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. It clearly discloses that the image is written to disk and the path is returned (not inline), and it specifies dimension constraints. However, it does not disclose error behavior, permission requirements, rate limits, or what happens if constraints are violated, leaving room for improvement.

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 two sentences, front-loaded with the core purpose and output format, followed by prompt guidance and constraints. Every sentence is necessary and informative, with no redundancy or wasted words. It is highly 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 the tool has 4 parameters, no output schema, and no annotations, the description covers the essential aspects: purpose, output format, constraints, and prompt advice. It is mostly complete but lacks details on error handling, performance, or any prerequisites, which would be nice to have for a generation tool.

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%, so the description adds value beyond the schema by explaining the dimension constraints (min 768px sides, max 1048576 total pixels) and examples of valid sizes. It also adds context about prompt quality. The fact that the tool returns the path is not in the schema but is in the description. This meaningfully supplements the parameter definitions.

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 generates a PNG image using gpt-image-2 on Azure AI Foundry, and distinguishes it from the sibling tools 'edit_image' (editing) and 'check_config' (configuration checking). The verb 'generate' and resource 'PNG image' are specific, and the output behavior (written to disk, returns path) is explicitly noted.

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 actionable guidance: 'Use a detailed prompt covering subject, style, composition, lighting and colors.' It also gives explicit dimension constraints (minimum side 768px, max total pixels 1048576) with valid examples. However, it does not explicitly state when to use this tool versus alternatives (e.g., edit_image), nor does it mention any prerequisites or context for using the tool.

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