get_targeting_suggestions

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

No annotations are provided, so the description carries the behavioral burden. It discloses the return shape ('A dictionary containing suggested targeting options') and the input/output relationship, but it doesn't mention side effects (none implied), auth requirements, or rate limits. For a read-style suggestion tool this is adequate but not rich.

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 a one-sentence purpose, followed by a compact Args/Returns docstring. There is no filler; the example is the only extra and it earns its place.

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?

With three parameters, a nested object, and no annotations, the description covers all required and optional inputs and states the return type. It is complete enough for an agent to invoke correctly; minor gaps like pagination or output details are covered by the output schema and are not fatal.

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%, and the description compensates by documenting all three parameters: act_id with an example, targeting_spec with a concrete JSON example, and limit with its meaning. The example for the nested targeting_spec adds real value beyond the schema's additionalProperties object.

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 uses a specific verb ('Get'), names the resource ('targeting suggestions'), and anchors the operation to an existing targeting spec with an 'expand interests' example. It is clear on its own, but it doesn't explicitly differentiate from sibling tools like search_targeting_options or get_targeting_sentence_lines.

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 conveys the key usage context: call this when you already have a targeting spec and want suggestions derived from it. It doesn't state when not to use it or name alternative sibling tools, but the 'based on an existing targeting spec' condition is clear enough to guide selection.

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