generate_ad_from_url

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that 'Brand guidelines are resolved server-side,' which adds useful context about how inputs are handled. However, it lacks details on critical behaviors like whether this is a read-only or mutation operation, potential rate limits, error handling, or what the output entails (though an output schema exists). For a tool with no annotations, this is insufficient.

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 highly concise and well-structured: three sentences that efficiently convey purpose, parameter guidance, and server-side behavior. Each sentence adds clear value without redundancy, making it easy to parse and front-loaded with key information.

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 has an output schema (which handles return values) but no annotations and 0% schema coverage, the description is moderately complete. It covers the core purpose and parameter usage but misses behavioral details like mutation status or error cases. For a tool with 5 parameters and no annotations, it should provide more context to be fully adequate.

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 explains that 'product_url' is the only required parameter and others have 'smart defaults,' adding meaning beyond the bare schema. However, it doesn't describe what the other parameters (objective, platform, ad_type, aspect_ratio) do or their possible values, leaving significant gaps. With 0% coverage, the description provides some but not enough semantic detail.

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 tool's purpose: 'Generate an ad creative concept from a product URL.' It specifies the verb ('generate'), resource ('ad creative concept'), and input source ('from a product URL'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'generate_ad_concepts', which might have overlapping functionality, so it doesn't reach a perfect score.

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 some usage guidance by stating 'Only ask the user for product_url — all other params have smart defaults,' which implies when to use this tool (for quick generation with defaults) and hints at alternatives (tools requiring more parameters). However, it doesn't explicitly name when-not-to-use scenarios or specific sibling alternatives, leaving some ambiguity.

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