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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description adds useful behavioral context by explaining that the tool counts and ranks commercials with breakdowns by dimension. It still does not explain the exact return format, ranking metric, or how limit affects results, leaving some operational details implicit.

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 front-loaded with the core action ('Count and rank the ads library') and follows with a compact enumeration of dimensions plus one concrete example. Every sentence contributes to understanding how to use the tool.

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?

For a 26-parameter aggregation tool with no output schema, the description is adequate: it explains the central concept, identifies the required fields dimension, and demonstrates a realistic filtered query. It still leaves some gaps around output structure and ranking behavior, but the combination of schema descriptions and this narrative is sufficient for common calls.

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?

With 65% schema description coverage across 26 parameters, the description adds meaningful semantics for the key fields parameter by framing its values as breakdown dimensions. The worked example also clarifies how award_show, industry, and year_min combine in practice, though several parameters such as limit and min_award are left to 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 uses a specific verb and resource: 'Count and rank the ads library'. It immediately clarifies that this is an aggregation tool rather than a search or record-retrieval tool, which distinguishes it from siblings like search_commercials and get_commercial.

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 example query ('which agencies won the most Cannes Lions for car ads since 2015') clearly illustrates the intended aggregation use case and maps it to parameters. However, it does not explicitly state when not to use this tool or name alternatives such as search_commercials.

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