review_image

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

No annotations are provided, so the description carries the full disclosure burden. It adds genuinely useful behavioral context: cost ('one small vision chat call, well under $0.01'), the shape of the return value, and a portability trait (works in every MCP client). It stops short of stating whether the call has side effects or how it behaves on failure, which keeps it from a 5.

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 sentences, front-loaded with the core purpose, then usage context, then a cost note. Every sentence carries distinct information and none of it repeats what the input schema already states.

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 3-parameter tool with 100% schema coverage and no output schema, the description covers what it returns, when to call it, and what it costs. The only gaps are error behavior and an explicit statement that the operation has no side effects, which are minor for a review-style read 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 description coverage is 100%, so the baseline is 3. The description adds workflow context by implying image_url is typically 'a URL returned by generate_image' and framing brief as the original generation prompt, but the schema already documents both parameters thoroughly, so the marginal gain is modest.

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 ('Have a vision model look at an image and critique it against a brief') and enumerates the output: what matches, what is wrong (garbled text, composition, colors, artifacts), and a revised prompt. The explicit placement as the follow-up to generate_image distinguishes it from the generation siblings without needing to open any schema.

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?

'Use it after generate_image to check the result and decide whether to regenerate' is an explicit trigger condition with a clear decision outcome. The clause 'works in every MCP client, including ones that do not pass tool-result images to you' gives a concrete reason it beats the alternative of relying on native image display.

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