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audience_segments

Read-only

Retrieve Google Ads audience segments by type and search query to target campaigns precisely.

Instructions

Browse Google Ads audience segments for campaign targeting.

Returns available audience segments filtered by type and optional search query.

Args:
    segment_type: Segment type — "IN_MARKET", "AFFINITY", or "LIFE_EVENTS"
    query: Optional filter (e.g. "fitness", "travel") to narrow results

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
configNo
segment_typeNoIN_MARKET
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the read-only nature is known. The description adds that results are filtered by type and optional query, which is useful behavior context. It does not discuss pagination, response format, or rate limits, but for a simple read-only browse tool, this is acceptable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured: a one-line purpose, a one-line return description, and a bulleted list of arguments. Every sentence adds value, with no fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only list tool with a clear purpose and parameter explanations, the description is largely complete. It covers the main parameters and the read-only safety annotation. It does not describe the response structure, but no output schema exists, and the return type ('segments') is reasonably clear. The 'config' parameter omission slightly reduces completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, so the description must compensate. It explains segment_type with enumerated values and query with examples, adding meaningful semantics. However, the 'config' parameter is completely undocumented in both schema and description, leaving a notable gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Browse Google Ads audience segments for campaign targeting' using a specific verb ('browse') and resource ('audience segments'). It also specifies the return value: 'Returns available audience segments filtered by type and optional search query', which distinguishes it from siblings like audience_recommendations or demographic_options.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: this is for campaign targeting and returns segments filtered by type and query. While it doesn't explicitly name alternative tools or give when-not-use cases, the context is sufficient for an agent to infer when this tool is appropriate.

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

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