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

Beyond the annotations, the description discloses important behavioral traits: definition=true returns rule details per list type, Google may not store a readable rule for every list, older lists return definition_available=false, and the Google Ads interface is the only fallback. This adds substantial context beyond the read-only and idempotent annotations. The final 'Read-only' label is redundant with annotations but does not detract.

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 list operation and returned fields, then moves into the important definition=true behavior and caveats. It is dense but largely earns its length, though the warning about excluding lists is somewhat verbose and the trailing 'Read-only' phrase is redundant with annotations.

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 moderate complexity, the output schema, and the strong read-only annotations, the description is nearly complete. It covers the definition behavior and its limitations well. The main gap is lack of guidance on the limit parameter, and customer_id is only implicitly identified as the account selector.

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 0%, so the description must compensate. It thoroughly explains the definition parameter, including what each list type returns when definition=true, but it does not explain the limit parameter or the required customer_id parameter. Definition semantics are strong, but the other two parameters remain undocumented.

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 states a specific verb and resource: it lists an account's audiences and enumerates the audience types and returned fields. It also anchors the tool to Google Ads via references to rule-based lists and the Google Ads interface. However, it does not explicitly differentiate itself from sibling audience-listing tools such as list_meta_audiences or list_linkedin_audiences, so sibling differentiation is left implicit.

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 strongly explains when to set definition=true and warns against excluding a list without checking its rule, which gives useful usage context. It does not, however, state when to choose this tool over the various other list_audiences siblings across platforms, nor does it describe when not to use it. Usage is therefore implied rather than fully specified.

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