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 useful constraint that it honors the same filters as search, but says nothing about aggregation semantics, whether page/page_size affect facet output, or result limits.

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 with zero padding, and the core purpose is front-loaded before the usage note. Every sentence carries information.

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 no explanation, and the schema fully documents the large filter set. The description covers purpose and usage adequately, though for a 31-parameter tool it could say a bit more about how the facet aggregation relates to the pagination parameters.

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 31 parameters including the required 'facet' enum list are documented in the schema itself. The description adds no parameter-level meaning beyond confirming the filter set matches search, so the baseline 3 applies.

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 and resource ("Returns terms aggregation counts over the GitHub users dataset") and its scope ("honoring the same filters as search"), which lets an agent distinguish it from datasets_github_users_search. It does not name the search sibling explicitly, only referring to "the related search tool", so it falls just short of a 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?

Clearly frames the use case: run it alongside the search tool to inspect filter counts under the same query filters. It gives positive guidance but no explicit when-not or exclusion (e.g. that it returns counts rather than records), so it is not fully prescriptive.

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