Server Quality Checklist

Tool Scores

• generate_imageA
  4.1/5.0
  Behavior4/5

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

  The description adds concrete behavioral details beyond the annotations: it saves the image to local storage, returns an absolute path and file URI, and exposes that API costs are incurred. Annotations already indicate non-read-only and side-effecting behavior; the description enriches that with practical cost and persistence facts.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  A single sentence is front-loaded with the main action ('generate an image'), followed immediately by the return/side-effect behavior and the cost warning. It has no filler or duplication of schema information, and every character earns its place.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a 7-parameter tool with 100% schema coverage and a defined output schema, the description adds precisely the context that is not in structured data: persistence to local disk, the returned path/URI shape, and API fees. All the information an agent needs to call the tool correctly is covered by the description, schema, and annotations together.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100%, so all 7 parameters already carry detailed semantic descriptions and enums. The description only repeats that the prompt drives generation, adding no new parameter meaning. The baseline of 3 is therefore correct.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly specifies the action 'generate an image from GPT Image', the resource, and the deliverable: a local file with absolute path and file URI. It distinguishes itself from 'edit_image' (generating a new image vs modifying an existing one) and from 'check_endpoint', which is unrelated.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage by contextually framing a text-to-image generation task. It does not explicitly state when to prefer this over edit_image or check_endpoint, and it provides no exclusion criteria or when-not-to-use guidance, leaving that inference to the agent.

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

• edit_imageA
  4.5/5.0
  Behavior5/5

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

  Beyond annotations, the description discloses that it saves a new file and returns an absolute path without overwriting the original, and that the call incurs API costs. This adds meaningful behavioral context that annotations alone don't provide, and it doesn't contradict readOnlyHint=false or destructiveHint=false.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Four short sentences, front-loaded with the core purpose and followed by invocation guidance, output behavior, and cost warning. No filler; each sentence adds distinct value.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a 9-parameter tool with an output schema, the description covers the critical operational facts: local input requirement, reference-image handling, mask support, non-destructive output, returned absolute path, and cost. The schema handles parameter details, so nothing essential is missing.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%, so the baseline is 3. The description adds useful guidance about clarifying each reference image's role and what to preserve, which maps to images/prompt, but doesn't add detail beyond the already-rich schema for mask, size, format, or quality.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description opens with a specific verb and resource: it reads local images, edits them per prompt, replaces backgrounds, or generates new images from reference style/composition. This clearly differentiates it from the generate_image sibling by requiring local image input and an edit/reference workflow.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  It lists concrete use cases (edit, background replacement, reference-based generation), instructs users to clarify each reference image's role and what to preserve, and notes when to pass a mask for local edits. It doesn't explicitly name alternatives or exclusions, but the local-image/edit framing makes the appropriate context clear.

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

• check_endpointA
  4.7/5.0
  Behavior5/5

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

  Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds meaningful context beyond annotations by explicitly stating it sends no generation or editing requests and by warning that a passing check does not guarantee actual image capability. This is valuable behavioral nuance.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Two sentences with no wasted words. The primary action and purpose come first, followed by the critical limitation. Every sentence earns its place.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a zero-parameter diagnostic tool with full annotations and an output schema, the description covers purpose, side-effect absence, and the key limitation. The agent has everything needed to invoke and interpret this tool correctly.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The tool has zero parameters, so there is nothing for the description to clarify about parameter usage. The baseline of 4 applies because the description does not need to compensate for any schema gaps.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description states a specific action: request the current endpoint's model list and check the response format and model presence. It also explicitly distinguishes itself from the sibling tools generate_image and edit_image by stating it will not send generation or editing requests.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description clearly indicates when not to rely on this tool: even a successful check does not verify actual image capabilities, which require real invocation. It implies this tool is for endpoint/model-list validation, and the sibling names make the alternative clear, though it stops short of explicitly naming which sibling to use.

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