Server Quality Checklist

Tool Scores

• list_model_idsB
  3.4/5.0
  Behavior2/5

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

  With no annotations provided, the description must fully disclose behavioral traits. It only states the action without mentioning if it is read-only, requires authentication, has rate limits, or describes the output format. This minimal disclosure is insufficient for an agent to understand the tool's behavior.

  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 consists of two short, front-loaded sentences with no redundant information. Every word adds value, making it highly concise 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?

  Despite having a single parameter and no output schema, the description fails to mention the return format (e.g., list of strings) or behavior when the optional 'provider' is omitted. This lack of completeness could lead the agent to misuse the output.

  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% coverage for the one parameter 'provider' with description 'Filter by provider'. The tool description adds no additional meaning beyond the schema. Baseline score of 3 is appropriate since the schema already handles parameter clarity.

  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 all available model IDs for a provider, using the verb 'List' and the resource 'model IDs'. It differentiates from sibling tools like compare_models, get_model, and query_models by focusing on ID enumeration rather than details or comparisons.

  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 hints at usage with 'Useful for finding exact API identifiers', but does not explicitly state when not to use this tool or mention alternatives. The context from sibling names provides implicit guidance but the description itself lacks exclusion criteria.

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

• query_modelsB
  3.4/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries full burden. It only says 'filter by provider, type, or modality support' which adds minimal behavioral info. It omits return format, pagination, error handling, and any side effects. The schema details parameters but not overall behavior.

  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 purpose is front-loaded, and every part is functional. It efficiently conveys the tool's action and filter options.

  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?

  Despite 6 parameters and no output schema, the description does not explain what the response contains (e.g., model IDs, full details). It also lacks usage constraints, limits, or pagination behavior. For a search tool, this leaves significant gaps in understanding.

  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 baseline is 3. The description summarizes filter dimensions ('provider, type, modality support') but does not add significant meaning beyond what the schema already provides. The mapping from 'type' to 'model_type' is clear, but no extra context.

  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 'Search and filter' and clearly identifies the resource as 'AI models available via API'. It distinguishes from sibling tools (compare_models, get_model, list_model_ids) by focusing on search/filter versus comparison, single retrieval, or ID listing.

  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 when to use (when needing to find models by criteria) but does not explicitly state when not to use or provide alternatives. It mentions filter dimensions but lacks guidance on choosing between this and siblings like get_model for exact model lookup.

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

• get_modelA
  3.5/5.0
  Behavior2/5

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

  No annotations provided, so description carries full burden. States 'detailed information' but does not specify what fields are returned or any side effects. Minimal behavioral disclosure.

  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?

  Single sentence, no wasted words. Clearly conveys the essential purpose.

  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?

  Low complexity tool with 1 parameter and no output schema. Description is adequate but lacks specifics about what 'detailed information' includes, leaving some ambiguity.

  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%. Description merely restates 'by its API ID' which is already in the schema parameter description. Adds no new meaning.

  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?

  Description clearly states verb (Get), resource (model), and method (by its API ID). Distinguishes from siblings like compare_models and list_model_ids.

  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?

  Implied usage (when you have a model ID and want details), but no explicit when-to-use or when-not-to-use compared to siblings. No alternatives mentioned.

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

• compare_modelsA
  3.9/5.0
  Behavior3/5

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

  No annotations exist, so the description carries the burden. It implies a read operation ('compare') but does not explicitly state it is non-destructive or disclose output details.

  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 zero wasted words, efficiently conveying the tool's purpose and required input. Front-loaded for quick understanding.

  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 one-parameter tool, the description is functional but lacks detail on what 'detailed comparison' entails. No output schema, so additional context on return format would improve completeness.

  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% for the single parameter 'model_ids', which is well-described in the schema. The description adds no new semantic meaning beyond what the schema provides.

  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 action ('Compare specific models side-by-side') and resource, distinguishing it from siblings like 'get_model' (single model) and 'list_model_ids' (listing IDs).

  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 instructs to 'Provide model IDs to get a detailed comparison,' but lacks explicit when-to-use or when-not-to-use guidance relative to sibling tools. Implicit differentiation is present.

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