generate_image

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

With no annotations, the description carries the full behavioral burden and handles it well. It discloses side effects such as creating out_dir, model compatibility constraints, exact-size resizing behavior, seed reproducibility, and the return value of saved file paths.

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 front-loaded with its core purpose and follows with a tight bulleted Args section. Every sentence adds operational value, and the length is justified by the complexity of seven parameters with conditional constraints.

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?

For a seven-parameter generation tool with no annotations, this is remarkably complete. It covers required inputs, optional customizations, model selection, image-to-image requirements, resizing behavior, and what the tool returns, leaving no critical gap for an agent to call it correctly.

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 explain every parameter, and it does. Each parameter receives meaningful detail, including examples, defaults, conditional requirements, and interaction rules between image and model, and between size and aspect_ratio.

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 identifies the action and target: 'Generate an image with Siray and save it into the current project.' It gives a specific verb and resource, but it does not explicitly distinguish itself from the sibling generate_backdrop tool, so it is clear without full sibling differentiation.

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 gives strong parameter-level usage guidance: when to pass size, when to ignore aspect_ratio, and when an -i2i/-edit model is required. It references list_models() for the live model list, but it does not provide explicit when-to-use versus generate_backdrop guidance.

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