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youtube_comments

Scrape YouTube video comments, including text, likes, replies, author details, and pagination tokens to fetch more pages.

Instructions

Scrapes comments from any YouTube video, returning comment text, likes, reply counts, author details, and pagination tokens for fetching additional pages. [Credits: 5 API credits per successful request] Notes: Shares the single /youtube endpoint with all other YouTube tools; combination of v + comment-specific params selects Comments behavior (distinguish from Transcripts/Video by the presence of next_page_token support and response shape). Each comment includes its own replies_next_page_token for paginating that comment's reply thread. ENDPOINT VERIFIED LIVE 2026-07-10: docs show bare /youtube but the working endpoint is /youtube/comments. Returns: { total_comments, comments: [{ comment_id, link, channel: {id,handle,link,thumbnail}, published_date, text, likes, replies, replies_next_page_token }], pagination: {next_page_token} }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vYesVideo ID of the YouTube video whose comments you want to scrape, found in the video URL after `?v=`.
countryNoTwo-letter country code specifying search location (e.g., `us`, `uk`, `fr`). (default: us)
languageNoLanguage of the results. Possible values: `en`, `es`, `fr`, `de`, etc. (default: en)
next_page_tokenNoDefines the next page token for retrieving the next page of comments or replies. Use the `next_page_token` value from the previous response (top-level pagination.next_page_token, or a comment's own replies_next_page_token to fetch that comment's replies).
Behavior5/5

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

No annotations provided, so description carries full burden. It discloses credits cost, endpoint verification, endpoint discrepancy (docs vs working), and detailed response structure including pagination tokens. Fully transparent about behavior.

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?

Description is structured with clear sections (credits, notes, endpoint note, returns) but is somewhat lengthy. Could omit some details or condense, but still effective.

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

Completeness5/5

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

No output schema, so description must cover return format. It does so comprehensively with field names and types. Endpoint and pagination details are included. Complete for a 4-parameter tool.

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 coverage is 100%, baseline 3. Description adds value by explaining next_page_token usage for paginating both comments and replies, and notes defaults for country/language. Exceeds baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scrapes comments from YouTube videos, listing returned fields and pagination support. It distinguishes from sibling tools like youtube_transcripts and youtube_video by noting endpoint sharing and behavior differences.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides guidance on when to use (comments) and indicates differentiation from transcripts/video via next_page_token support and response shape. Implicitly advises against using for other YouTube data types, though explicit when-not-to-use is lacking.

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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