Get comments from a YouTube video. Returns each comment's text, author, like count, reply count, date, a direct link, and up to 5 preview replies. Billed $0.005 per page.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | YouTube video URL or 11-character video ID | |
| pages | No | Number of pages to fetch, 1-20 (default: 1). Each page returns up to ~100 comments. | |
| sort_by | No | Sort order: most_recent (newest first) or relevance (default: relevance) | relevance |
Changes observed during successful MCP inspections.
Input schema / properties / pages / descriptionPrevious value: -"Number of pages to fetch, 1-10 (default: 1). Each page returns up to ~100 comments."New value: +"Number of pages to fetch, 1-20 (default: 1). Each page returns up to ~100 comments."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses a notable operational trait—billing $0.005 per page—and the limitation that only up to 5 preview replies are returned. This goes beyond a bare operation statement, though it does not discuss error cases, rate limits, or access prerequisites.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two dense sentences with no filler. The primary action and return contents are front-loaded, and the cost caveat is placed at the end. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The absence of an output schema raises the burden on the description, and it does enumerate the returned fields and reply preview limit. It also tells the agent about cost, while the schema covers paging and sort options. Missing are the top-level response shape and any failure modes, but these are minor for a simple read tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3 even without parameter details in the description. The description does not add new meaning for url, pages, or sort_by beyond what the schema already says; it only reinforces pagination through the per-page billing mention.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Get comments from a YouTube video.' This clearly targets comments rather than video metadata, distinguishing it from youtube_video_details and search tools, and the listed return fields (text, author, likes, replies, date, link) make the exact purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: use this tool when you need the comment feed of a YouTube video, including preview replies. It does not explicitly name alternatives or state when not to use it, so it stops short of a 5, but the wording leaves little ambiguity against sibling comment tools for other platforms.
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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