Server Quality Checklist

Tool Scores

• vision_helper_list_modelsA
  4.2/5.0
  Behavior4/5

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

  The annotation already covers read-only, idempotent, non-destructive behavior, so little additional safety disclosure is needed. The description adds useful behavioral context about the live nature of OpenRouter availability and what the result contains: model IDs, context length, and input price.

  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 front-loaded with the main purpose and organized into clear functions: what the tool lists, when to use it, how to narrow/paginate, and what is returned. It is efficient but slightly repeats the picking-a-model idea across the first two clauses.

  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?

  Since there is no output schema, the description usefully specifies the return contents: model IDs, context length, and input price. Combined with the annotations, it gives an agent everything needed to select and invoke the tool correctly.

  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?

  Input schema coverage is 100%, so the schema already documents limit, offset, and search well. The description adds a small amount of practical guidance about search and pagination, but does not materially extend the schema's meaning beyond paging and search usage.

  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?

  States the exact action: list vision-capable models currently available on OpenRouter. Purpose is further clarified with concrete use cases, such as finding a valid model ID when a configured model fails, and the resource is clearly distinct from the sibling analyze_image and check_config tools.

  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?

  Clearly says when to use the tool: when a configured model fails, when asked what models are available, or when choosing a model for image analysis. It gives practical navigation guidance via search and pagination, though it does not explicitly name alternatives or state when NOT to use it.

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

• vision_helper_check_configA
  4.4/5.0
  Behavior4/5

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

  Annotations already declare readOnly and idempotent, so safety is covered. The description adds useful details: it reports the API key status (masked), model selection, and limits, giving insight into the output and behavior beyond the annotations. It doesn't describe the return format, but the key masking and reporting specifics add transparency.

  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 concise, consisting of two clear sentences. It provides essential information without unnecessary elaboration, and the key details (what it reports, masking) are front-loaded. Every word contributes to the tool's clarity.

  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?

  The description covers purpose, usage trigger, and key output details (reports, masks key, lists models/limits). It doesn't describe the exact return format, but for a simple config check, this is likely sufficient. The tool is well-contextualized within the sibling set.

  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?

  The tool has no parameters, so the input schema is fully covered (100% coverage). The description does not add parameter-related information, but none is needed. Baseline score of 3 is appropriate given no parameters exist.

  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 uses the specific verb 'Diagnose' and clearly identifies the resource as 'vision analysis configuration problems'. It unambiguously states the tool's purpose and differentiates it from the sibling tools through its action and scope.

  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 explicitly states when to use the tool: 'Run this when analysis fails with a missing-key or configuration error.' This provides clear usage context and indicates the tool is for troubleshooting, even without referencing alternatives.

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

• vision_helper_analyze_imageA
  4.7/5.0
  Behavior5/5

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

  The description discloses behavior beyond annotations: high reasoning effort, high-quality model, automatic retry and fallback, quick mode with ~1024-token output, supported image formats, up to 5 images for comparison, and truncation at 25000 characters. These traits are not present in the annotations, which only declare read-only, open-world, idempotent, non-destructive hints. No contradiction.

  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?

  Three paragraphs, each serving a purpose: purpose/usage, default vs quick mode, and input formats/limits. Front-loaded with the core action and usage. No filler words.

  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 six parameters and no output schema, the description covers all essential aspects: input types, model selection (default and quick), prompt customization, token limits, truncation, and retries/fallback. The output type is clarified as text. Sibling tools are checkable via vision_helper_list_models. Nothing critical is missing.

  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 input schema provides 100% description coverage for all six parameters, so baseline is 3. The description adds value by specifying image file types (PNG, JPEG, WebP, GIF), clarifying array usage for comparison (state the comparison in the prompt), and explaining quick mode behavior. This goes beyond the schema's generic 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?

  The description opens with a clear verb-resource pair: 'Analyze one or more images with a vision-capable model on OpenRouter and return the analysis as text.' It distinguishes itself from siblings (list_models, check_config) by the task type and explicitly states when to use it: 'whenever you need to know what is in an image.'

  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 provides clear usage context: 'Use this whenever you need to know what is in an image but you cannot see it yourself.' It also offers conditional guidance for quick mode vs default mode, specifying examples like yes/no, captions, or object checks. It doesn't explicitly mention sibling alternatives or when not to use, but the context is sufficient.

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