get_targeting_options_tool

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

With no annotations provided, the description carries the full burden, and it delivers the key behavioral facts: it returns a list of interest categories, specifies the returned fields, and notes optional filtering by objective_type. It does not discuss pagination or error behavior, but for a simple read-style getter the disclosed behavior is sufficient.

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?

Four concise sentences flow logically: what it does, what it returns, how to use the output, and the optional filter. Every sentence adds useful information, and the purpose is front-loaded with no 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?

The output schema covers return-value structure, so that gap is already filled. The description covers purpose, usage context, and the optional parameter. The main missing piece is a clearer explanation of advertiser_id's role in determining the available categories, but the overall definition is strong enough for an agent to invoke it correctly.

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 does explain objective_type with example values ('TRAFFIC', 'CONVERSIONS') and optionality, but advertiser_id—a required parameter—receives no semantic explanation beyond the schema title 'Advertiser Id.' This is partial compensation only.

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 opens with a specific verb and resource: 'Get all available interest categories for audience targeting.' It also lists the returned fields (IDs, names, levels, sub-category IDs), making the tool's purpose unmistakable and distinct from siblings like get_audience_reach_tool, which is about audience size rather than interest taxonomy.

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 operational context: 'Use the returned interest_category_id values when setting up ad group targeting' and explains the optional objective_type filter. It does not explicitly mention alternatives or when not to use this tool, but the intended use case is clear enough.

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