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 operation is an aggregation over the same filter space as search, which is useful context, but adds little else beyond annotations.

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?

Front-loaded with the purpose, followed by the facet enum and pagination notes. Slightly verbose in repeating schema-provided pagination detail, but no wasted framing.

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 100% schema coverage and an output schema present, the description needn't explain return values or most params. It covers the facet concept and the search alternative, leaving little an agent needs missing.

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 parameters. The description restates the facet enum and page/page_size pagination rules, which duplicate the schema rather than adding meaning. 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 for one facet of the TrustMRR dataset'. This clearly distinguishes it from datasets_trustmrr_search, which it names as the search counterpart.

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 results are 'scoped to the same filters as search' and explicitly directs the agent to datasets_trustmrr_search for full search, giving clear context. However it doesn't spell out the when-not conditions (e.g. use facets to build filter UIs, not to retrieve records).

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