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YouTube Transcript Extractor

Free

Transform YouTube videos into structured text outputs.

by browser-act5.3k stars on browser-act/skills
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Updated Aug 5, 2026
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Free · Opens the source repo

What YouTube Transcript Extractor does

The YouTube Transcript Extractor skill allows users to efficiently extract and reformat transcripts from YouTube videos. By simply providing a YouTube video URL, users can access the built-in transcript panel, which the skill opens automatically. Once the transcript is visible, the skill extracts all timestamped segments, enabling users to transform the raw transcript into various formats such as summaries, chapter outlines, Twitter threads, blog posts, or notable quotes. This functionality is particularly useful for content creators, educators, and researchers who need to distill video content into more digestible formats.

The skill operates by leveraging Python scripts that interact with the YouTube page's Document Object Model (DOM). It first checks for the availability of transcripts and supported languages before opening the transcript panel. After ensuring that the transcript is fully loaded, it extracts the segments, which can then be reformatted based on user requests. The default output includes a summary, chapters, a Twitter thread, a blog post, and notable quotes, making it a comprehensive tool for anyone looking to repurpose video content.

This skill is particularly beneficial for users who frequently work with video content and need to summarize or analyze information quickly. By automating the extraction and transformation processes, users save time and effort compared to manual transcription and formatting. Additionally, the skill can handle various video formats and is designed to work seamlessly as long as the user has the relevant YouTube video page open in their browser.

However, it's important to note that the skill's capabilities are limited to the data visible on the YouTube page. It cannot bypass any restrictions or access controls that may prevent transcript availability. Users should also be aware that auto-generated transcripts may not always be accurate, and language switching requires manual adjustment in the YouTube settings. Overall, the YouTube Transcript Extractor skill is a powerful tool for anyone looking to enhance their productivity when working with video content.

When to use it

Use this skill when you need to extract and reformat transcripts from YouTube videos for summaries, outlines, or social media posts.

When not to use it

Avoid using this skill for videos without available transcripts or when you need to access restricted content.

What you can build with it

Summarizing Educational Content

Extract key points and summaries from educational YouTube videos for study notes.

Creating Social Media Threads

Transform video insights into concise Twitter threads for sharing with your audience.

Blog Post Generation

Reformat video transcripts into structured blog posts with headings and key takeaways.

How to install YouTube Transcript Extractor

View source

1. Install with the skills CLI

npx skills add browser-act/skills/youtube-transcript --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by browser-act

YouTube — Transcript Extraction & Content Reformatting

YouTube video URL → timestamped transcript → summary / chapters / thread / blog / quotes

Language

All process output to user (progress updates, process notifications) follows the user's language.

Objective

Extract the full transcript from a YouTube video's built-in transcript panel, then transform it into the output format the user requests.

Prerequisites

  • Target YouTube video page is already open in the browser: https://www.youtube.com/watch?v={VIDEO_ID}

Pre-execution Checks

1. Tool Readiness

If browser-act has been confirmed available in the current session → skip this step.

Invoke browser-act via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.

Capability Components

This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page, never bypassing authentication or access controls. JS code is encapsulated in Python files under the scripts/ directory, invoked via eval "$(python scripts/xxx.py)". Use the bash tool for execution.

DOM: Check transcript availability and list languages

eval "$(python scripts/get-languages.py)"

No parameters. Reads ytInitialPlayerResponse from the current page.

Output example:

{
  "available_languages": [
    {"code": "en", "name": "English", "kind": "manual", "is_auto": false},
    {"code": "en", "name": "English (auto-generated)", "kind": "asr", "is_auto": true}
  ],
  "count": 2
}

Returns {"error": true, "message": "..."} when transcripts are disabled or page is not a YouTube video.

DOM: Open transcript panel

eval "$(python scripts/open-transcript-panel.py)"

No parameters. Clicks the "Show transcript" button below the video (handles multiple UI language variants automatically for robustness).

Must call wait stable after this to allow the panel to fully load.

Output example:

{"success": true, "label": "内容转文字"}

DOM: Extract all transcript segments

eval "$(python scripts/extract-transcript-segments.py)"

No parameters. Scrolls the open transcript panel to trigger lazy loading for long videos, then extracts all segments.

Output example:

{
  "segment_count": 24,
  "segments": [
    {"ts": "0:18", "text": "We're no strangers to love"},
    {"ts": "0:27", "text": "You know the rules and so do I"}
  ],
  "full_text": "We're no strangers to love You know the rules...",
  "timestamped_text": "0:18 We're no strangers to love\n0:27 You know the rules..."
}

Composite: Full transcript fetch workflow

  1. navigate https://www.youtube.com/watch?v={VIDEO_ID}wait stable
  2. eval "$(python scripts/get-languages.py)" — confirm transcripts are available; note the language list
  3. eval "$(python scripts/open-transcript-panel.py)" — open the panel
  4. wait stable — wait for panel content to load
  5. eval "$(python scripts/extract-transcript-segments.py)" — extract all segments

Use timestamped_text from the output as input for the Transform step below.

Transform: Content Reformatting

After fetching the transcript, transform it based on what the user requests. If the user did not specify a format, default to the Full Document — output all five sections in order.

  • Summary: Concise 5–10 sentence overview of the entire video
  • Chapters: Group by topic shifts, output timestamped chapter list
  • Thread: Twitter/X thread format — numbered posts, each under 280 characters
  • Blog post: Full article with title, H2 sections per major topic, key quotes, and takeaways
  • Quotes: Notable quotes with their timestamps

Default Full Document output order (when no specific format is requested):

  1. Summary
  2. Chapters
  3. Thread
  4. Blog Post
  5. Quotes

Workflow

  1. Fetch transcript using the Composite component above.
  2. Validate: confirm segment_count >= 1. If empty, tell the user the video has transcripts disabled.
  3. Chunk if needed: if full_text exceeds ~50,000 characters, split timestamped_text into overlapping chunks (~40K characters with 2K overlap) and summarize each chunk before merging.
  4. Transform into the requested format(s) using the timestamped_text field. If no format specified, produce all five sections.
  5. Verify: re-read the output for coherence, correct timestamps (if chapters), and completeness before presenting.

Example — Chapters Output

0:00 Introduction — host opens with the problem statement
3:45 Background — prior work and why existing solutions fall short
12:20 Core method — walkthrough of the proposed approach
24:10 Results — benchmark comparisons and key takeaways
31:55 Q&A — audience questions on scalability and next steps

Example — Thread Output

1/ Just watched an incredible video on [topic]. Key takeaways 🧵

2/ First insight: [point]. This matters because [reason].

3/ The surprising part: [finding]. Most assume [belief], but this shows otherwise.

4/ Practical takeaway: [action].

5/ Full video: [URL]

Error Handling

  • Transcripts disabled: get-languages.py returns error; tell user and suggest checking if captions are available on the video page
  • Private/unavailable video: page will not load correctly; relay the error and ask user to verify the URL
  • Transcript button not found: usually means the user is not on a video page, or the page hasn't finished loading; navigate to the URL and retry
  • No segments after panel opens: retry open-transcript-panel.py + wait stable + extract-transcript-segments.py once

Known Limitations

  • Language selection: the transcript panel shows the language YouTube defaults to for the user's region. Switching to a specific language requires changing the caption language in the player's CC settings first; automatic language switching is not implemented.
  • Auto-generated transcripts (kind: asr) may have lower accuracy than manual captions.
  • Videos that require login to view will not have a transcript panel accessible.

Execution Efficiency

  • Batch orchestration: Write a bash script to loop through video URLs serially within a single session — navigate to each video, run the 3-step composite workflow, save result, then move to the next. Do not parallelize within one browser. To increase throughput for large batches, open multiple stealth browser sessions and distribute URLs across them.
  • Test before batch execution: After writing a batch script, first test with 1–2 videos to confirm the full workflow runs correctly; only then run the full batch.
  • Reduce redundant pre-operations: Pre-execution checks (tool readiness) only need to run once per session; skip them for subsequent videos in the same batch.
  • Error resumption: Save each video's result immediately after extraction; on failure, resume from the failed video rather than starting over.

Success Criteria

segment_count >= 1 AND full_text length > 0

Experience Notes

Path: {working-directory}/browser-act-skill-forge-memories/youtube-content-youtube-transcript.memory.md

Before execution: If the file exists, read it first — it records unexpected situations encountered during past executions (e.g., a strategy has become ineffective); adjust strategy order accordingly.

After execution: If an unexpected situation is encountered (strategy became ineffective, page redesigned, anti-scraping upgraded, better path discovered), append a line: {YYYY-MM-DD}: {what happened} → {conclusion}

Normal execution does not write to the file.

Frequently asked questions about YouTube Transcript Extractor

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