novelai_generate_image

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 mentions supported prompt styles and output options like transparent background and custom dimensions, but it does not disclose side effects (e.g., file saving, output format, API costs, rate limits) or any destructive actions. The agent is left uninformed about what happens after generation, such as whether the image is returned, saved to disk, or requires further steps.

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, tightly written sentence that front-loads the core purpose and highlights the most salient features. There is no filler, and every clause adds relevant information about capabilities. This is appropriately concise for a tool with such a broad feature set.

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's complexity (22 parameters, no output schema), the description is significantly under-specified. It does not explain the return value, how the generated image is delivered, or the meaning of advanced parameters. The absence of any output schema means the description should at least hint at the result format, but it does not. An agent would struggle to correctly configure the tool beyond the basics.

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 does mention transparent background and custom dimensions, which map to the 'transparent' and 'width'/'height' parameters, and it hints at prompt flexibility (natural language, Danbooru tags, multilingual). However, the description does not explain the meaning or effect of most parameters (e.g., scale, steps, sampler, cfg_rescale, dynamic_thresholding), leaving the agent to guess for 18+ parameters.

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 clear verb ('Generate') and resource ('anime/art images') and specifies the models used. It is distinct from sibling tools like upscale, img2img, and inpaint, which have different purposes. The capability list (natural language, Danbooru tags, transparent background, custom dimensions) makes the tool's scope unambiguous.

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 does not mention scenarios where img2img, inpaint, or vibe_transfer would be more appropriate, nor does it state any exclusions or prerequisites. The only hint is the mention of model priorities, which is about model selection, not usage context.

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