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

With no annotations present, the description carries the burden of behavioral disclosure. It usefully discloses transport-dependent behavior: SSE/HTTP auto-save files and return URLs, while stdio requires a filepath. However, it omits external API dependencies, authentication, network failure behavior, and whether output files may be overwritten, which is important for an editing tool.

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 compact, front-loaded with the primary purpose, and contains no filler. The second sentence efficiently packs transport-specific behavior into one clause, making it easy to scan.

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 a tool with 12 parameters, no annotations, and no output schema, this description is incomplete. It covers the core purpose and one transport distinction, but it does not address return-value behavior for stdio, authentication, or error handling. Still, it provides essential context and is not misleading.

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 baseline is 3. The description adds meaning by clarifying that filepath is required for stdio and that SSE/HTTP transports auto-save files, which helps the agent understand the filepath parameter's role beyond its schema entry. Other parameters remain schema-documented, which is sufficient.

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 verb and resource: 'Edit image(s)' via the 'OpenAI Images Edit API.' The name and wording imply a distinction from the sibling generate_image, but it never explicitly names that alternative, so it falls just short of a 5.

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 implies use when editing existing images rather than generating new ones, and the sibling name generate_image hints at the alternative. However, there is no explicit when-to-use vs. when-not-to-use guidance, and it does not mention generate_image or other alternatives.

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

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

With no annotations provided, the description carries the burden of disclosing behavior. It usefully reveals that SSE/HTTP transports auto-save files and return URLs, which is behavioral context beyond the schema. Still, it does not mention other notable behaviors such as default overwrite behavior, moderation handling, or exactly what happens in stdio mode after generation.

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 short sentences with no filler. The primary purpose is front-loaded, and the transport nuance is stated efficiently. Every sentence earns its place.

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?

The description covers the tool's purpose and a key transport difference, and the schema fully documents the parameters. However, with 10 parameters, no annotations, and no output schema, an agent might still be unsure what to expect as a result in stdio mode or how this tool relates to edit_image. The description is adequate but not fully complete.

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 baseline is 3. The description adds almost no parameter-level detail beyond the schema; the only minor addition is the contextual note that stdio requires filepath, but that is already captured by the required field.

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 a specific action ('Generate image(s)') and resource ('with the OpenAI Images API'). It is easy to understand that this tool creates new images, and the sibling 'edit_image' suggests the complementary operation, though the description does not explicitly compare itself to that sibling.

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 gives transport-specific guidance: SSE/HTTP auto-save files and return image URLs, while stdio requires filepath. However, it does not explicitly explain when to choose this tool over edit_image; the use case is only implied by the tool name and the generate-vs-edit distinction.

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