Server Quality Checklist

Tool Scores

• generate_imageB
  3.1/5.0
  Behavior3/5

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

  Without annotations, the description adds behavioral context by noting support for multi-turn and interleaved output, but lacks detail on safety, permissions, or side effects. The description is adequate but not comprehensive.

  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 brief (two sentences) and front-loaded with the core purpose, followed by supporting capabilities. Every sentence earns its place with no redundancy.

  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 (9 parameters, no output schema, no annotations), the description is insufficient. It does not explain return values or how parameters like model or reference_images affect behavior, leaving significant gaps.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters1/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, meaning no parameter descriptions exist in the schema. The description does not explain any of the 9 parameters, leaving the agent to infer from names and enums alone.

  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 generates or edits images using Gemini models and lists specific capabilities like conversational workflows, embedded text, and infographics. It distinguishes from sibling tools (speech, video, music) by focusing on images.

  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 describes what the tool does but provides no explicit guidance on when to use it versus the sibling tools (generate_speech, generate_video, generate_music). No when-not or alternative scenarios are mentioned.

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

• generate_musicB
  3.3/5.0
  Behavior2/5

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

  There are no annotations provided, so the description must fully disclose behavioral traits. It mentions the tool generates music and internally manages streaming, but it does not disclose whether the operation is destructive, requires authentication, has rate limits, or what the output format (e.g., audio file URL) is. This is insufficient for an AI agent to understand side effects.

  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 only two sentences, making it very concise. It front-loads the primary purpose and then adds a clarifying technical detail. However, it could be slightly more structured by separating parameter explanation from behavioral notes.

  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 five parameters and no output schema, the description is incomplete. It fails to mention what the tool returns (e.g., an audio file URL or stream), and it does not cover the optional parameters. This leaves significant gaps for an AI agent to correctly invoke the tool.

  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 0%, so the description must add meaning to parameters. It clarifies that the 'prompts' array contains objects with 'text' and 'weight' fields, which aids the agent. However, it does not explain other parameters like bpm, scale, temperature, or duration_seconds, leaving them underdocumented.

  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 it generates instrumental music from weighted text prompts using Google's Lyria model, specifying the verb (generate), resource (music), and technology, distinguishing it from sibling tools like generate_image or generate_speech.

  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 explains the prompt structure and mentions server streaming, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it include prerequisites or exclusions. The context signals indicate sibling tools are different modalities, so the usage is partially implied.

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

• generate_videoB
  3.3/5.0
  Behavior3/5

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

  Discloses that generation is asynchronous, which is a key behavioral trait. However, with no annotations, the description does not cover other aspects like auth needs, rate limits, or return format, leaving gaps 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?

  Three concise sentences front-loading key information about purpose, capabilities, and async nature. No wasted words.

  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?

  Missing crucial details for an async tool, such as how to retrieve generated videos, polling mechanism, or expected output format. With no output schema and 8 parameters, the description is insufficient for correct invocation.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, and the description does not explain the purpose of parameters like extend_video_id, reference_images, etc. It only lists modes without mapping them to specific parameters, providing minimal additive value.

  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?

  Clearly states that the tool generates videos from text prompts or reference images using Google's Veo models, and lists specific modes (text-to-video, image-to-video, etc.), distinguishing it from sibling tools like generate_image.

  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?

  Does not provide explicit guidance on when to use this tool vs. alternatives (generate_image, generate_speech, generate_music). The description implies usage for video generation but lacks when-not-to-use or prerequisites.

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

• generate_speechA
  3.6/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It discloses modes, voice selection, and style control, which are key behavioral traits. However, it omits details like supported audio formats, latency, or that it uses specific models (though model enum is in schema). Missing some 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?

  Two concise sentences, front-loaded with purpose, no unnecessary words. Efficiently conveys key capabilities.

  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 6 parameters, no output schema, and no annotations, the description is incomplete. It lacks details on the 'speakers' parameter structure, relationship between voice_name and speakers, and return format. Agent would need to infer or guess for effective use.

  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 0%, so description must add meaning. It hints at model, multi-speaker mode, voice selection, and style instructions, but does not explicitly map to parameters or explain complex ones like 'speakers' array. Adds some value but insufficient for full understanding.

  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 it generates speech audio from text using Gemini TTS models, and mentions modes and voice selection. It distinguishes from sibling tools (image, video, music) implicitly by modality, but does not explicitly differentiate.

  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?

  The description provides clear context for when to use the tool: for text-to-speech with optional multi-speaker mode, voice selection, and style control. It does not explicitly state when not to use or list alternatives, which is acceptable given sibling tools cover different modalities.

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