generate_image

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

No annotations are provided, so the description carries the full behavioral burden. It discloses base64/MIME output, but omits that display_mode defaults to "display" and would show the image rather than return base64, making the only behavioral claim conditional/inaccurate; it also says nothing about credit/cost implications.

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?

Two short sentences, front-loaded with the action and then the output format. There is no fluff; even though the second sentence is imprecise about display_mode, it is structurally efficient.

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 10 parameters, 11 sibling tools, and no annotations or output schema, the description is too thin for an agent to reliably select and invoke it. It lacks routing guidance, output mode semantics, and cost/credit context.

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 100% with detailed descriptions for all 10 parameters, so the descriptive burden is already met. The tool description adds no extra parameter meaning beyond tying generation to text prompts and models.

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 uses a specific verb and resource: "Generate images from text prompts", which clearly identifies the tool's core action and separates it from generate_video/generate_audio and from transform/enhance tools. The addition of "various AI models" and return format further clarifies scope.

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 phrase "from text prompts" implies the text-to-image use case, but there is no explicit when-to-use vs alternatives or any exclusions. With siblings like transform_image, enhance_image, and generate_video, the agent must infer routing from the resource noun alone.

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