datasets_youtube_creators_facets

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

With no annotations, the description must carry the behavioral burden. It does disclose that the tool returns terms aggregation counts, but it does not explain whether the many filter parameters are applied to the aggregation, how many buckets are returned, or the exact response shape. This is adequate but not transparent.

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?

The description is short and front-loaded with the core operation and output type. However, 'for the YouTube creators dataset' appears twice, creating minor redundancy; otherwise 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?

The tool has 21 parameters and no output schema or annotations, yet the description only provides the facet enum and the vague output type. It does not explain filter-query interaction, response shape, or aggregation limits, leaving meaningful gaps for a tool of this complexity.

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 every parameter. The description repeats the facet enum values that are also in the schema but adds no new semantic meaning beyond the structured field descriptions.

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 specifies the verb 'facet,' the resource ('YouTube creators dataset'), and the exact output type ('terms aggregation counts'). It also lists the facet enum values, which clearly separates this aggregation tool from sibling record-level tools like datasets_youtube_creators_search and datasets_youtube_creators_item.

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?

Usage is implied by the word 'facet' and the description of aggregation counts, but there is no explicit guidance about when to choose this over the search or item siblings. No exclusions or alternative routing are provided, leaving the agent to infer the appropriate context.

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