Server Quality Checklist

Tool Scores

• chat_with_modelC
  2.9/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden for behavioral disclosure. It states the basic action but reveals nothing about authentication requirements, rate limits, cost implications, response format, error handling, or whether this initiates a new conversation versus continues an existing one. For a tool that likely involves API calls with potential costs, this is a significant gap.

  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 a single, efficient sentence that states the core functionality without any unnecessary words. It's perfectly front-loaded with the essential information, making it immediately clear what the tool does.

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

  Completeness2/5

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

  For a tool with 5 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, how responses are structured, or important behavioral aspects like conversation state management. The agent would need to guess about the response format and operational characteristics.

  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 parameters are documented in the schema. The description adds no additional parameter semantics beyond what's already in the structured schema, which provides clear descriptions for each parameter including defaults for optional ones. This meets the baseline expectation when schema coverage is complete.

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

  Purpose4/5

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

  The description clearly states the action ('Send a message') and target resource ('specific OpenRouter model'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'compare_models' or 'get_model_info', which have different purposes but operate on the same resource domain.

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

  Usage Guidelines2/5

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

  The description provides no guidance on when to use this tool versus alternatives like 'compare_models' or 'list_models'. There's no mention of prerequisites, appropriate contexts, or exclusion criteria, leaving the agent to infer usage from the tool name alone.

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

• compare_modelsC
  2.9/5.0
  Behavior2/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal insight. It states what the tool does (compare responses) but doesn't describe how the comparison is performed, what the output format looks like, whether it's a read-only operation, or any performance considerations like rate limits or latency.

  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 extremely concise at just four words, front-loading the core purpose without any wasted text. Every word earns its place by directly conveying the tool's function, making it efficient and easy to parse.

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

  Completeness2/5

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

  Given the complexity of comparing multiple model responses and the lack of annotations or output schema, the description is insufficient. It doesn't explain what 'compare' entails (e.g., side-by-side display, metrics, or qualitative analysis), the return format, or error handling, leaving significant gaps for the agent to navigate.

  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 description adds no parameter-specific information beyond what's already in the schema, which has 100% coverage with clear descriptions for 'models', 'message', and 'max_tokens'. Since the schema fully documents the parameters, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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

  Purpose4/5

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

  The description 'Compare responses from multiple models' clearly states the verb (compare) and resource (responses from multiple models), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'chat_with_model' or 'get_model_info' beyond the comparative nature implied by 'compare'.

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

  Usage Guidelines2/5

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

  The description provides no guidance on when to use this tool versus alternatives like 'chat_with_model' (for single-model interaction) or 'list_models' (for enumeration). There's no mention of prerequisites, typical use cases, or exclusions, leaving the agent to infer usage from the tool name alone.

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

• get_model_infoC
  2.9/5.0
  Behavior2/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'gets' information, implying a read-only operation, but doesn't clarify if it requires authentication, has rate limits, returns structured data, or handles errors. This leaves significant gaps for a tool with no annotation coverage.

  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 a single, efficient sentence that directly states the tool's function without unnecessary words. It could be slightly improved by front-loading key details like the required parameter, but it's appropriately sized and clear.

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

  Completeness2/5

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

  Given no annotations and no output schema, the description is incomplete. It doesn't explain what 'detailed information' includes, how results are structured, or behavioral aspects like error handling. For a tool with rich potential output and no structured support, more context is needed.

  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 input schema has 100% description coverage, with the 'model' parameter documented as 'Model ID to get information about'. The description adds no additional meaning beyond this, such as format examples or valid ID sources. Baseline 3 is appropriate since the schema does the heavy lifting.

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

  Purpose4/5

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

  The description clearly states the verb ('Get') and resource ('detailed information about a specific model'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_models' (which might provide summary vs detailed info) or 'compare_models' (which might compare multiple models), missing full sibling distinction.

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

  Usage Guidelines2/5

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

  The description provides no guidance on when to use this tool versus alternatives like 'list_models' or 'compare_models'. It doesn't mention prerequisites, such as needing a model ID, or context for when detailed info is required over other operations.

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

• list_modelsB
  3.2/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe how it behaves - no information about rate limits, authentication requirements, response format, pagination, or whether this is a read-only operation. The description is functional but lacks behavioral context.

  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 a single, efficient sentence that states exactly what the tool does without any wasted words. It's appropriately sized for a simple list operation and gets straight to the point.

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

  Completeness3/5

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

  For a simple list operation with no parameters and no output schema, the description is adequate but minimal. It tells what the tool does but doesn't provide context about the return format, filtering options, or how this differs from similar tools. Given the simplicity of the tool, it's minimally viable but could be more helpful.

  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 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and it doesn't 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.

  Purpose4/5

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

  The description clearly states the verb 'Get' and resource 'list of available OpenRouter models', making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_model_info' or 'compare_models', which might also involve retrieving model information.

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

  Usage Guidelines2/5

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

  The description provides no guidance on when to use this tool versus alternatives like 'get_model_info' or 'compare_models'. There's no mention of prerequisites, context, or specific use cases that would help an agent choose between these sibling tools.

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