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 genuinely useful behavior: it is an aggregation endpoint and it 'honors the same filters as search,' which matters for consistency of counts. It does not discuss pagination or result-size behavior.

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-packed sentences with the core function front-loaded and the usage hint second. No filler or restated name.

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?

An output schema exists, so return values need not be described. The description covers the aggregation semantics and filter parity with search, which is what an agent needs to call it correctly. Minor gaps remain around whether pagination parameters have meaning for facets.

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% across all 25 parameters, so the schema already documents q, facet, and every filter. The description only adds that the filter set mirrors the search tool; it does not explain the required facet values or how page/page_size interact with an aggregation response. Baseline 3 is correct.

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 US housing markets dataset.' An agent can distinguish it from the related search tool, which returns rows rather than counts. It does not name the sibling by exact name, but the function is clear.

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?

Tells the agent to use it 'alongside the related search tool to inspect filter counts under the same query filters,' which implies a companion usage pattern. It does not state when this tool should be preferred over or skipped in favor of datasets_housing_markets_search, leaving some inference to the agent.

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