generate_openai_image

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

No annotations exist, so the description carries the full burden. It discloses deployment location ('Runs in your Kuudo deployment, not here'), the auth mechanism (Bearer key), and the iteration semantics via previous_response_id. These are substantive behavioral traits, though rate limits, error behavior, and storage/retention are not covered.

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?

Three front-loaded sentences with zero filler. Purpose first, then sibling distinction, then auth, then iteration — each sentence earns its place and the key usage signal is stated up front.

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?

For an 11-parameter tool with no output schema, the description covers purpose, sibling routing, auth, and iteration. The schema handles parameter details. The main gap is the absence of return-value or error-behavior context, but that is partly mitigated by the absence of an output schema.

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 baseline is 3. The schema already documents every parameter richly (n as N server-side calls, size constraints, input_images URL resolution). The description adds only marginal meaning by framing previous_response_id as the OpenAI analog of Gemini's interaction_id.

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?

States a specific verb and resource: 'Generate images with OpenAI gpt-image-2 via the Responses API.' It distinguishes itself from the sibling generate_image (Google Gemini) by naming the provider explicitly, so an agent can tell the two apart immediately.

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?

Names the sibling generate_image and positions this tool as 'the additive OpenAI provider,' giving the selection criterion (which provider/API you want). It also discloses the auth prerequisite (Bearer key). The when-to-choose condition is slightly implied via provider naming rather than spelled out as an explicit rule.

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