datasets_trustmrr_facets

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

With no annotations provided, the description carries the burden of behavioral disclosure. It does state the core behavior (returns terms-aggregation counts) and that it is scoped to filters. However, it does not disclose details such as response structure (e.g., array of key-count pairs), potential pagination or limits, error conditions, or any side effects. Since it's a read-only operation, the absence of destructive effects is implied but not explicit. This is a moderate disclosure but leaves room for improvement.

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 two sentences with no fluff. The first sentence states the action and result, and the second lists the valid facet values. It is front-loaded with the primary purpose, making it easy to scan. Every word 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?

Given the tool's relative simplicity, the description is adequate but not complete. It clearly indicates that the output is counts per facet, but it does not describe the exact return format (e.g., objects with key and count, sorting, or limits). Since there is no output schema, this missing detail could lead an agent to guess the response structure. It also doesn't clarify whether multiple facets can be requested (though 'one facet' implies single). For a filtering and aggregation tool, this level of completeness is acceptable but leaves some ambiguity.

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 describes each parameter (q, country, min_mrr, etc.). The description adds the phrase 'scoped to the same filters as search,' which clarifies that these filter parameters apply to the aggregation, but it does not explain how each parameter interacts with the facet computation beyond that. The facet enum is already in the schema. The description adds only a small amount of semantic value beyond the schema.

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 clearly states the tool's function: 'Returns terms-aggregation counts for one facet of the TrustMRR dataset.' It specifies the verb (returns counts), the resource (TrustMRR dataset), and the scope (one facet). The list of facet enums adds precision. It is distinct from sibling tools like datasets_trustmrr_search, which presumably returns full records rather than counts.

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?

The description mentions 'scoped to the same filters as search,' implying that the filter parameters (q, country, min_mrr, etc.) work the same as in the search tool. However, it does not explicitly state when to use this tool versus search or other facet tools, nor does it provide any exclusions. An agent might infer it is for getting distributions, but the guidance is implicit rather than explicit.

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