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, 1-10 (default: 1). Each page returns up to ~100 comments. | |
| sort_by | No | Sort order: most_recent (newest first) or relevance (default: relevance) | relevance |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description takes on the full burden of disclosure. It lists the returned fields and the cost per page, but does not mention rate limits, authentication needs, or error behavior. The read-only nature is implicit but not explicitly stated.
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?
The description is two sentences, with the first stating the purpose and the second listing return fields and cost. It is concise, well-structured, and contains no filler or redundancy.
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 tool is relatively simple with three parameters and no output schema. The description compensates for the missing output schema by listing return fields and adds cost information. However, it lacks usage context, possible limitations, or any prerequisites, making it only minimally complete for an unannotated 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?
The input schema already provides detailed descriptions for all three parameters, achieving 100% coverage. The description adds billing cost per page, but this is not a parameter semantic—it relates to the pages parameter. Therefore, the description adds little beyond the schema, matching the baseline for high coverage.
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 starts with 'Get comments from a YouTube video,' which clearly states the verb and resource. This distinguishes it from sibling tools like youtube_video_details and search_youtube, making its 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 implies usage (fetching comments for a given video) but does not explicitly state when to use it over alternatives or provide exclusions. The billing note adds context but does not serve as usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly scoped by platform and resource (e.g. search_twitter vs twitter_user_tweets vs twitter_tweet_details). A few pairs like twitter_tweet_comments vs twitter_user_replies or facebook_page_posts vs search_facebook_posts could cause minor confusion, but descriptions generally clarify the distinction.
The dominant pattern is snake_case with a platform_prefix_resource suffix, and search_* consistently marks search operations. Minor deviations include noun-style names like amazon_best_sellers and place_photos, and the odd get_ skill/comments tools, but the overall convention is predictable.
74 tools is far beyond the typical well-scoped MCP server, even for a multi-platform API aggregator. The breadth is justified by the many platforms covered, but an agent will face a very large action space, and this could reasonably be split into per-platform servers.
The server provides strong lifecycle coverage for its read-only domain: search, profile/details, posts, and engagement data across most platforms. Gaps exist for some platforms (e.g. no LinkedIn person profile, no Facebook event details, no Truth Social profile/search, no Reddit subreddit-specific tools), but the core workflows are well covered.
