yolo

name

yolo

description

Automation skill for Lovable deployments. Activates when: - yolo_mode: on in CLAUDE.md - Running /deploy-edge or /apply-migration commands - After git push when auto_deploy: on (automatic detection) - Any mention of "yolo mode", "automate Lovable", "browser automation", "Lovable MCP" Uses Lovable MCP (preferred) or browser automation to submit deployment prompts. Runs verification tests based on configuration. Auto-deploys after git push when enabled.

Yolo Mode Automation Skill

This skill automates Lovable deployment workflows using either the Lovable MCP server (preferred) or Claude's browser automation as a fallback.

When to Activate

This skill should be active when:

1. Yolo mode is enabled in CLAUDE.md (yolo_mode: on)
2. User runs deployment commands:
   • /deploy-edge - Edge function deployment
   • /apply-migration - Database migration application
3. After git push to main (if auto_deploy: on):
   • Automatically detect backend file changes
   • Trigger deployment without manual command
4. User mentions yolo automation:
   • "use yolo mode"
   • "automate the Lovable prompt"
   • "submit this to Lovable automatically"
   • "browser automation"

Deployment Method Priority

When yolo mode triggers, always choose the deployment method in this order:

1. Lovable MCP (Preferred)

Check if Lovable MCP tools are available (look for send_message from a Lovable MCP connector):

• If available: Use the MCP workflow (references/mcp-workflows.md)

  • Extract project ID from lovable_url in CLAUDE.md
  • Call send_message(project_id, prompt)
  • Poll for response if async
  • Run verification tests as configured

• Why preferred: 3-5x faster, no Chrome extension needed, unaffected by UI changes

2. Browser Automation (Fallback)

If MCP is not available or Deployment Method: browser is set in CLAUDE.md:

• Use Claude's browser automation (references/automation-workflows.md)
• Navigate to Lovable, submit prompt via chat interface
• Monitor for response

3. Manual Prompt (Last Resort)

If both MCP and browser automation fail:

• Show the deployment prompt to the user for copy-paste into Lovable
• Never block the user - always provide a manual fallback

Checking Deployment Method

Read Deployment Method from the Yolo Mode Configuration section of CLAUDE.md:

• auto (default): Try MCP first, fall back to browser
• mcp: Use MCP only, fall back to manual prompt (skip browser)
• browser: Use browser automation only (skip MCP check)

---

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 (form_input tool calls)
• Key presses and simple navigation
• Waiting/polling operations
• Simple element finding with find tool

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:

• find and read_page over screenshots for element location
• form_input over click + type for input values
• ref parameters over coordinates for clicking
• 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 supabase/functions/ modified
• 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:

1. Analyze files changed in the push
2. Check for supabase/functions/ or supabase/migrations/ changes
3. 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. Deployment Execution

When a deployment is needed, execute based on the chosen method:

MCP Method:

1. Extract project ID from lovable_url in CLAUDE.md
2. Call Lovable MCP send_message with the deployment prompt
3. Poll for completion if the response is async
4. Parse success/failure from response

See references/mcp-workflows.md for full MCP workflow.

Browser Automation Method:

1. Navigate to Lovable

   • Read lovable_url from CLAUDE.md
   • Open browser and navigate to project
   • Handle login if needed

2. Submit Prompt

   • Locate chat input element
   • Type the generated Lovable prompt
   • Submit and confirm message sent

3. 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 yolo_testing: on (default):

• 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

Level 4 (optional): Preview test plans If the project has preview testing enabled (CLAUDE.md → Preview Testing Configuration) and Test After Deploy is smoke or all, run the corresponding test plans against the Lovable Preview app after deployment verification. This is handled by the testing skill (skills/testing/SKILL.md) - equivalent to /lovable:test-run --smoke (or --all).

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
- **Deployment Method**: auto
- **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
• Deployment Method: auto (MCP first, then browser), mcp (MCP only), or browser (browser only)
• 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:

MCP Mode (debug off):

🤖 Yolo mode (MCP): Deploying send-email edge function

⏳ Sending deployment prompt via Lovable MCP...
✅ Deployment confirmed by Lovable (3.1s)
⏳ Running verification tests...
✅ All tests passed

Browser 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

MCP not connected (auto mode - will try browser next):

⚠️ Lovable MCP not connected - trying browser automation...
[continues with browser automation]

MCP not connected (mcp-only mode):

❌ Lovable MCP not available

Deployment Method is set to "mcp" but Lovable MCP tools are not connected.

To connect: /lovable:connect-mcp
To use browser automation instead: /lovable:yolo on --browser

Fallback - run this prompt manually in Lovable:
📋 "Deploy the send-email edge function"

Browser automation not available:

❌ Browser automation unavailable

Yolo mode requires the Claude in Chrome extension.

Install: https://chrome.google.com/webstore/detail/claude/...

Tip: Use Lovable MCP instead (no extension needed):
  /lovable:connect-mcp

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:

1. Capture error details
2. Show user-friendly error message
3. Provide manual prompt as fallback
4. Suggest troubleshooting steps
5. 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:

• /yolo on - Enables skill by setting yolo_mode: on
• /yolo off - Disables skill
• 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 via MCP (preferred) or browser
• Basic deployment verification
• Error handling with manual fallback

⚠️ Known limitations (MCP mode):

• Requires Lovable Pro plan
• Requires initial OAuth setup (/lovable:connect-mcp)
• Uses Lovable credits for send_message calls

⚠️ Known limitations (browser mode):

• Requires Claude in Chrome extension
• Lovable UI changes may break automation
• User must be logged into Lovable

⚠️ Shared limitations:

• Testing adds 1-3 minutes per deployment
• 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:

1. Batch operations

   • Deploy multiple edge functions at once
   • Apply multiple migrations in sequence

2. Rollback support

   • Detect deployment failures
   • Offer to rollback via Lovable

3. Monitoring mode

   • Periodically check logs
   • Alert on new errors

4. Custom test scripts

   • User-defined test payloads
   • Stored in CLAUDE.md

5. Broader operation support

   • Table creation
   • RLS policies
   • Storage buckets

Reference Files

This skill uses these reference documents:

1. references/mcp-workflows.md (NEW - preferred)

   • Lovable MCP send_message workflow
   • Project ID extraction
   • MCP error handling and fallbacks

2. references/automation-workflows.md

   • Browser automation step-by-step
   • Lovable UI navigation
   • Element selectors and wait conditions

3. references/detection-logic.md

   • When to trigger automation
   • File change detection
   • Integration with commands

4. references/post-push-automation.md

   • Auto-deploy after git push
   • Graceful fallback handling
   • User notification templates

5. 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. Read Deployment Method from CLAUDE.md (auto / mcp / browser)
3. If auto or mcp:
   - Check if Lovable MCP tools are available
   - If yes → Load mcp-workflows.md and execute MCP workflow
   - If no and auto → fall through to browser
4. If auto or browser:
   - Load automation-workflows.md
   - Execute navigation → submit → monitor workflow
5. Run tests if yolo_testing is on
6. 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.