TubeScribe

TubeScribe 🎬

Turn any YouTube video into a polished document + audio summary.

Drop a YouTube link → get a beautiful transcript with speaker labels, key quotes, timestamps that link back to the video, and an audio summary you can listen to on the go.

💸 Free & No Paid APIs

• -No subscriptions or API keys — works out of the box
• -Local processing — transcription, speaker detection, and TTS run on your machine
• -Network access — fetching from YouTube (captions, metadata, comments) requires internet
• -No data uploaded — nothing is sent to external services; all processing stays on your machine
• -Safe sub-agent — spawned sub-agent has strict instructions: no software installation, no network calls beyond YouTube

✨ Features

• -📄 Transcript with summary and key quotes — Export as DOCX, HTML, or Markdown
• -🎯 Smart Speaker Detection — Automatically identifies participants
• -🔊 Audio Summaries — Listen to key points (MP3/WAV)
• -📝 Clickable Timestamps — Every quote links directly to that moment in the video
• -💬 YouTube Comments — Viewer sentiment analysis and best comments
• -📋 Queue Support — Send multiple links, they get processed in order
• -🚀 Non-Blocking Workflow — Conversation continues while video processes in background

🎬 Works With Any Video

• -Interviews & podcasts (multi-speaker detection)
• -Lectures & tutorials (single speaker)
• -Music videos (lyrics extraction)
• -News & documentaries
• -Any YouTube content with captions

Quick Start

When user sends a YouTube URL:

1. Spawn sub-agent with the full pipeline task immediately

2. Reply: "🎬 TubeScribe is processing — I'll let you know when it's ready!"

3. Continue conversation (don't wait!)

4. Sub-agent notification will announce completion with title and details

DO NOT BLOCK — spawn and move on instantly.

First-Time Setup

Run setup to check dependencies and configure defaults:

python skills/tubescribe/scripts/setup.py

This checks: summarize CLI, pandoc, ffmpeg, Kokoro TTS

Full Workflow (Single Sub-Agent)

Spawn ONE sub-agent that does the entire pipeline:

sessions_spawn(
    task=f"""
TubeScribe: Process {youtube_url}

⚠️ CRITICAL: Do NOT install any software.
No pip, brew, curl, venv, or binary downloads.
If a tool is missing, STOP and report what's needed.

Run the COMPLETE pipeline — do not stop until all steps are done.

Step 1: Extract

bash

python3 skills/tubescribe/scripts/tubescribe.py "{youtube_url}"

Note the Source and Output paths printed by the script. Use those exact paths in subsequent steps.

Step 2: Read source JSON
Read the Source path from Step 1 output and note:
-metadata.title (for filename)
-metadata.video_id
-metadata.channel, upload_date, duration_string

Step 3: Create formatted markdown
Write to the Output path from Step 1:

1. # <title>
---
2. Video info block — Channel, Date, Duration, URL (clickable). Empty line between each field.
---
3. ## Participants — table with bold headers:
   

| Name | Role | Description |

|----------|----------|-----------------|

---

4. ## Summary — 3-5 paragraphs of prose
---
5. ## Key Quotes — 5 best with clickable YouTube timestamps. Format each as:
   

"Quote text here." - [12:34](https://www.youtube.com/watch?v=ID&t=754s)

"Another quote." - [25:10](https://www.youtube.com/watch?v=ID&t=1510s)

   Use regular dash -, NOT em dash —. Do NOT use blockquotes >. Plain paragraphs only.

---
6. ## Viewer Sentiment (if comments exist)
---
7. ## Best Comments (if comments exist) — Top 5, NO lines between them:
   

Comment text here.

*- ▲ 123 @AuthorName*

Next comment text here.

*- ▲ 45 @AnotherAuthor*

   Attribution line: dash + italic. Just blank line between comments, NO --- separators.


---
8. ## Full Transcript — merge segments, speaker labels, clickable timestamps

Step 4: Create DOCX
Clean the title for filename (remove special chars), then:

bash

pandoc <output_path> -o ~/Documents/TubeScribe/<safe_title>.docx

Step 5: Generate audio
Write the summary text to a temp file, then use TubeScribe's built-in audio generation:

bash

Write summary to temp file (use python3 to write, avoids shell escaping issues)

python3 -c "

text = '''YOUR SUMMARY TEXT HERE'''

with open('<temp_dir>/tubescribe_<video_id>_summary.txt', 'w') as f:

f.write(text)

"

Generate audio (auto-detects engine, voice, format from config)

python3 skills/tubescribe/scripts/tubescribe.py \

--generate-audio <temp_dir>/tubescribe_<video_id>_summary.txt \

--audio-output ~/Documents/TubeScribe/<safe_title>_summary

This reads ~/.tubescribe/config.json and uses the configured TTS engine (mlx/kokoro/builtin), voice blend, and speed automatically. Output format (mp3/wav) comes from config.

Step 6: Cleanup

bash

python3 skills/tubescribe/scripts/tubescribe.py --cleanup <video_id>

Step 7: Open folder

bash

open ~/Documents/TubeScribe/

Report
Tell what was created: DOCX name, MP3 name + duration, video stats.
""",
    label="tubescribe",
    runTimeoutSeconds=900,
    cleanup="delete"
)

After spawning, reply immediately:

> 🎬 TubeScribe is processing - I'll let you know when it's ready!

Then continue the conversation. The sub-agent notification announces completion.

Configuration

Config file: ~/.tubescribe/config.json

{
  "output": {
    "folder": "~/Documents/TubeScribe",
    "open_folder_after": true,
    "open_document_after": false,
    "open_audio_after": false
  },
  "document": {
    "format": "docx",
    "engine": "pandoc"
  },
  "audio": {
    "enabled": true,
    "format": "mp3",
    "tts_engine": "mlx"
  },
  "mlx_audio": {
    "path": "~/.openclaw/tools/mlx-audio",
    "model": "mlx-community/Kokoro-82M-bf16",
    "voice": "af_heart",
    "lang_code": "a",
    "speed": 1.05
  },
  "kokoro": {
    "path": "~/.openclaw/tools/kokoro",
    "voice_blend": { "af_heart": 0.6, "af_sky": 0.4 },
    "speed": 1.05
  },
  "processing": {
    "subagent_timeout": 600,
    "cleanup_temp_files": true
  }
}

Output Options

| Option | Default | Description |

|--------|---------|-------------|

| output.folder | ~/Documents/TubeScribe | Where to save files |

| output.open_folder_after | true | Open output folder when done |

| output.open_document_after | false | Auto-open generated document |

| output.open_audio_after | false | Auto-open generated audio summary |

Document Options

| Option | Default | Values | Description |

|--------|---------|--------|-------------|

| document.format | docx | docx, html, md | Output format |

| document.engine | pandoc | pandoc | Converter for DOCX (falls back to HTML) |

Audio Options

| Option | Default | Values | Description |

|--------|---------|--------|-------------|

| audio.enabled | true | true, false | Generate audio summary |

| audio.format | mp3 | mp3, wav | Audio format (mp3 needs ffmpeg) |

| audio.tts_engine | mlx | mlx, kokoro, builtin | TTS engine (mlx = fastest on Apple Silicon) |

MLX-Audio Options (preferred on Apple Silicon)

| Option | Default | Description |

|--------|---------|-------------|

| mlx_audio.path | ~/.openclaw/tools/mlx-audio | mlx-audio venv location |

| mlx_audio.model | mlx-community/Kokoro-82M-bf16 | MLX model to use |

| mlx_audio.voice | af_heart | Voice preset (used if no voice_blend) |

| mlx_audio.voice_blend | {af_heart: 0.6, af_sky: 0.4} | Custom voice mix (weighted blend) |

| mlx_audio.lang_code | a | Language code (a=US English) |

| mlx_audio.speed | 1.05 | Playback speed (1.0 = normal, 1.05 = 5% faster) |

Kokoro PyTorch Options (fallback)

| Option | Default | Description |

|--------|---------|-------------|

| kokoro.path | ~/.openclaw/tools/kokoro | Kokoro repo location |

| kokoro.voice_blend | {af_heart: 0.6, af_sky: 0.4} | Custom voice mix |

| kokoro.speed | 1.05 | Playback speed (1.0 = normal, 1.05 = 5% faster) |

Processing Options

| Option | Default | Description |

|--------|---------|-------------|

| processing.subagent_timeout | 600 | Seconds for sub-agent (increase for long videos) |

| processing.cleanup_temp_files | true | Remove /tmp files after completion |

Comment Options

| Option | Default | Description |

|--------|---------|-------------|

| comments.max_count | 50 | Number of comments to fetch |

| comments.timeout | 90 | Timeout for comment fetching (seconds) |

Queue Options

| Option | Default | Description |

|--------|---------|-------------|

| queue.stale_minutes | 30 | Consider a processing job stale after this many minutes |

Output Structure

~/Documents/TubeScribe/
├── {Video Title}.html         # Formatted document (or .docx / .md)
└── {Video Title}_summary.mp3  # Audio summary (or .wav)

After generation, opens the folder (not individual files) so you can access everything.

Dependencies

Required:

• -summarize CLI — brew install steipete/tap/summarize
• -Python 3.8+

Optional (better quality):

• -pandoc — DOCX output: brew install pandoc
• -ffmpeg — MP3 audio: brew install ffmpeg
• -yt-dlp — YouTube comments: brew install yt-dlp
• -mlx-audio — Fastest TTS on Apple Silicon: pip install mlx-audio (uses MLX backend for Kokoro)
• -Kokoro TTS — PyTorch fallback: see https://github.com/hexgrad/kokoro

yt-dlp Search Paths

TubeScribe checks these locations (in order):

| Priority | Path | Source |

|----------|------|--------|

| 1 | which yt-dlp | System PATH |

| 2 | /opt/homebrew/bin/yt-dlp | Homebrew (Apple Silicon) |

| 3 | /usr/local/bin/yt-dlp | Homebrew (Intel) / Linux |

| 4 | ~/.local/bin/yt-dlp | pip install --user |

| 5 | ~/.local/pipx/venvs/yt-dlp/bin/yt-dlp | pipx |

| 6 | ~/.openclaw/tools/yt-dlp/yt-dlp | TubeScribe auto-install |

If not found, setup downloads a standalone binary to the tools directory.

The tools directory version doesn't conflict with system installations.

Queue Handling

When user sends multiple YouTube URLs while one is processing:

Check Before Starting

python skills/tubescribe/scripts/tubescribe.py --queue-status

If Already Processing

Add to queue instead of starting parallel processing
python skills/tubescribe/scripts/tubescribe.py --queue-add "NEW_URL"
→ Replies: "📋 Added to queue (position 2)"

After Completion

Check if more in queue
python skills/tubescribe/scripts/tubescribe.py --queue-next
→ Automatically pops and processes next URL

Queue Commands

| Command | Description |

|---------|-------------|

| --queue-status | Show what's processing + queued items |

| --queue-add URL | Add URL to queue |

| --queue-next | Process next item from queue |

| --queue-clear | Clear entire queue |

Batch Processing (multiple URLs at once)

python skills/tubescribe/scripts/tubescribe.py url1 url2 url3

Processes all URLs sequentially with a summary at the end.

Error Handling

The script detects and reports these errors with clear messages:

| Error | Message |

|-------|---------|

| Invalid URL | ❌ Not a valid YouTube URL |

| Private video | ❌ Video is private — can't access |

| Video removed | ❌ Video not found or removed |

| No captions | ❌ No captions available for this video |

| Age-restricted | ❌ Age-restricted video — can't access without login |

| Region-blocked | ❌ Video blocked in your region |

| Live stream | ❌ Live streams not supported — wait until it ends |

| Network error | ❌ Network error — check your connection |

| Timeout | ❌ Request timed out — try again later |

When an error occurs, report it to the user and don't proceed with that video.

Tips

• -For long videos (>30 min), increase sub-agent timeout to 900s
• -Speaker detection works best with clear interview/podcast formats
• -Single-speaker videos (tutorials, lectures) skip speaker labels automatically
• -Timestamps link directly to YouTube at that moment
• -Use batch mode for multiple videos: tubescribe url1 url2 url3