Server Quality Checklist

Tool Scores

• pixara_list_image_modelsA
  4.5/5.0
  Behavior4/5

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

  Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds that it is a no-cost call (no image generated), providing useful behavioral context beyond the annotations.

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

  Conciseness4/5

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

  The description is well-structured with clear sections (Args, Returns, Examples) and front-loaded key points. Though somewhat long, every sentence earns its place.

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

  Completeness4/5

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

  Given 8 parameters and no output schema, the description adequately covers return formats for both JSON and Markdown. It provides sufficient context for a discovery tool, though more detail on pagination behavior could be added.

  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?

  Schema coverage is 100%, giving a baseline of 3. The description adds semantic meaning by explaining each filter's purpose (e.g., case-insensitive substring match) and output format behavior, enhancing understanding.

  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 states the tool lists image-generation models with filtering and pagination. It distinguishes itself from siblings by specifying it is a read-only discovery call before using pixara_generate_image or pixara_edit_image.

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

  Usage Guidelines5/5

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

  Explicit when-to-use and when-not-to-use examples are provided, such as 'Use when: What image models can do transparent backgrounds?' and 'Don't use when you already know the exact model ID.' It also references sibling tools.

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

• pixara_edit_imageA
  4.8/5.0
  Behavior5/5

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

  Annotations (readOnlyHint=false, destructiveHint=false) are supplemented by the description's disclosure that the tool saves images to disk, handles encoding of local files, and returns a Markdown summary. It also includes error handling details. No contradictions.

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

  Conciseness4/5

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

  The description is well-structured with sections (general, Args, Returns, Examples, Error Handling). It is comprehensive but not excessively long. Could be slightly more concise, but it 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?

  Given the tool's complexity (15 params, nested objects, no output schema), the description covers purpose, usage, all parameter categories, return format, and error scenarios. It is sufficiently complete for an AI agent to invoke 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?

  Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the three input_reference source types (file, url, base64) and automating local file reading. It groups some parameters by referencing pixara_generate_image, which is efficient but assumes knowledge of that tool.

  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 states it edits/transforms an existing image using a text prompt and reference images. It specifies the action (edit/transform), resource (image), and method (via OpenRouter). It distinguishes from sibling pixara_generate_image by noting when not to use it (no reference image).

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

  Usage Guidelines5/5

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

  The description provides explicit examples ('Use when: ...', 'Don't use when: ...') and advises checking model capabilities with pixara_get_model_details before selecting a model. This gives clear guidance on when to invoke this tool vs alternatives.

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

• pixara_generate_imageA
  4.8/5.0
  Behavior5/5

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

  Discloses that the tool saves images to disk, calls OpenRouter's Image API (not chat), and returns file paths and cost. No annotation contradictions; adds context beyond annotations such as error handling and environment variable usage.

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

  Conciseness4/5

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

  Well-structured with sections: summary, args, returns, examples, error handling. Slightly lengthy but justified by the tool's complexity (14 params); no unnecessary sentences.

  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?

  No output schema but describes return format adequately. Covers error scenarios, environment variable defaults, and sibling tool references. Thorough for a complex tool.

  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?

  Schema coverage is 100%, baseline 3. Description adds significant value by explaining parameter constraints (e.g., n>1 not universal), mutual exclusivity rules, and defaults, surpassing basic schema descriptions.

  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?

  Clearly states the tool generates images from text prompts using OpenRouter models. Distinguishes itself from sibling pixara_edit_image by explicitly noting it does not edit or use reference images.

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

  Usage Guidelines5/5

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

  Provides explicit when-to-use and when-not-to-use examples, plus alternatives like pixara_edit_image for editing. Also references pixara_list_image_models for model discovery and error handling guidance.

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

• pixara_get_model_detailsA
  4.9/5.0
  Behavior5/5

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

  Annotations already declare readOnlyHint, idempotentHint, destructiveHint. The description adds that the call is 'no-cost' and explains that unsupported parameters are silently ignored or rejected, justifying why checking first is important. No contradictions.

  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?

  The description is well-structured with clear sections (main description, args, returns, examples, error handling). It is front-loaded with the primary purpose and every sentence adds meaningful information without redundancy.

  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?

  Even without an output schema, the description details the return structure (per-provider pricing, parameter descriptors, passthrough options). It also covers error scenarios. All aspects of the tool's usage are covered comprehensively.

  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?

  Schema coverage is 100%, so baseline is 3. The description adds example model slugs and clarifies the response_format options with practical examples ('markdown' for humans, 'json' for machines), adding value beyond the schema.

  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 states the tool retrieves per-provider pricing, supported parameters, and passthrough options for a single OpenRouter model. It uses specific verbs ('Get', 'confirm') and distinguishes itself from sibling tools like pixara_generate_image, pixara_edit_image, and pixara_list_image_models.

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

  Usage Guidelines5/5

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

  Explicit guidance: use before generate/edit to avoid wasted calls, and avoid when browsing many models (suggesting pixara_list_image_models). Provides example use cases and error handling instructions.

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