generate_data_table

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It only states the generation action without clarifying whether the tool writes to disk, returns a string, or requires a specific project context. This is a significant gap for a code generation 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 a single, direct sentence that gets straight to the point without fluff or repetition.

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 simple parameter set and full schema coverage, the description is adequate but not rich. It lacks explicit differentiation from sibling generators and does not describe the return format, which the missing output schema would otherwise clarify.

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?

The input schema provides complete descriptions for all three parameters (module, properties, structName) with 100% coverage, so the description adds no parameter information. Baseline of 3 is appropriate.

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 generates a USTRUCT specifically for DataTable row structures, using the verb 'generate' and identifying the concrete deliverable. This distinguishes it from sibling tools like generate_uclass or generate_actor_component that target different code generation needs.

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 context for when to use this tool: whenever a struct is needed as a DataTable row. However, it does not explicitly mention alternatives or 'when not to use' scenarios, though the purpose is specific enough to infer.

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