DevOps
glasses-to-social
Turn smart glasses photos into social media posts.
---
name: glasses-to-social
description: Turn smart glasses photos into social media posts. Monitors a Google Drive folder for new images from Meta Ray-Ban glasses (or any smart glasses), analyzes them with vision AI, drafts tweets/posts in the user's voice, and publishes on approval. Use when setting up a glasses-to-social pipeline, processing smart glasses photos for social media, or creating hands-free content workflows.
---
# Glasses-to-Social
Transform photos from smart glasses into social media posts with AI-generated captions.
## Overview
This skill creates a pipeline from smart glasses (Meta Ray-Ban, etc.) to social media:
1. User snaps photo with glasses
2. Photo syncs to Google Drive folder
3. Agent detects new photo, analyzes with vision
4. Agent drafts post matching user's voice/style
5. User approves, agent publishes
## Setup
### 1. Configure Google Drive Folder
Create a shared Google Drive folder for glasses photos:
```bash
# User creates folder "Glasses-to-Social" in Google Drive
# Share with "Anyone with link can view"
# Copy the folder URL
```
### 2. Set Up Config
Create config file at `glasses-to-social/config.json`:
```json
{
"googleDriveFolderUrl": "https://drive.google.com/drive/folders/YOUR_FOLDER_ID",
"folderId": "YOUR_FOLDER_ID",
"downloadPath": "./glasses-to-social/downloads",
"processedFile": "./glasses-to-social/data/processed.json",
"defaultHashtags": ["#MedicalAI", "#HealthTech"],
"autoPost": false
}
```
### 3. Configure Glasses Auto-Sync
For Meta Ray-Ban glasses:
1. Open Meta View app on phone
2. Settings > Gallery > Enable "Import Automatically"
3. iOS: Enable Google Photos backup (syncs Camera Roll)
4. Create iOS Shortcut to copy new Meta photos to Google Drive folder
## Usage
### Manual Check
Ask the agent to check for new photos:
```
Check my glasses folder for new photos
```
### Automated Monitoring
Set up a cron job to check periodically:
```json
{
"name": "Glasses-to-Social: Check photos",
"schedule": {"kind": "cron", "expr": "*/15 * * * *", "tz": "UTC"},
"payload": {
"message": "Check the Glasses-to-Social folder for new photos. If found, analyze and draft a tweet."
}
}
```
### Processing Flow
When a new photo is detected:
1. Download from Google Drive using `gdown`:
```bash
gdown --folder "FOLDER_URL" -O ./downloads/ --remaining-ok
```
2. Compare against processed list in `data/processed.json`
3. For new photos, analyze with vision:
- Describe the scene/subject
- Identify relevant context for social post
- Note any text, people, or notable elements
4. Draft post matching user's voice:
- Keep it concise and authentic
- Add relevant hashtags
- First-person perspective works well for glasses content
5. Send draft to user for approval:
- Include image preview
- Show proposed caption
- Wait for "POST" confirmation or edits
6. On approval, publish to configured platform (X/Twitter, etc.)
7. Mark photo as processed in `data/processed.json`
## Scripts
### check-new-photos.sh
Checks Google Drive folder for new images:
```bash
scripts/check-new-photos.sh
```
Output format when new photo found:
```
NEW_PHOTO_PATH:/path/to/downloaded/photo.jpg
```
## File Tracking
Track processed photos in `data/processed.json`:
```json
{
"processed": ["photo1.jpg", "photo2.jpg"],
"pending": []
}
```
## Tips
- First-person POV content performs well ("Look what I just saw...")
- Keep captions authentic, not overly polished
- Works great for conferences, interesting sightings, daily moments
- Consider time-of-day context when drafting
## Requirements
- `gdown` Python package for Google Drive access
- Vision-capable model for image analysis
- Twitter/X credentials for posting (optional)
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