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YouTube Transcript AI

by ai.youtube-transcript
OverviewDiscussionsAdmin

get_transcripts_batch

Read the transcripts of several videos in one call (up to 5, or 25 on the Ultra plan), each cut to a length you choose, so you can skim a set of search results without filling your context. Each video counts as one request against your daily quota. For the rest of a long video use find_in_transcript or get_youtube_transcript.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "videos": "<videos>"
    },
    "name": "get_transcripts_batch"
  }
}

Input Schema

NameRequiredDescriptionDefault
langNoOptional BCP-47 caption language code applied to every video.
videosYesYouTube URLs or 11-character video IDs (up to 5, or 25 on the Ultra plan; get_account_status shows the limit for this key).
max_chars_eachNoCharacters of transcript to keep per video. Default 6000.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / videos / description
      Previous value: -"YouTube URLs or 11-character video IDs (up to 5)."New value: +"YouTube URLs or 11-character video IDs (up to 5, or 25 on the Ultra plan; get_account_status shows the limit for this key)."
    • changedInput schema / properties / videos / maxItems
      Previous value: -5New value: +25
  2. Added

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the quota cost ('each video counts as one request against your daily quota'), the batch caps, and the truncation model ('each cut to a length you choose'). It omits failure behavior — what happens when one video lacks captions or the batch partially fails — and says nothing about the return shape.

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?

Three sentences, each doing distinct work: what it does, what it costs, where to go instead. Limits are front-loaded in the first clause and there is no filler.

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?

For a 3-parameter batch read with no output schema and no annotations, the description covers scope, cost, and alternatives adequately. The remaining gap is partial-failure and no-caption behavior, which an agent would want before batching five videos.

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 coverage is 100%, so the schema already documents lang, videos, and max_chars_each including the 1000-30000 range and default 6000. The description adds only the conceptual framing of truncation ('cut to a length you choose') and the batch limit, so baseline 3 applies.

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?

States a specific verb and resource ('Read the transcripts of several videos') plus the batching scope ('in one call'), which immediately separates it from the single-video siblings. The parenthetical limits (5, or 25 on Ultra) further pin down exactly what 'several' means.

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?

Gives a clear use case ('skim a set of search results without filling your context') and routes the agent elsewhere for the remainder of a long video via find_in_transcript and get_youtube_transcript. It stops short of an explicit 'use this instead of get_youtube_transcript when you have 2+ videos', leaving the single-video case implied rather than stated.

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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