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

Beyond the annotations, the description discloses non-obvious behavior: the call consumes monthly generation allowance and requires a follow-up poll to get_ad_generation. It also surfaces the quote prerequisite. This is meaningful behavioral context that the annotations alone do not provide.

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 short, front-loaded with the core purpose, and contains no fluff. The layout sentence is somewhat redundant with the schema but is still compact and useful. Structure is strong, if slightly informal with the lowercase 'layout.'

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 that an output schema exists and the input schema covers all parameters, the description is mostly complete: it covers the async polling pattern, quota usage, and quote prerequisite. It could be slightly richer by naming sibling alternatives, but an agent has enough to call 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 100%, so the schema already documents all parameters. The description largely repeats what the schema states, such as layout values and the optional quoteId flow. It adds no new parameter-level meaning beyond the structured definitions.

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 states a specific verb ('Generate') and resource ('Ad Lab stills'), and it clarifies the output format via the layout options. It doesn't explicitly distinguish this from sibling tools like generate_ad_studio or generate_ad_proof_pack, though 'stills' narrows the scope considerably.

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 useful context: it consumes the monthly generation allowance, requires polling get_ad_generation, and implies quotes should be generated first when quoteId is omitted. However, it never explicitly says when to use this tool versus alternatives or when not to use it, so usage guidance remains mostly implied.

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