add_audience_signal

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

Annotations indicate a write operation that is not idempotent and not destructive. The description adds valuable behavioral context beyond annotations by stating that audience signals are 'suggestions, not hard targeting constraints,' clarifying the non-binding nature of the operation. It does not cover every side effect, but the annotations plus this context provide adequate transparency.

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 compact and front-loaded: the main purpose appears first, followed by a short conceptual note and a four-line parameter list. Every sentence contributes useful information without redundancy or filler.

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 4-parameter mutation tool with no output schema, the description covers the core invocation details: purpose, parameter meanings, and the conceptual nature of audience signals. It lacks explicit guidance on parameter combinations or required-at-least-one behavior, but overall it is sufficient for correct tool selection and invocation.

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 for all four parameters. It does so with a concise Args list explaining customer_id, asset_group_id, audience_resource_name, and search_themes, including that audience_resource_name comes from audience manager and search_themes are keywords describing the ideal customer. It stops short of clarifying whether the two optional signals can be combined or whether at least one is required, leaving a minor gap.

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 first sentence states a specific verb, object, and target: 'Add audience or search theme signals to a PMax asset group.' It clearly differentiates from sibling tools like add_assets_to_group by focusing on audience/search theme signals. The added note that these are 'suggestions, not hard targeting constraints' removes ambiguity about the tool's role.

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 gives clear context for when to use the tool: when adding audience or search theme signals to a PMax asset group, and explains they help Google's AI find customers. It does not explicitly name alternative tools or state when not to use it, but the purpose and semantic distinction are clear enough for an agent to select it appropriately.

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