start_image_batch

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

With no annotations provided, the description carries full burden and does well. It discloses key behavioral traits: the tool blocks until the first image is ready, generates remaining images in the background, returns a session ID for retrieval, and specifies the return structure. It doesn't mention rate limits, authentication needs, or error conditions, but covers the core execution behavior adequately.

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 perfectly structured and concise. It starts with a clear purpose statement, explains the execution behavior, lists all parameters with brief explanations, and describes the return value. Every sentence earns its place with no wasted words, and information is front-loaded appropriately.

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 (batch generation with background processing), no annotations, and the presence of an output schema, the description is mostly complete. It explains the execution model, parameters, and return structure. However, it doesn't mention error handling, rate limits, or how the session ID should be used with sibling tools like 'get_next_image', leaving some gaps.

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?

With 0% schema description coverage, the description compensates well by documenting all 6 parameters with clear semantics. It explains what each parameter controls (prompt=description, count=number of images with range, model=generation model, size=image size, quality=image quality with options, style=image style with options). This adds significant value beyond the bare schema.

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: 'Start generating multiple images and return the first one.' It specifies the verb ('start generating'), resource ('multiple images'), and distinguishes it from sibling tools like 'generate_image' (single image) and 'get_batch_status' (status check). The description explicitly mentions it returns the first image immediately while generating others in the background.

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 clear context about when to use this tool: for generating multiple images where you need the first one immediately and can retrieve others later. It distinguishes from 'generate_image' (single image) and 'get_batch_status'/'get_next_image' (retrieval tools). However, it doesn't explicitly state when NOT to use it or compare all alternatives in detail.

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