Server Quality Checklist

Tool Scores

• extract_key_momentsC
  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 but offers minimal behavioral insight. It mentions what is extracted ('timestamps and descriptions') but doesn't cover critical aspects like error handling (e.g., invalid URLs, unsupported videos), performance (e.g., processing time), or output format details. This is inadequate for a tool with potential complexity.

  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 directly states the tool's function without unnecessary words. It is front-loaded with the core action and resource, 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?

  Given no annotations, no output schema, and incomplete parameter documentation (50% coverage), the description is insufficient. It lacks details on behavioral traits, error conditions, and output structure, which are essential for an extraction tool. The description does not compensate for these gaps in structured data.

  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 50% (only 'number_of_moments' has a description), and the description adds no parameter-specific information beyond implying a YouTube URL is needed. It doesn't clarify URL format requirements or the nature of 'key moments,' leaving gaps in understanding the 'youtube_url' parameter. Baseline 3 is appropriate given partial schema coverage.

  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 ('extracts') and resource ('key moments from a given YouTube video'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'summarize_youtube_video' or 'ask_about_youtube_video', which might also process video content in different ways.

  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 when to choose extraction over summarization or querying, nor does it specify prerequisites or constraints (e.g., video length, availability). This leaves 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.

• summarize_youtube_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. It mentions the method ('using Gemini Vision API') but lacks details on rate limits, authentication needs, error handling, or output format. For a tool that likely involves API calls and video processing, 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 a single, efficient sentence that front-loads the core purpose without unnecessary details. It's appropriately sized for the tool's complexity, with zero waste or redundancy, making it easy to understand at a glance.

  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 (involving video processing and an external API), lack of annotations, no output schema, and incomplete parameter documentation, the description is insufficient. It doesn't cover behavioral aspects like performance, limitations, or what the summary output looks like, leaving significant gaps for effective tool 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 description coverage is 50% (only 'summary_length' has a description). The description adds no parameter semantics beyond the schema, as it doesn't explain the 'youtube_url' parameter or provide additional context for 'summary_length'. With partial schema coverage, the description doesn't compensate for the undocumented parameter, resulting in a baseline score.

  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: 'Generates a summary of a given YouTube video URL using Gemini Vision API.' It specifies the verb ('Generates a summary'), resource ('YouTube video URL'), and method ('using Gemini Vision API'). However, it doesn't explicitly differentiate from sibling tools like 'ask_about_youtube_video' or 'extract_key_moments', which might offer similar or overlapping functionality.

  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 sibling tools or contexts where this tool is preferred, such as for quick overviews versus detailed analysis. Without such guidance, users might struggle to choose between this and tools like 'ask_about_youtube_video' or 'extract_key_moments'.

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

• list_supported_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 but only states what the tool does, not how it behaves. It lacks details on permissions, rate limits, output format, or whether it's a read-only operation. 'Lists' implies a safe read, but this isn't explicitly confirmed, leaving behavioral gaps.

  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 directly states the tool's purpose without redundancy. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place, with no wasted verbiage.

  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?

  Given the tool's simplicity (0 parameters, no output schema), the description is minimally adequate but incomplete. It explains what the tool does but lacks context on why to use it, output details, or behavioral traits. For a list operation, this is the bare minimum, scoring a 3.

  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 schema fully documents the absence of inputs. The description adds no parameter information, which is appropriate here. Baseline is 4 for zero parameters, as no compensation is needed.

  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 ('Lists') and resource ('available Gemini models'), specifying they support the 'generateContent' method. It distinguishes from sibling tools (YouTube-related) by focusing on model listing rather than video processing. However, it doesn't explicitly differentiate from hypothetical model-related siblings, keeping it at 4 rather than 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, context for selecting models, or relationships to sibling tools. The agent must infer usage from the purpose alone, which is insufficient for optimal tool selection.

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

• ask_about_youtube_videoB
  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 full burden for behavioral disclosure. It mentions the tool can answer questions or provide descriptions, but doesn't cover important aspects like rate limits, authentication needs, error conditions, or what constitutes a 'general description.' This leaves significant gaps for a tool that presumably processes external content.

  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 communicates the core functionality without any wasted words. It's appropriately sized for a tool with two parameters and front-loads the essential information about what the tool does.

  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?

  Given no annotations and no output schema, the description provides basic purpose and parameter guidance but lacks sufficient detail about behavioral traits, error handling, or output format. For a tool that interacts with external video content, more context about limitations or capabilities would be helpful to achieve completeness.

  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?

  Schema description coverage is 50% (only the question parameter has a description). The description adds valuable context by explaining that omitting the question parameter triggers a general description, which clarifies the optional nature and default behavior. This compensates well for the schema's partial coverage.

  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: answering questions about YouTube videos or providing general descriptions. It specifies the verb ('answers'/'provides') and resource ('video'), but doesn't explicitly differentiate from sibling tools like summarize_youtube_video or extract_key_moments, which prevents a perfect score.

  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 this tool (for questions about video content or general descriptions) but doesn't provide explicit guidance on when to choose alternatives like summarize_youtube_video or extract_key_moments. No exclusions or prerequisites are mentioned, leaving usage context somewhat vague.

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