Server Quality Checklist

Tool Scores

• validate_api_keyC
  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. It states the tool validates an API key and checks account credits/status, but doesn't disclose behavioral traits such as what happens on validation failure (e.g., error messages), whether it makes network calls, rate limits, authentication requirements beyond the key, or the format of the status response. This is a significant gap 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.

  Conciseness5/5

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

  The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part earns its place by specifying the tool's actions and targets, making it appropriately sized for its 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?

  Given the tool's complexity (validation with potential network interaction), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., credit balance, validation result), error conditions, or behavioral details, leaving gaps for an AI agent to use it 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?

  The input schema has 100% description coverage, with the parameter 'api_key' fully documented in the schema. The description adds no additional meaning beyond what the schema provides (e.g., it doesn't explain key format or validation rules). With high schema coverage, the baseline is 3, as the description doesn't compensate but doesn't need to.

  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 tool's purpose with specific verbs ('validate', 'check') and resources ('MMAudio API key', 'account credits/status'). It distinguishes this as a validation/status-checking tool rather than a processing tool like its siblings (text_to_audio, video_to_audio). However, it doesn't explicitly differentiate from potential sibling validation tools (none listed), so it falls short of a perfect 5.

  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 (e.g., before using text_to_audio), when not to use it, or how it relates to sibling tools. The only implied usage is for validation, but this is basic and lacks context.

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

• video_to_audioB
  3.1/5.0
  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 mentions that the tool 'analyzes video frames and generates synchronized audio', implying processing and creation, but fails to disclose critical traits like whether it's a read-only or destructive operation, rate limits, authentication needs, or output format (e.g., file type, size). This leaves significant gaps for an AI 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.

  Conciseness4/5

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

  The description is concise and front-loaded, with two sentences that directly state the tool's purpose and key functionality. Every sentence earns its place by explaining the core action and the types of audio generated, though it could be slightly more structured by explicitly listing output details.

  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 7-parameter tool with no annotations and no output schema, the description is incomplete. It lacks information on the output (e.g., audio format, how to access it), error handling, performance expectations, or any constraints beyond what's implied. This makes it inadequate for an AI agent to fully understand the tool's context and usage.

  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 description coverage is 100%, so the input schema already documents all parameters thoroughly. The description adds no additional meaning beyond what's in the schema, such as explaining interactions between parameters or providing usage examples. However, since the schema is comprehensive, a baseline score of 3 is appropriate as the description doesn't need to compensate.

  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's purpose with specific verbs ('generate AI-powered audio from video content') and resources ('video content'), distinguishing it from sibling tools like 'text_to_audio' by specifying video input. It also mentions the technology used ('MMAudio technology'), which adds specificity.

  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 'text_to_audio' or 'validate_api_key'. It lacks explicit instructions on prerequisites, such as whether the video must be pre-processed or if there are usage limits, leaving the agent without context for tool selection.

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

• text_to_audioB
  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 carries the full burden of behavioral disclosure. It mentions 'AI-powered' and 'MMAudio technology' but doesn't cover critical aspects like rate limits, authentication needs, output format, or potential costs/latency. The description is insufficient for a tool with 6 parameters and 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 efficiently structured in two sentences: the first states the core functionality, and the second provides concrete examples. Every word earns its place with no redundancy or wasted text, making it easy to parse quickly.

  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 complex audio generation tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (audio format, file type, size), error conditions, or practical constraints. The examples help but don't compensate for missing behavioral and output 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?

  Schema description coverage is 100%, so the schema fully documents all 6 parameters. The description adds no specific parameter information beyond what's in the schema, meeting the baseline of 3 where the schema does the heavy lifting. No additional semantic context is provided for parameters.

  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's purpose: 'Generate AI-powered audio content from text descriptions using MMAudio technology.' It specifies the action (generate), resource (audio content), and technology (MMAudio), and distinguishes itself from siblings by focusing on text-to-audio generation rather than validation or video conversion.

  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 usage through examples ('sound effects, ambient audio, music, and atmospheric soundscapes'), but lacks explicit guidance on when to use this tool versus alternatives like 'video_to_audio'. It provides context for generating audio from text but doesn't state exclusions or compare to sibling tools.

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