Marketplace yolo
git clone https://github.com/aiskillstore/marketplace
T=$(mktemp -d) && git clone --depth=1 https://github.com/aiskillstore/marketplace "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/10k-digital/yolo" ~/.claude/skills/aiskillstore-marketplace-yolo && rm -rf "$T"
skills/10k-digital/yolo/SKILL.mdYolo Mode Automation Skill
This skill automates Lovable deployment workflows using Claude's browser automation capabilities.
When to Activate
This skill should be active when:
- Yolo mode is enabled in CLAUDE.md (
)yolo_mode: on - User runs deployment commands:
- Edge function deployment/deploy-edge
- Database migration application/apply-migration
- After git push to main (if
):auto_deploy: on- Automatically detect backend file changes
- Trigger deployment without manual command
- User mentions yolo automation:
- "use yolo mode"
- "automate the Lovable prompt"
- "submit this to Lovable automatically"
- "browser automation"
Performance Optimization
Model Selection (Hybrid Approach)
For optimal speed + reliability, use different models for different tasks:
Use Haiku for:
- Clicking elements using refs (simple, deterministic)
- Form input operations (
tool calls)form_input - Key presses and simple navigation
- Waiting/polling operations
- Simple element finding with
toolfind
Use Sonnet for:
- Initial page understanding after navigation
- Error detection and recovery decisions
- Parsing Lovable's responses for success/failure
- Deciding next steps when something unexpected happens
- Complex page state analysis
Why this matters:
- Haiku is 3-5x faster for simple operations
- Sonnet provides better reliability for complex reasoning
- Hybrid approach gives best of both: speed + accuracy
Tool Preferences
Always prefer these tools:
andfind
over screenshots for element locationread_page
over click + type for input valuesform_input
parameters over coordinates for clickingref- DOM polling over screenshot-based monitoring
See
references/automation-workflows.md for detailed implementation.
Core Functionality
1. Auto-Detection
When yolo mode is enabled, automatically detect when Lovable prompts are needed:
Edge Function Deployment:
- Files in
modifiedsupabase/functions/ - Changes committed and pushed to
main - Deployment prompt generated
Migration Application:
- New files in
supabase/migrations/ - Changes committed and pushed to
main - Migration prompt generated
See
references/detection-logic.md for complete detection criteria.
1.5. Auto-Deploy After Git Push (NEW)
When
auto_deploy: on is enabled, Claude automatically detects and deploys backend changes after a successful git push:
Trigger: Successful
git push origin main
Detection:
- Analyze files changed in the push
- Check for
orsupabase/functions/
changessupabase/migrations/ - If backend files found AND auto_deploy enabled → trigger automation
Flow:
git push origin main [succeeds] ↓ Claude detects backend file changes ↓ Check: yolo_mode: on AND auto_deploy: on ↓ 🤖 "Auto-deploy: Backend changes detected, starting deployment..." ↓ Execute browser automation ↓ Run verification tests ↓ Show deployment summary
Graceful Fallback: If auto-deploy fails for any reason:
- Show clear error message
- Provide manual prompt as fallback
- Never block the user
See
references/post-push-automation.md for complete implementation.
2. Browser Automation Workflow
When a deployment is needed:
-
Navigate to Lovable
- Read
from CLAUDE.mdlovable_url - Open browser and navigate to project
- Handle login if needed
- Read
-
Submit Prompt
- Locate chat input element
- Type the generated Lovable prompt
- Submit and confirm message sent
-
Monitor Response
- Wait for Lovable's response
- Check for success indicators
- Detect errors or warnings
- Timeout after 3 minutes
See
references/automation-workflows.md for detailed browser automation steps.
3. Testing & Verification
After successful deployment, run tests based on
yolo_testing setting:
If
(default):yolo_testing: on
- Level 1: Basic verification (check logs via Lovable)
- Level 2: Console error checking (monitor production URL)
- Level 3: Functional testing (test endpoints/queries)
If
:yolo_testing: off
- Skip all testing
- Only confirm deployment success from Lovable response
See
references/testing-procedures.md for complete testing workflows.
4. Debug Mode
When
yolo_debug: on, provide verbose output:
🐛 DEBUG: Browser Automation Step 1: Navigating to Lovable URL: https://lovable.dev/projects/abc123 Wait for: Page load complete ✅ Success (1.2s) Step 2: Locating chat interface Selector: textarea[data-testid="chat-input"] Wait for: Element interactable ✅ Found (0.3s) Step 3: Typing prompt Text: "Deploy the send-email edge function" ✅ Typed (0.5s) Step 4: Submitting Action: Press Enter ✅ Submitted (0.1s) Step 5: Monitoring response Watching for: New message from assistant Timeout: 180s ✅ Response received (4.2s) Response content: "I'll deploy the send-email edge function now..." [full response text] Success keywords detected: ['deploy', 'function'] No error keywords found
Configuration in CLAUDE.md
The skill reads these fields from CLAUDE.md:
## Yolo Mode Configuration (Beta) - **Status**: on - **Auto-Deploy**: on - **Deployment Testing**: on - **Auto-run Tests**: off - **Debug Mode**: off - **Last Updated**: 2025-01-03 10:30:00
Configuration options:
- Status: Enable/disable yolo mode entirely
- Auto-Deploy: Auto-deploy after git push (no manual command needed)
- Deployment Testing: Run verification tests after deployments
- Auto-run Tests: Run project test suite after git push
- Debug Mode: Show verbose automation logs
And from Project Overview:
- **Lovable Project URL**: https://lovable.dev/projects/abc123 - **Production URL**: https://my-app.lovable.app
User Notifications
Progress Updates
Show real-time progress during automation:
Standard Mode (debug off):
🤖 Yolo mode: Deploying send-email edge function ⏳ Step 1/8: Navigating to Lovable project... ⏳ Step 2/8: Waiting for GitHub sync... ✅ Step 3/8: Sync verified - Lovable has latest code ✅ Step 4/8: Located chat interface ✅ Step 5/8: Submitted prompt ⏳ Step 6/8: Waiting for Lovable response... ✅ Step 7/8: Deployment confirmed ⏳ Step 8/8: Running verification tests... ✅ Step 8/8: All tests passed
Debug Mode (debug on): Include detailed logs with timing, selectors, and full responses.
Deployment Summary
After automation completes:
## Deployment Summary **Operation:** Edge Function Deployment **Function:** send-email **Status:** ✅ Success **Duration:** 45 seconds **Automation Steps:** 1. ✅ Navigated to Lovable 2. ✅ Submitted deployment prompt 3. ✅ Received deployment confirmation **Verification Tests:** (if testing enabled) 1. ✅ Basic verification: Deployment logs show no errors 2. ✅ Console check: No errors at production URL 3. ✅ Functional test: Function endpoint responds (200 OK) **Production Status:** - Function is live and responding - No errors detected - Ready for use 💡 Yolo mode is enabled. I'll continue automating deployments. Run `/yolo off` to disable.
Error Handling
All automation failures fall back gracefully to manual prompts:
Common Errors
Browser automation not available:
❌ Browser automation unavailable Yolo mode requires the Claude in Chrome extension. Install: https://chrome.google.com/webstore/detail/claude/... Docs: https://docs.claude.com/claude/code-intelligence/browser-automation Fallback - run this prompt manually in Lovable: 📋 "Deploy the send-email edge function"
Login required:
🔐 Please log in to Lovable The browser opened to your Lovable project, but you're not logged in. Please log in and I'll retry automatically. Or run this prompt manually: 📋 "Deploy the send-email edge function"
UI element not found:
❌ Could not locate Lovable chat interface The Lovable UI may have changed since this plugin was created. Fallback - run this prompt manually in Lovable: 📋 "Deploy the send-email edge function" 💡 Please report this issue at: https://github.com/10kdigital/lovable-claude-code/issues
Timeout:
⏱️ Lovable hasn't responded after 3 minutes The operation may still be processing. Please check Lovable manually to verify status. Prompt that was submitted: 📋 "Deploy the send-email edge function"
Deployment failed:
❌ Deployment failed in Lovable Error from Lovable: [captured error message] Suggested fixes: - Check function code for syntax errors - Verify required secrets are set in Cloud → Secrets - Review function logs in Lovable Would you like me to: 1. Review the function code for issues 2. Check if secrets are documented in CLAUDE.md 3. Show you how to access logs in Lovable
Graceful Degradation
When automation fails:
- Capture error details
- Show user-friendly error message
- Provide manual prompt as fallback
- Suggest troubleshooting steps
- Offer to disable yolo mode if errors persist
Never fail silently - always inform user and provide manual options.
Integration with Other Commands
/deploy-edge
When yolo mode is on,
/deploy-edge automatically triggers browser automation:
[... existing deploy-edge logic ...] ## Deployment Execution 1. Check yolo mode status from CLAUDE.md 2. If `yolo_mode: on`: - Activate yolo skill - Execute browser automation workflow - Run tests based on `yolo_testing` setting - Report results 3. If `yolo_mode: off`: - Show manual prompt (current behavior) - Suggest enabling yolo mode
/apply-migration
Same pattern as deploy-edge for migration workflows.
/yolo
The
/yolo command controls this skill:
- Enables skill by setting/yolo onyolo_mode: on
- Disables skill/yolo off- Accepts flags:
,--testing
,--no-testing--debug
Beta Status & Limitations
Beta Warning
Yolo mode is in beta - users should be aware:
✅ What works well:
- Automated prompt submission
- Basic deployment verification
- Error handling with manual fallback
⚠️ Known limitations:
- Requires Claude in Chrome extension
- Lovable UI changes may break automation
- Testing adds 1-3 minutes per deployment
- User must be logged into Lovable
- Only works for edge functions and migrations (not tables, RLS, etc.)
When to Recommend Yolo Mode
✅ Good for:
- Frequent deployments (saves time)
- Users comfortable with browser automation
- Development workflows (fast iteration)
❌ Not ideal for:
- One-off deployments (manual is faster)
- Production deployments requiring extra review
- Users without Chrome extension
- Environments without browser access
Future Enhancements
Not yet implemented, but could be added:
-
Batch operations
- Deploy multiple edge functions at once
- Apply multiple migrations in sequence
-
Rollback support
- Detect deployment failures
- Offer to rollback via Lovable
-
Monitoring mode
- Periodically check logs
- Alert on new errors
-
Custom test scripts
- User-defined test payloads
- Stored in CLAUDE.md
-
Broader operation support
- Table creation
- RLS policies
- Storage buckets
Reference Files
This skill uses these reference documents:
-
references/automation-workflows.md- Browser automation step-by-step
- Lovable UI navigation
- Element selectors and wait conditions
-
references/detection-logic.md- When to trigger automation
- File change detection
- Integration with commands
-
(NEW)references/post-push-automation.md- Auto-deploy after git push
- Graceful fallback handling
- User notification templates
-
references/testing-procedures.md- Level 1: Basic verification
- Level 2: Console checking
- Level 3: Functional testing
Quick Reference
Check if Yolo Mode is Active
1. Read CLAUDE.md 2. Look for "Status: on" in Yolo Mode Configuration 3. If not found or "off", yolo mode is disabled
Check if Auto-Deploy is Enabled
1. Read CLAUDE.md 2. Check both "Status: on" AND "Auto-Deploy: on" 3. Both must be enabled for auto-deploy to trigger
Execute Automation
1. Confirm yolo_mode is on 2. Load automation-workflows.md 3. Execute navigation → submit → monitor workflow 4. Run tests if yolo_testing is on 5. Report results
Auto-Deploy After Git Push
1. Git push succeeds 2. Check for backend file changes (supabase/functions/, supabase/migrations/) 3. If changes found AND auto_deploy enabled: - Trigger automation automatically - Show: "🤖 Auto-deploy: Backend changes detected..." 4. If auto_deploy disabled: - Show notification only - Suggest running /deploy-edge or /apply-migration
Handle Errors
1. Try automation 2. If fails, capture error 3. Show error + manual fallback prompt 4. Never block user - always provide manual option 5. Suggest troubleshooting based on error type
This skill enables hands-free Lovable deployments while maintaining safety through manual fallbacks and comprehensive testing.