instagram-reels

Original source / Raw SKILL.md

---
name: instagram-reels
version: "1.0.0"
description: Download Instagram Reels, transcribe audio, and extract captions. Share a reel URL and get back a full transcript with the original description.
metadata:
  openclaw:
    requires:
      env:
        - GROQ_API_KEY
      bins:
        - curl
        - yt-dlp
        - ffmpeg
        - python3
    primaryEnv: GROQ_API_KEY
    homepage: https://groq.com
---

# Instagram Reels Skill

Download Instagram Reels, transcribe the audio, and extract the caption/description.

## Setup

1. Install required tools:

```bash
pip install yt-dlp
apt install ffmpeg    # or: brew install ffmpeg
```

2. Get a free Groq API key at [https://console.groq.com](https://console.groq.com)
3. Set your environment variable:

```bash
export GROQ_API_KEY="your-groq-api-key"
```

## Usage

Process a reel in three steps: extract metadata, download audio, transcribe.

### Step 1: Extract metadata and audio URL

```bash
yt-dlp --write-info-json --skip-download -o "/tmp/reel" "REEL_URL"
```

This writes `/tmp/reel.info.json` with the caption, uploader, CDN URLs, and other metadata. No login required for public reels.

### Step 2: Download audio and convert to mp3

Extract the audio CDN URL from metadata and download it directly:

```bash
AUDIO_URL=$(python3 -c "
import json
d = json.load(open('/tmp/reel.info.json'))
for f in d.get('formats', []):
    if f.get('ext') == 'm4a':
        print(f['url'])
        break
")
curl -sL "$AUDIO_URL" -o /tmp/reel-audio.m4a
ffmpeg -y -i /tmp/reel-audio.m4a -acodec libmp3lame -q:a 4 /tmp/reel-audio.mp3
```

### Step 3: Transcribe with Groq Whisper

```bash
curl -s https://api.groq.com/openai/v1/audio/transcriptions \
  -H "Authorization: Bearer $GROQ_API_KEY" \
  -F "file=@/tmp/reel-audio.mp3" \
  -F "model=whisper-large-v3-turbo" \
  -F "response_format=verbose_json"
```

Returns JSON with `text` (full transcript) and `segments` (with timestamps). Language is auto-detected.

### Extract caption from metadata

```bash
python3 -c "
import json
d = json.load(open('/tmp/reel.info.json'))
print('Caption:', d.get('description', 'No caption'))
print('Author:', d.get('uploader', 'Unknown'))
print('Duration:', round(d.get('duration', 0)), 'seconds')
"
```

## Notes

- Metadata extraction works on public reels without authentication
- For private reels, pass cookies: `yt-dlp --cookies /path/to/cookies.txt --write-info-json --skip-download -o "/tmp/reel" "REEL_URL"`
- Export cookies with a browser extension like "Get cookies.txt LOCALLY"
- Groq Whisper is free (rate-limited) and returns results in ~1-2 seconds
- Max audio length: 25 minutes per request
- Clean up temp files after: `rm -f /tmp/reel.info.json /tmp/reel-audio.*`
- Also works with TikTok, YouTube Shorts, and other platforms supported by yt-dlp

## Examples

```bash
# Full transcription pipeline
yt-dlp --write-info-json --skip-download -o "/tmp/reel" "https://www.instagram.com/reel/ABC123/" && \
AUDIO_URL=$(python3 -c "import json; [print(f['url']) for f in json.load(open('/tmp/reel.info.json')).get('formats',[]) if f.get('ext')=='m4a'][:1]") && \
curl -sL "$AUDIO_URL" -o /tmp/reel-audio.m4a && \
ffmpeg -y -i /tmp/reel-audio.m4a -acodec libmp3lame -q:a 4 /tmp/reel-audio.mp3 2>/dev/null && \
curl -s https://api.groq.com/openai/v1/audio/transcriptions \
  -H "Authorization: Bearer $GROQ_API_KEY" \
  -F "file=@/tmp/reel-audio.mp3" \
  -F "model=whisper-large-v3-turbo" \
  -F "response_format=verbose_json"

# Just get the caption (no transcription)
yt-dlp --write-info-json --skip-download -o "/tmp/reel" "https://www.instagram.com/reel/ABC123/" && \
python3 -c "import json; d=json.load(open('/tmp/reel.info.json')); print(d.get('description',''))"

# Transcribe a TikTok video (same pipeline)
yt-dlp --write-info-json --skip-download -o "/tmp/reel" "https://www.tiktok.com/@user/video/123" && \
AUDIO_URL=$(python3 -c "import json; [print(f['url']) for f in json.load(open('/tmp/reel.info.json')).get('formats',[]) if f.get('ext')=='m4a'][:1]") && \
curl -sL "$AUDIO_URL" -o /tmp/reel-audio.m4a && \
ffmpeg -y -i /tmp/reel-audio.m4a -acodec libmp3lame -q:a 4 /tmp/reel-audio.mp3 2>/dev/null && \
curl -s https://api.groq.com/openai/v1/audio/transcriptions \
  -H "Authorization: Bearer $GROQ_API_KEY" \
  -F "file=@/tmp/reel-audio.mp3" \
  -F "model=whisper-large-v3-turbo" \
  -F "response_format=verbose_json"
```


---

## Skill Companion Files

> Additional files collected from the skill directory layout.

### _meta.json

```json
{
  "owner": "antoinedc",
  "slug": "instagram-reels",
  "displayName": "Instagram Reels",
  "latest": {
    "version": "1.0.0",
    "publishedAt": 1770995490281,
    "commit": "https://github.com/openclaw/skills/commit/6591eaae88c94a1de5ad2898005e86ef7ccdfa0a"
  },
  "history": []
}

```