img-gen

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Create images' implies a generative/mutation operation, the description lacks critical behavioral details: it doesn't mention authentication requirements, rate limits, cost implications, quality expectations, or what happens when generation fails. For a generative AI tool with zero annotation coverage, this is a significant gap.

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 efficiently structured with clear sections (Args, Returns) and uses minimal sentences. The first sentence directly states the purpose, and subsequent sections provide necessary information without redundancy. However, the 'Args' section could be more integrated with the main description rather than appearing as a separate bullet.

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 covers return values) and only one parameter, the description is reasonably complete for basic understanding. However, for an AI image generation tool with no annotations, it should provide more context about behavioral characteristics like generation time, supported image formats, resolution options, or usage limitations to be truly complete.

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 description provides basic semantic information about the single parameter ('A prompt to generate the image using image generation model'), but with 0% schema description coverage, this doesn't fully compensate. The description doesn't specify prompt format requirements, length constraints, style guidance, or what makes an effective prompt. Baseline 3 is appropriate as the description adds some value but doesn't fully address the coverage gap.

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 with 'Create images based on the prompt' - a specific verb ('Create') and resource ('images') with the mechanism ('based on the prompt'). However, without sibling tools, there's no opportunity to differentiate from alternatives, so it cannot achieve a perfect score of 5.

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 no guidance on when to use this tool versus alternatives. It simply states what the tool does without any context about appropriate use cases, prerequisites, or limitations. There's no mention of when this tool would be preferred over other image generation methods.

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