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 one useful behavioral fact: this tool applies the same filter set as the search tool. Beyond that it discloses no rate limits, auth needs, or rationale for the facet requirement.

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 short sentences with zero waste; the core purpose is front-loaded and the sibling pointer follows. Every sentence earns its place.

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 annotations and an output schema present, the description only needs to carry purpose and routing, which it does. It is slightly thin on the facet-counting workflow but nothing an agent needs to call it correctly is 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 all 18 parameters (including the required 'facet' with its allowed values) are already documented in the schema. The description adds no parameter syntax or format detail beyond what the schema provides, so the baseline of 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?

States a specific verb and resource ('Count facet values ... in the stored X users dataset') with scope ('using the same filters as search'). It also distinguishes itself from the sibling 'datasets_x_users_search', so an agent can tell the aggregate-count tool apart from the record-list tool without opening either schema.

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?

Explicitly routes the agent to 'datasets_x_users_search for the matching user records', giving a clear alternative and implying this tool is for counts. It does not state an explicit 'when-not' exclusion, but the contrast with the named sibling is strong and unambiguous.

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