generate_ad_concepts

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates this is a generation/creation tool (not read-only) and provides important workflow guidance about parameter sourcing. However, it doesn't disclose other behavioral traits like rate limits, authentication needs, output format, or whether this creates persistent resources versus temporary concepts.

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 perfectly front-loaded with the core purpose in the first sentence, followed by essential usage guidance. Every sentence earns its place by providing critical information about parameter sourcing and workflow constraints. No wasted words or redundant 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 (so return values are documented elsewhere), no annotations, and 3 parameters with 0% schema coverage, the description does well by explaining the critical product_id parameter workflow. However, it leaves ad_type and ad_objective parameters completely unexplained, which is a gap for a tool with multiple parameters.

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?

With 0% schema description coverage, the description must compensate. It provides crucial semantic guidance for the product_id parameter (must come from list_products, match user mentions, use internal ID). However, it doesn't explain the semantics of ad_type or ad_objective parameters, which have defaults but no explanation of what values are valid or what they mean.

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 specific action ('generate multiple ad creative concepts') and the target resource ('for an existing product in the system'), distinguishing it from siblings like generate_ad_from_url or analyze_* tools. It provides a complete verb+resource+scope statement.

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 explicitly states when to use this tool ('for an existing product in the system') and provides clear prerequisites ('product_id must come from list_products'). It also gives specific guidance on parameter sourcing ('match the product name the user mentions, then pass the corresponding internal ID') and what not to do ('Never ask the user to provide a product ID').

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