add_audience_targeting

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

With no annotations, the description carries the full burden for behavioral disclosure. It discloses the fail-closed rule for bid adjustments, notes that the read-side fault is non-applicable, and includes a live verification timestamp, which adds credibility and context. It does not cover idempotency or response format, but the key behavioral constraints are well documented.

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 verbose but every sentence carries critical information: the core action, the namespace disambiguation, the bid adjustment constraint, and the verification note. It is appropriately structured, front-loading the purpose and then supporting details. Not excessively wordy for the complexity involved.

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 4 parameters, no annotations, and no output schema, the description covers the most complex aspects (bid adjustment rules, audience_type enum) adequately. It does not mention return value, but with no output schema that is not required. It also omits any mention of prerequisites (e.g., campaign must exist), but those are likely implicit. Overall, it is complete enough for an agent to call 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 coverage is 0%, so the description must compensate. It explains audience_type as a namespace disambiguator and lists the valid enum values, and it explains the conditional semantics of bid_adjustment_pct. It does not explicitly describe campaign_id or audience_id, but their meaning is self-evident from the names and context. This is strong compensation given the schema offers no help.

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 clearly states the action ('Draft audience targeting on a campaign') with a specific resource (campaign) and distinct intent (adding audience targeting). It disambiguates the audience_type namespaces, which helps distinguish it from other audience-related tools like create_custom_audience, making its purpose unambiguous.

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 provides clear usage context by explaining when bid_adjustment_pct is allowed (only with manual bidding strategies) and when it is rejected, which is a concrete usage condition. It does not explicitly mention alternatives or when not to use the tool, but the functional condition is a useful guide, and the 'on a campaign' phrasing implies an existing campaign context. Missing explicit comparisons to siblings prevents a 5.

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