glasses-to-social

# 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)