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baoyu-youtube-transcript

jimliu/baoyu-skills

Download YouTube transcripts, subtitles, and cover images with multi-language support and speaker identification.

What is baoyu-youtube-transcript?

Extracts transcripts, captions, and metadata from YouTube videos by URL or video ID. Supports multiple languages, translation, chapters, and speaker identification with intelligent caching for fast re-formatting. Use when a user asks for YouTube transcripts, subtitles, captions, or cover images.

  • Downloads transcripts from manually created or auto-generated YouTube captions
  • Fetches video metadata and cover images, cached for fast re-formatting
  • Supports multiple output formats: markdown with timestamps, SRT subtitle files, or plain text
  • Segments transcripts by chapters from video description and identifies speaker boundaries
  • Translates transcripts to specified languages and lists available caption options
  • Falls back to yt-dlp when YouTube blocks direct API access

How to install baoyu-youtube-transcript

npx skills add https://github.com/jimliu/baoyu-skills --skill baoyu-youtube-transcript
Prerequisites
  • bun or npx installed (for running TypeScript scripts)
  • yt-dlp available as fallback when YouTube blocks direct API access (optional but recommended)
Claude Code
Cursor
Windsurf
Cline

How to use baoyu-youtube-transcript

  1. 1.Run with --list first to see available transcripts: ${BUN_X} {baseDir}/scripts/main.ts '<youtube-url>' --list
  2. 2.Execute the main command with desired options: ${BUN_X} {baseDir}/scripts/main.ts '<youtube-url>' --chapters --speakers
  3. 3.For multiple languages, specify priority order: ${BUN_X} {baseDir}/scripts/main.ts '<youtube-url>' --languages zh,en,ja
  4. 4.Use --format srt to generate subtitle files instead of markdown
  5. 5.For speaker identification, run with --speakers flag and post-process the output with AI if needed
  6. 6.Cached data is automatically reused for subsequent runs on the same video; use --refresh to force re-fetch

Use cases

Good for
  • Extract a transcript from a YouTube video URL with timestamps and chapter markers
  • Download subtitles in SRT format for use in video editing or players
  • Get a video's cover image and metadata without downloading the full video
  • Translate a YouTube transcript to a different language for accessibility
  • Identify speakers in a multi-speaker video transcript for better readability
Who it's for
  • Content creators and researchers analyzing video content
  • Accessibility specialists creating captions and transcripts
  • Video editors and producers working with subtitle files
  • Multilingual teams needing translated transcripts
  • Developers building tools that consume YouTube transcript data

baoyu-youtube-transcript FAQ

What YouTube URL formats are supported?

Full URLs (youtube.com/watch?v=ID), short URLs (youtu.be/ID), embed URLs, Shorts URLs, and bare video IDs are all accepted.

Do I need a YouTube API key?

No. The script uses YouTube's InnerTube API directly and falls back to yt-dlp if blocked, requiring no authentication.

How does caching work?

On first fetch, transcripts and metadata are cached in youtube-transcript/ directory. Subsequent runs reuse cached data unless --refresh is used or a different language is requested.

Can I get speaker names automatically?

The --speakers flag outputs raw transcript with speaker boundaries. Full speaker identification requires AI post-processing to extract and label speaker names from the video description and transcript.

What languages are supported?

Any language code supported by YouTube's caption system. Use --list to see available transcripts for a specific video, or --translate <code> to translate to a target language.

Full instructions (SKILL.md)

Source of truth, from jimliu/baoyu-skills.


name: baoyu-youtube-transcript description: 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. version: 1.1.0 metadata: openclaw: homepage: https://github.com/JimLiu/baoyu-skills#baoyu-youtube-transcript requires: anyBins: - bun - npx

YouTube Transcript

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.

ScriptPurpose
scripts/main.tsTranscript 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

OptionDescriptionDefault
<url-or-id>YouTube URL or video ID (multiple allowed)Required
--languages <codes>Language codes, comma-separated, in priority orderen
--format <fmt>Output format: text, srttext
--translate <code>Translate to specified language code
--listList available transcripts instead of fetching
--timestampsInclude [HH:MM:SS → HH:MM:SS] timestamps per paragraphon
--no-timestampsDisable timestamps
--chaptersChapter segmentation from video description
--speakersRaw transcript with metadata for speaker identification
--exclude-generatedSkip auto-generated transcripts
--exclude-manually-createdSkip manually created transcripts
--refreshForce re-fetch, ignore cached data
-o, --output <path>Save to specific file pathauto-generated
--output-dir <dir>Base output directoryyoutube-transcript

Optional Environment Variables

VariableDescription
YOUTUBE_TRANSCRIPT_COOKIES_FROM_BROWSERPassed 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
  • Short URL: https://youtu.be/dQw4w9WgXcQ
  • Embed URL: https://www.youtube.com/embed/dQw4w9WgXcQ
  • Shorts URL: https://www.youtube.com/shorts/dQw4w9WgXcQ
  • Video ID: dQw4w9WgXcQ

Output Formats

FormatExtensionDescription
text.mdMarkdown with frontmatter (incl. description), title heading, summary, optional TOC/cover/timestamps/chapters/speakers
srt.srtSubRip 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:

  1. Run with --list first if the user hasn't specified a language, to show available options
  2. 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'
  3. Default: run with --chapters --speakers for the richest output (chapters + speaker identification)
  4. The script auto-saves cached data + output file and prints the file path
  5. 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:

  1. Read the saved .md file
  2. Read the prompt template at {baseDir}/prompts/speaker-transcript.md
  3. 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
  4. 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

ErrorMeaning
Transcripts disabledVideo has no captions at all
No transcript foundRequested language not available
Video unavailableVideo deleted, private, or region-locked
IP blockedToo many requests, try again later
Age restrictedVideo requires login for age verification
bot detectedThe 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)