generate_image

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

With no annotations, the description carries full burden. It discloses behavioral traits: stable endpoints, automatic model upgrades, pay-per-request with Bitcoin Lightning, and no signup needed. It also mentions return format (JSON with image URL). This is sufficient for safe invocation.

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 5 sentences and front-loaded with the main action. Every sentence adds unique value, though it could be slightly more concise. Still, it's well-structured and easy to parse.

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 4 parameters, no output schema, and no annotations, the description covers the essential aspects: payment requirement, model choices, img2img, automatic upgrades. It lacks mention of error handling or rate limits, but is fairly complete for a tool of this complexity.

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 coverage is 100%, but the description adds significant value beyond the schema: it explains the payment flow (requires create_payment with specific toolName), elaborates on model options with pricing and defaults, and clarifies the img2img use case for imageBase64. This makes the parameters much more understandable.

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 'Generate an image from a text prompt' and lists available models with their characteristics. It distinguishes this tool from siblings like analyze_image or edit_image by specifying its core function.

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 context on when to use the tool (generating images), mentions img2img capability, and explains the payment prerequisite. However, it doesn't explicitly state when not to use it compared to other image tools on the server.

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