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

Beyond the annotations, the description discloses key behavior: the source image and existing library creative remain unchanged, the result is a new standalone hosted URL, it is not automatically attached to an ad, and AI edits may alter text or visual details outside the requested region. These details are highly relevant for a non-destructive but open-world image-editing tool.

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 the core action and result, then adds only the operational caveats that matter: source preservation, standalone output, non-attachment, and AI edit variability. There is no redundant or filler language.

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?

For a mutation-style generation tool with no output schema, the description sufficiently explains the return value and side-effect behavior. It could still mention credit consumption or other operational constraints, but it covers the essential call semantics.

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 all three parameters are already well documented. The description reinforces that image_source is an existing image, edit_instruction carries the desired edits, and domain supplies brand context, but it adds little beyond the schema itself.

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 and resource: 'Create an AI-edited copy of an existing image' using edit instructions and brand context. This clearly distinguishes the tool from generation-from-scratch siblings by emphasizing that the source must already exist.

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?

It gives clear context for when to use the tool: editing an existing image and receiving a standalone hosted result rather than an attached ad creative. It also names upload_image_creative as the follow-up for storing the result, but it does not explicitly contrast this tool with generate_brand_creative or generate_flexible_brand_creative.

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