent can infer this is for exploring how a query distributes across categories rather than retrieving items, but there is no explicit when-to-use, when-not-to-use, or named alternative such as depop_search. This is minimum-viable guidance.

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