Server Quality Checklist

Tool Scores

• get_task_resultC
  2.1/5.0
  Behavior1/5

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

  No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Get task result' implies a read operation, but it does not specify whether this is safe, requires authentication (though the schema includes an api_key), involves side effects, or details response behavior. The description lacks any behavioral traits beyond the basic action, making it inadequate for a tool with no annotation support.

  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 with just three words, 'Get task result', which is front-loaded and wastes no space. Every word directly contributes to stating the tool's purpose, making it efficient and well-structured for its minimal content.

  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 tool's complexity (a read operation with authentication) and lack of annotations and output schema, the description is incomplete. It does not explain what a 'task result' is, how results are returned, or any behavioral context. The schema covers parameters, but the overall tool behavior remains underspecified, leaving significant gaps for agent 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?

  The input schema has 100% description coverage, with clear documentation for 'taskId' and 'api_key'. The description adds no additional meaning beyond what the schema provides, as it does not explain parameter usage or constraints. According to the rules, with high schema coverage (>80%), the baseline score is 3 when no param info is added in the description.

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

  Purpose2/5

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

  The description 'Get task result' is a tautology that essentially restates the tool name 'get_task_result'. It specifies the verb 'get' and resource 'task result', but provides no additional context about what a 'task result' entails or how this differs from sibling tools like 'get_points' or 'image_to_video'. The purpose is minimally stated but lacks specificity and differentiation.

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

  Usage Guidelines1/5

  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. There are no indications of context, prerequisites, or exclusions, and it does not reference sibling tools or suggest when this tool is appropriate. This leaves the agent with no usage instructions beyond the tool name.

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

• get_pointsC
  2.3/5.0
  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. 'Get remaining points' implies a read-only operation, but it doesn't specify whether this requires authentication (though the schema shows an api_key parameter), what format the response returns, whether there are rate limits, or any side effects. The description adds minimal behavioral context beyond what's implied by the verb 'Get'.

  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 three words. It's front-loaded with the core action ('Get remaining points') and contains no unnecessary verbiage or redundant information. Every word serves a purpose in conveying the basic function.

  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 no annotations, no output schema, and a single parameter, the description is inadequate. It doesn't explain what 'points' are, what system they belong to, what format the response will have, or any behavioral characteristics. The agent would need to guess about the tool's purpose and output based on minimal information.

  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 schema has 100% description coverage (the api_key parameter is fully documented in the schema), so the baseline is 3. The description doesn't add any parameter-specific information beyond what's already in the schema - it doesn't explain how the api_key relates to 'remaining points' or provide additional context about parameter usage.

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

  Purpose2/5

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

  The description 'Get remaining points' is a tautology that essentially restates the tool name 'get_points' without adding meaningful specificity. It doesn't specify what kind of points (e.g., API usage points, user points, reward points) or from what system/context. While it includes a verb ('Get'), it lacks the resource specificity needed for clear differentiation from sibling tools like 'get_task_result' and 'image_to_video'.

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

  Usage Guidelines1/5

  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. It doesn't mention any prerequisites, context for usage, or relationship to sibling tools. There's no indication of whether this should be used before/after other operations or under what conditions 'remaining points' would be relevant.

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

• image_to_videoC
  2.9/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Convert image to animated video' implies a generative or processing operation, but it doesn't disclose critical traits like whether it's a read-only or destructive operation, authentication requirements (though hinted by api_key parameter), rate limits, or output format. For a tool with no annotations, this is a significant gap in 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 extremely concise with a single sentence 'Convert image to animated video', which is front-loaded and wastes no words. Every part of the sentence directly contributes to understanding the tool's purpose, making it efficient and well-structured.

  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 a generative video tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks information on behavioral aspects, output format, error handling, and usage context. The description should do more to compensate for the absence of structured data, making it inadequate for full agent 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 description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no additional meaning beyond the schema, such as explaining how parameters interact or providing usage examples. With high schema coverage, the baseline is 3, 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 'Convert image to animated video' clearly states the verb ('Convert') and resource ('image to animated video'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools (get_points, get_task_result), which are unrelated to media conversion, so it doesn't need sibling differentiation but could be more specific about the type of conversion.

  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. It doesn't mention prerequisites, context for use, or exclusions, leaving the agent to infer usage based on the tool name alone. This lack of explicit guidance reduces its effectiveness in tool selection.

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