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Get raw video subtitles

get_raw_subtitles
Read-onlyIdempotent

Retrieve raw subtitle text from video URLs. Supports multiple formats (SRT, VTT, ASS, LRC) and options for language, type, and pagination.

Instructions

Fetch raw SRT/VTT subtitles for a video (supported platforms). Optional: type, lang, response_limit (when omitted returns full content), next_cursor for pagination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesVideo URL (supported: YouTube, Twitter/X, Instagram, TikTok, Twitch, Vimeo, Facebook, Bilibili, VK, Dailymotion, Reddit) or YouTube video ID
formatNoSubtitle format (default from YT_DLP_SUB_FORMAT or srt)
typeNoSubtitle track type: official or auto-generated
langNoLanguage code (e.g. en, es). When omitted with Whisper fallback, language is auto-detected
response_limitNoMax characters per response. When omitted, returns full content. When set: min 1000
next_cursorNoOpaque cursor from previous response for pagination

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoIdYes
typeYes
langYes
formatYes
contentYes
next_cursorNo
is_truncatedYes
total_lengthYes
start_offsetYes
end_offsetYes
sourceNo
Behavior4/5

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

Annotations declare readOnlyHint and idempotentHint true, confirming safe reads. The description adds valuable behavioral context: optional type/lang, response_limit behavior (full content when omitted), and pagination via next_cursor, which enhances transparency beyond annotations.

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?

The description is a single, well-structured sentence that front-loads the core purpose and efficiently conveys key optional parameters and behaviors. No wasted words.

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?

Given the output schema exists (reducing need to explain returns), the description covers essential aspects: supported platforms, format handling, language/track type options, pagination, and response limit behavior. It is complete for the tool's complexity.

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%, so baseline is 3. The description adds meaning by explaining response_limit's omitted behavior (returns full content) and notes pagination cursor, providing context not in the schema alone.

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 fetches raw SRT/VTT subtitles for a video, mentioning supported platforms and optional parameters. It distinguishes from siblings like get_available_subtitles (lists available tracks) and get_transcript (likely plain text).

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

Usage Guidelines3/5

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

The description does not explicitly advise when to use this tool versus alternatives. It implies usage for raw subtitle fetching but lacks exclusions or contextual guidance for selection among siblings.

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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