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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds that the aggregation honors the same filters as search, which is useful context, but it does not describe the aggregation output shape, cardinality limits, or how page/page_size interact with aggregation results.

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 tightly written sentences with the core action front-loaded. The second sentence slightly restates the 'same filters' idea from the first, but overall it is efficient and appropriately sized.

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 and 100% parameter coverage, the description need not explain return values or params. Still, for an 18-parameter facets tool it is thin on the practical relationship to search (e.g. that facet counts reflect the filtered result set), leaving a minor contextual gap.

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 all 18 parameters are already documented in the schema, including the required facet and its allowed values. The description adds no syntax or semantics beyond the schema, so the 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?

The description states a specific verb and resource ('Returns terms aggregation counts over the X users dataset'), which clearly distinguishes it from the sibling item/search tools. However, it never names the actual sibling (datasets_x_users_search) and instead refers to 'the related search tool', leaving the differentiation slightly inferential.

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 says to 'use alongside the related search tool to inspect filter counts under the same query filters', which implies the usage context (pairing facet counts with a search query). It gives no explicit when-not-to-use, prerequisites, or named alternative, so the guidance is implied rather than spelled out.

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