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get_video_comments_tool

Retrieve comments from YouTube videos to analyze audience feedback, gather insights, or monitor discussions. Specify video ID and optional result limit.

Instructions

Get comments for a video.

Args: video_id: YouTube video ID max_results: Maximum number of comments to return (default: 100)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
video_idYes
max_resultsNo
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 states what the tool does but doesn't mention important behavioral aspects like authentication requirements, rate limits, pagination behavior, comment sorting order, whether it retrieves top-level comments only or includes replies, or what happens when max_results exceeds available comments.

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 appropriately concise with a clear purpose statement followed by parameter explanations. The two-sentence structure is efficient, though the 'Args:' section formatting could be slightly cleaner. Every sentence serves a purpose.

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 2 parameters, 0% schema description coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain what the return value looks like (comment structure, fields), doesn't mention error conditions, and provides minimal behavioral context despite the lack of structured metadata.

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 compensate. It provides basic semantic meaning for both parameters ('YouTube video ID' and 'Maximum number of comments to return'), which adds value beyond the schema's bare titles. However, it doesn't explain format requirements for video_id or constraints on max_results (minimum/maximum values).

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 'Get comments for a video' - a specific verb ('Get') and resource ('comments for a video'). It distinguishes from some siblings like 'get_video_info' (which gets metadata) or 'summarize_video' (which creates summaries), but doesn't explicitly differentiate from all comment-related tools (though none exist in the sibling list).

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. While the sibling list includes other video-related tools, there's no indication of when to choose this comment-fetching tool over others, nor any prerequisites or constraints for usage.

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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