chatgpt_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 of behavioral disclosure. It clearly explains side effects: opens a fresh chat, optionally uploads reference images, submits the prompt, waits for completion, and writes a PNG to disk. It also discloses authentication requirements and a realistic performance caveat (~60-120s), giving the agent important operational expectations.

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 well-structured and front-loaded with the core purpose, followed by the workflow, prerequisites, return value, and performance warning. Every sentence adds useful information; there is no filler or redundancy.

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 moderate complexity, the absence of annotations, and the absence of an output schema, the description is remarkably complete. It covers behavior, prerequisites, return data (saved path and pixel dimensions), and a critical timeout consideration. An agent has enough context to invoke 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 100%, so the schema already documents all four parameters. The description adds some color, such as reference images being used for inputs like a brand logo and output being a PNG at output_path, but it does not provide substantial meaning beyond what the input schema already states.

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 tool's purpose: generate or edit an image on chatgpt.com, save it to disk in one call. It uses specific verbs and resources, and describes the full pipeline. However, it does not explicitly distinguish itself from the sibling chatgpt_generate_batch, so an agent must infer which one to choose based on 'ONE call' wording.

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: requires an authenticated chatgpt.com session, instructs to import cookies first via cookie_import, and warns to set timeout_ms because generation is slow. It does not explicitly state when to use this tool versus chatgpt_generate_batch or other image-related tools, so it stops short of full when/when-not guidance.

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