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list_comments

Retrieve top-level comments from YouTube videos by specifying video ID, with options to sort by relevance or time and control result count.

Instructions

List top-level comments on a video. Costs 1 quota unit.

Args: video_id: The video ID max_results: Number of comment threads (1-100, default 20) order: Sort — relevance or time

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
video_idYes
max_resultsNo
orderNorelevance

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the quota cost (1 unit), which is useful behavioral context. However, it lacks details on permissions, rate limits, pagination, or error handling, leaving gaps for a mutation-free but resource-intensive operation.

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 front-loaded with the core purpose and cost, followed by a structured Args section. Every sentence earns its place with no wasted words, making it highly efficient and easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 3 parameters with 0% schema coverage and no annotations, the description does well by explaining all parameters and noting the quota cost. An output schema exists, so return values needn't be described. However, it could better address behavioral aspects like pagination or error cases for 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 0%, so the description must compensate. It explains all three parameters: 'video_id' (the video ID), 'max_results' (number of comment threads with range and default), and 'order' (sort options). This adds clear meaning beyond the bare schema, though it could specify what 'top-level' means in relation to threads.

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 verb 'List' and resource 'top-level comments on a video', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'reply_to_comment' or 'delete_comment' beyond the 'list' action, 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 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 'get_video_details' or 'search_videos' that might include comments. It mentions a quota cost, but this doesn't help with tool selection among siblings.

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

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