Agent-Reach/skills/video/skill.md

Video & Podcast Digest Skill

Send a video/podcast link → get full transcript + structured summary

Supported Platforms

Platform	Type	Subtitles	Whisper Transcription
YouTube	Video	✅	✅
Bilibili	Video	✅	✅
X/Twitter	Video	❌	✅
Xiaoyuzhou (小宇宙)	Podcast	❌	✅
Apple Podcasts	Podcast	❌	✅
Direct links (mp3/mp4/m3u8)	Any	❌	✅

Trigger

Auto-triggered when a media URL is detected:

• YouTube: youtube.com, youtu.be
• Bilibili: bilibili.com, b23.tv
• X/Twitter: x.com, twitter.com (tweets with video)
• Xiaoyuzhou: xiaoyuzhoufm.com
• Apple Podcasts: podcasts.apple.com
• Direct: .mp3, .mp4, .m3u8, .m4a, .webm

Pipeline

Step 0: Detect Media Type

URL Pattern	Type	Pipeline
xiaoyuzhoufm.com/episode/	Podcast	→ Step 1b (Xiaoyuzhou)
podcasts.apple.com	Podcast	→ Step 1c (Apple)
bilibili.com, b23.tv	Video	→ Step 1d (Bilibili API)
.mp3, .m4a direct link	Audio	→ Step 2b (direct download)
Other	Video	→ Step 1a (subtitle extraction)

Step 1a: Video — Extract Subtitles

# Clean up temp files
rm -f /tmp/media_sub*.vtt /tmp/media_audio.mp3 /tmp/media_transcript*.json /tmp/media_segment_*.mp3 2>/dev/null || true

# YouTube (prefer English, fallback Chinese)
yt-dlp --skip-download --write-auto-sub --sub-lang "en,zh-Hans" -o "/tmp/media_sub" "VIDEO_URL"

# Bilibili
yt-dlp --skip-download --write-auto-sub --sub-lang "zh-Hans,zh" -o "/tmp/media_sub" "VIDEO_URL"

Check for subtitles:

ls /tmp/media_sub*.vtt 2>/dev/null

• Has subtitles → Read VTT content, skip to Step 3
• No subtitles → Step 2a (download audio)

Step 1b: Xiaoyuzhou (小宇宙) — Extract Audio URL

# Extract CDN direct link from __NEXT_DATA__
# Xiaoyuzhou is a Next.js SPA, but initial HTML contains audio URL in __NEXT_DATA__
AUDIO_URL=$(curl -sL -H "User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36" \
  "EPISODE_URL" \
  | grep -oE 'https://media\.xyzcdn\.net/[^"]+\.(m4a|mp3)' \
  | head -1)

echo "Audio URL: $AUDIO_URL"

# Download audio
curl -L -o /tmp/media_audio.mp3 "$AUDIO_URL"

If curl extraction is empty (rare), fallback: use Puppeteer/browser to get rendered page and extract.

→ Step 2b (check size & transcribe)

Step 1c: Apple Podcasts — via yt-dlp

yt-dlp -f "ba[ext=m4a]/ba/b" --extract-audio --audio-format mp3 --audio-quality 5 \
  -o "/tmp/media_audio.%(ext)s" "APPLE_PODCAST_URL"

→ Step 2b (check size & transcribe)

Step 1d: Bilibili — API Direct Audio Stream

yt-dlp returns 412 for Bilibili even with cookies. Use Bilibili's API instead:

# 1. Extract BV number from URL
BV="BV1xxxxx"  # Replace with actual BV number

# 2. Get video info (title, duration, CID)
curl -s "https://api.bilibili.com/x/web-interface/view?bvid=$BV" \
  -H "User-Agent: Mozilla/5.0" -H "Referer: https://www.bilibili.com/" \
  | python3 -c "import json,sys; d=json.load(sys.stdin)['data']; print(f\"Title: {d['title']}\nDuration: {d['duration']}s\nCID: {d['cid']}\")"

# 3. Get audio stream URL
CID=<CID from previous step>
AUDIO_URL=$(curl -s "https://api.bilibili.com/x/player/playurl?bvid=$BV&cid=$CID&fnval=16&qn=64" \
  -H "User-Agent: Mozilla/5.0" -H "Referer: https://www.bilibili.com/" \
  | python3 -c "import json,sys; print(json.load(sys.stdin)['data']['dash']['audio'][0]['baseUrl'])")

# 4. Download audio (Referer header required, otherwise 403)
curl -L -o /tmp/media_audio.m4s \
  -H "User-Agent: Mozilla/5.0" -H "Referer: https://www.bilibili.com/" "$AUDIO_URL"

# 5. Convert to mp3
ffmpeg -y -i /tmp/media_audio.m4s -acodec libmp3lame -q:a 5 /tmp/media_audio.mp3

→ Step 2b (check size & transcribe)

Step 2a: Video — Download Audio (when no subtitles)

# YouTube may need --cookies-from-browser chrome to bypass bot detection
yt-dlp --cookies-from-browser chrome -f "ba[ext=m4a]/ba/b" --extract-audio --audio-format mp3 --audio-quality 5 \
  -o "/tmp/media_audio.%(ext)s" "VIDEO_URL"

Step 2b: Check Audio Size & Segment

FILE_SIZE=$(stat -f%z /tmp/media_audio.* 2>/dev/null || stat -c%s /tmp/media_audio.* 2>/dev/null)
echo "File size: $FILE_SIZE bytes"

• ≤ 25MB (25000000) → Step 2c (transcribe directly)
• > 25MB → Split first, then transcribe each segment

Splitting large audio (>25MB):

# Get total duration
DURATION=$(ffprobe -v error -show_entries format=duration -of csv=p=0 /tmp/media_audio.* | head -1)

# Split into 10-minute segments (keeps each under 25MB)
SEGMENT_SEC=600
SEGMENTS=$(python3 -c "import math; print(math.ceil(float('$DURATION')/$SEGMENT_SEC))")

# Cut segments
for i in $(seq 0 $((SEGMENTS-1))); do
  START=$((i * SEGMENT_SEC))
  ffmpeg -y -i /tmp/media_audio.* -ss $START -t $SEGMENT_SEC -acodec libmp3lame -q:a 5 \
    "/tmp/media_segment_${i}.mp3" 2>/dev/null
done

→ Call Step 2c for each segment sequentially (parallel triggers Groq 524 timeout), concatenate results

Step 2c: Whisper Transcription

Prerequisite: GROQ_API_KEY environment variable

# Check API key
if [ -z "$GROQ_API_KEY" ]; then
  echo "❌ GROQ_API_KEY not set. Get one at: https://console.groq.com/keys"
  exit 1
fi

# Transcribe single file (replace AUDIO_FILE with actual path)
curl -s -X POST "https://api.groq.com/openai/v1/audio/transcriptions" \
  -H "Authorization: Bearer $GROQ_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "file=@AUDIO_FILE" \
  -F "model=whisper-large-v3-turbo" \
  -F "response_format=verbose_json" \
  -F "language=zh" \
  > /tmp/media_transcript.json

# Extract plain text
python3 -c "import json; print(json.load(open('/tmp/media_transcript.json'))['text'])"

Whisper model options:

Model	Speed	Accuracy	Use Case
whisper-large-v3-turbo	10x realtime	High	Default choice
whisper-large-v3	5x realtime	Highest	Professional/noisy content

Language parameter:

• Chinese: language=zh
• English: language=en
• Auto-detect: omit language parameter

Step 3: Structured Summary

Choose output format based on media type:

Video (≤20 min):

1. Overview (1-2 sentences)
2. Key Points (3-5 bullet points)
3. Notable Quotes (if any)
4. Action Items (if applicable)

Podcast (>20 min):

1. Overview (2-3 sentences: who discussed what)
2. Chapter Summary (segmented by topic, 2-3 sentences each)
3. Key Points (5-8 bullet points)
4. Notable Quotes
5. Action Items (if applicable)

Output Format

Video

## 📺 Video Digest

**Title**: [Video Title]
**Duration**: [x minutes]
**Language**: [Chinese/English]

### Overview
[1-2 sentence summary]

### Key Points
1. [Point 1]
2. [Point 2]
...

### Notable Quotes
> "xxx" — [timestamp]

### Action Items
- [if applicable]

Podcast

## 🎙️ Podcast Digest

**Show**: [Podcast Name]
**Episode**: [Episode Title]
**Duration**: [x minutes]
**Guests**: [if any]

### Overview
[2-3 sentences: who discussed what, core conclusions]

### Chapter Summary
#### 1. [Topic] (~xx:xx-xx:xx)
[2-3 sentences of core content]

#### 2. [Topic] (~xx:xx-xx:xx)
[2-3 sentences of core content]
...

### Key Points
1. [Point 1]
2. [Point 2]
...

### Notable Quotes
> "xxx"

### Action Items
- [if applicable]

Error Handling

Situation	Action
No subtitles + no GROQ_API_KEY	Prompt user to set API key
No subtitles + has API key	Auto Whisper transcription
Xiaoyuzhou curl extraction empty	Use Puppeteer/browser to get rendered HTML
Audio >25MB	ffmpeg segment (10min/segment), transcribe sequentially
Podcast >2 hours	Warn user about duration, confirm before proceeding
Groq 524 timeout	Do NOT parallelize — transcribe sequentially, sleep 5-8s between segments
Groq 429 rate limit	7200s/hour limit, wait for retry-after header, then retry
yt-dlp Bilibili 412	Use Bilibili API instead (Step 1d)
yt-dlp YouTube bot detection	Add --cookies-from-browser chrome
Network timeout	Retry once
Spotify links	Inform user: not supported (DRM protected)

Groq Whisper Limits

• Max 25MB per request
• Free tier: 7200 seconds of audio/hour (rolling window), ~20 hours/day
• Supported formats: mp3, mp4, mpeg, mpga, m4a, wav, webm

Dependencies

• yt-dlp: video download + subtitle extraction
• ffmpeg: audio conversion + segmentation
• curl: Xiaoyuzhou audio download, Bilibili API
• GROQ_API_KEY: Whisper transcription API (free at https://console.groq.com/keys)