Downloads YouTube video transcripts/subtitles and cover images by URL or video ID. Supports multiple languages, translation, chapters, and speaker identification. Caches raw data for fast re-formatting. Use when user asks to "get YouTube transcript", "download subtitles", "get captions", "YouTube字幕", "YouTube封面", "视频封面", "video thumbnail", "video cover image", or provides a YouTube URL and wants the transcript/subtitle text or cover image extracted.
Downloads YouTube video transcripts/subtitles and cover images by URL or video ID. Supports multiple languages, translation, chapters, and speaker identification. Caches raw data for fast re-formatting. Use when user asks to "get YouTube transcript", "download subtitles", "get captions", "YouTube字幕", "YouTube封面", "视频封面", "video thumbnail", "video cover image", or provides a YouTube URL and wants the transcript/subtitle text or cover image extracted.
Downloads transcripts (subtitles/captions) from YouTube videos. Works with both manually created and auto-generated transcripts. No API key or browser required — uses YouTube's InnerTube API directly and automatically falls back to yt-dlp when YouTube blocks the direct API path.
Fetches video metadata and cover image on first run, caches raw data for fast re-formatting.
Script Directory
Scripts in scripts/ subdirectory. {baseDir} = this SKILL.md's directory path. Resolve ${BUN_X} runtime: if bun installed → bun; if npx available → npx -y bun; else suggest installing bun. Replace {baseDir} and ${BUN_X} with actual values.
Script
Purpose
scripts/main.ts
Transcript download CLI
Usage
# Default: markdown with timestamps (English)${BUN_X} {baseDir}/scripts/main.ts <youtube-url-or-id>
# Specify languages (priority order)${BUN_X} {baseDir}/scripts/main.ts <url> --languages zh,en,ja
# Without timestamps${BUN_X} {baseDir}/scripts/main.ts <url> --no-timestamps
# With chapter segmentation${BUN_X} {baseDir}/scripts/main.ts <url> --chapters
# With speaker identification (requires AI post-processing)${BUN_X} {baseDir}/scripts/main.ts <url> --speakers
# SRT subtitle file${BUN_X} {baseDir}/scripts/main.ts <url> --format srt
# Translate transcript${BUN_X} {baseDir}/scripts/main.ts <url> --translate zh-Hans
# List available transcripts${BUN_X} {baseDir}/scripts/main.ts <url> --list
# Force re-fetch (ignore cache)${BUN_X} {baseDir}/scripts/main.ts <url> --refresh
Options
Option
Description
Default
<url-or-id>
YouTube URL or video ID (multiple allowed)
Required
--languages <codes>
Language codes, comma-separated, in priority order
en
--format <fmt>
Output format: text, srt
text
--translate <code>
Translate to specified language code
--list
List available transcripts instead of fetching
--timestamps
Include [HH:MM:SS → HH:MM:SS] timestamps per paragraph
on
--no-timestamps
Disable timestamps
--chapters
Chapter segmentation from video description
--speakers
Raw transcript with metadata for speaker identification
--exclude-generated
Skip auto-generated transcripts
--exclude-manually-created
Skip manually created transcripts
--refresh
Force re-fetch, ignore cached data
-o, --output <path>
Save to specific file path
auto-generated
--output-dir <dir>
Base output directory
youtube-transcript
Optional Environment Variables
Variable
Description
YOUTUBE_TRANSCRIPT_COOKIES_FROM_BROWSER
Passed to yt-dlp --cookies-from-browser during fallback, e.g. chrome, safari, firefox, or chrome:Profile 1
Input Formats
Accepts any of these as video input:
Full URL: https://www.youtube.com/watch?v=dQw4w9WgXcQ
Markdown with frontmatter (incl. description), title heading, summary, optional TOC/cover/timestamps/chapters/speakers
srt
.srt
SubRip subtitle format for video players
Output Directory
youtube-transcript/
├── .index.json # Video ID → directory path mapping (for cache lookup)
└── {channel-slug}/{title-full-slug}/
├── meta.json # Video metadata (title, channel, description, duration, chapters, etc.)
├── transcript-raw.json # Raw transcript snippets from YouTube API (cached)
├── transcript-sentences.json # Sentence-segmented transcript (split by punctuation, merged across snippets)
├── imgs/
│ └── cover.jpg # Video thumbnail
├── transcript.md # Markdown transcript (generated from sentences)
└── transcript.srt # SRT subtitle (generated from raw snippets, if --format srt)
{channel-slug}: Channel name in kebab-case
{title-full-slug}: Full video title in kebab-case
The --list mode outputs to stdout only (no file saved).
Caching
On first fetch, the script saves:
meta.json — video metadata, chapters, cover image path, language info
transcript-raw.json — raw transcript snippets from YouTube API ({ text, start, duration }[])
transcript-sentences.json — sentence-segmented transcript ({ text, start: "HH:mm:ss", end: "HH:mm:ss" }[]), split by sentence-ending punctuation (.?!…。？！ etc.), timestamps proportionally allocated by character length, CJK-aware text merging
imgs/cover.jpg — video thumbnail
Subsequent runs for the same video use cached data (no network calls). Use --refresh to force re-fetch. If a different language is requested, the cache is automatically refreshed.
When YouTube returns anti-bot / blocked responses on the direct InnerTube path, the script retries with alternate client identities and then falls back to yt-dlp if available. If fallback is needed but yt-dlp is unavailable, the agent should decide how to make yt-dlp available and continue rather than pushing the installation decision to the user.
SRT output (--format srt) is generated from transcript-raw.json. Text/markdown output uses transcript-sentences.json for natural sentence boundaries.
Workflow
When user provides a YouTube URL and wants the transcript:
Run with --list first if the user hasn't specified a language, to show available options
Always single-quote the URL when running the script — zsh treats ? as a glob wildcard, so an unquoted YouTube URL causes "no matches found": use 'https://www.youtube.com/watch?v=ID'
Default: run with --chapters --speakers for the richest output (chapters + speaker identification)
The script auto-saves cached data + output file and prints the file path
For --speakers mode: after the script saves the raw file, follow the speaker identification workflow below to post-process with speaker labels
When user only wants a cover image or metadata, running the script with any option will also cache meta.json and imgs/cover.jpg.
When re-formatting the same video (e.g., first text then SRT), the cached data is reused — no re-fetch needed.
Chapter & Speaker Workflow
Chapters (--chapters)
The script parses chapter timestamps from the video description (e.g., 0:00 Introduction), segments the transcript by chapter boundaries, groups snippets into readable paragraphs, and saves as .md with a Table of Contents. No further processing needed.
If no chapter timestamps exist in the description, the transcript is output as grouped paragraphs without chapter headings.
Speaker Identification (--speakers)
Speaker identification requires AI processing. The script outputs a raw .md file containing:
YAML frontmatter with video metadata (title, channel, date, cover, description, language)
Video description (for speaker name extraction)
Chapter list from description (if available)
Raw transcript in SRT format (pre-computed start/end timestamps, token-efficient)
After the script saves the raw file, spawn a sub-agent (use a cheaper model like Sonnet for cost efficiency) to process speaker identification:
Read the saved .md file
Read the prompt template at {baseDir}/prompts/speaker-transcript.md
Process the raw transcript following the prompt:
Identify speakers using video metadata (title → guest, channel → host, description → names)
Detect speaker turns from conversation flow, question-answer patterns, and contextual cues
Segment into chapters (use description chapters if available, else create from topic shifts)
Format with **Speaker Name:** labels, paragraph grouping (2-4 sentences), and [HH:MM:SS → HH:MM:SS] timestamps
Overwrite the .md file with the processed transcript (keep the YAML frontmatter)
When --speakers is used, --chapters is implied — the processed output always includes chapter segmentation.
Error Cases
Error
Meaning
Transcripts disabled
Video has no captions at all
No transcript found
Requested language not available
Video unavailable
Video deleted, private, or region-locked
IP blocked
Too many requests, try again later
Age restricted
Video requires login for age verification
bot detected
The script retries alternate clients and then yt-dlp; if fallback tooling is missing, the agent should resolve that itself, otherwise if it still fails try YOUTUBE_TRANSCRIPT_COOKIES_FROM_BROWSER=safari (or your browser)
