yolo

Browser 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" Automatically navigates to Lovable.dev and submits deployment prompts. Runs verification tests based on configuration. Auto-deploys after git push when enabled.

240 stars

Best use case

yolo is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Browser 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" Automatically navigates to Lovable.dev and submits deployment prompts. Runs verification tests based on configuration. Auto-deploys after git push when enabled.

Browser 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" Automatically navigates to Lovable.dev and submits deployment prompts. Runs verification tests based on configuration. Auto-deploys after git push when enabled.

Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.

Practical example

Example input

Use the "yolo" skill to help with this workflow task. Context: Browser 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"

Automatically navigates to Lovable.dev and submits deployment prompts.
Runs verification tests based on configuration.
Auto-deploys after git push when enabled.

Example output

A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.

When to use this skill

  • Use this skill when you want a reusable workflow rather than writing the same prompt again and again.

When not to use this skill

  • Do not use this when you only need a one-off answer and do not need a reusable workflow.
  • Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/yolo/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/10k-digital/yolo/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/yolo/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How yolo Compares

Feature / AgentyoloStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Browser 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" Automatically navigates to Lovable.dev and submits deployment prompts. Runs verification tests based on configuration. Auto-deploys after git push when enabled.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Yolo Mode Automation Skill

This skill automates Lovable deployment workflows using Claude's browser automation capabilities.

## 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"

## 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. Browser Automation Workflow

When a deployment is needed:

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

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:

```markdown
## 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:
```markdown
- **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:
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:

```markdown
[... 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
- 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:

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/automation-workflows.md`**
   - Browser automation step-by-step
   - Lovable UI navigation
   - Element selectors and wait conditions

2. **`references/detection-logic.md`**
   - When to trigger automation
   - File change detection
   - Integration with commands

3. **`references/post-push-automation.md`** (NEW)
   - Auto-deploy after git push
   - Graceful fallback handling
   - User notification templates

4. **`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.*

Related Skills

azure-quotas

242
from aiskillstore/marketplace

Check/manage Azure quotas and usage across providers. For deployment planning, capacity validation, region selection. WHEN: "check quotas", "service limits", "current usage", "request quota increase", "quota exceeded", "validate capacity", "regional availability", "provisioning limits", "vCPU limit", "how many vCPUs available in my subscription".

DevOps & Infrastructure

raindrop-io

242
from aiskillstore/marketplace

Manage Raindrop.io bookmarks with AI assistance. Save and organize bookmarks, search your collection, manage reading lists, and organize research materials. Use when working with bookmarks, web research, reading lists, or when user mentions Raindrop.io.

Data & Research

zlibrary-to-notebooklm

242
from aiskillstore/marketplace

自动从 Z-Library 下载书籍并上传到 Google NotebookLM。支持 PDF/EPUB 格式,自动转换,一键创建知识库。

discover-skills

242
from aiskillstore/marketplace

当你发现当前可用的技能都不够合适(或用户明确要求你寻找技能)时使用。本技能会基于任务目标和约束,给出一份精简的候选技能清单,帮助你选出最适配当前任务的技能。

web-performance-seo

242
from aiskillstore/marketplace

Fix PageSpeed Insights/Lighthouse accessibility "!" errors caused by contrast audit failures (CSS filters, OKLCH/OKLAB, low opacity, gradient text, image backgrounds). Use for accessibility-driven SEO/performance debugging and remediation.

project-to-obsidian

242
from aiskillstore/marketplace

将代码项目转换为 Obsidian 知识库。当用户提到 obsidian、项目文档、知识库、分析项目、转换项目 时激活。 【激活后必须执行】: 1. 先完整阅读本 SKILL.md 文件 2. 理解 AI 写入规则(默认到 00_Inbox/AI/、追加式、统一 Schema) 3. 执行 STEP 0: 使用 AskUserQuestion 询问用户确认 4. 用户确认后才开始 STEP 1 项目扫描 5. 严格按 STEP 0 → 1 → 2 → 3 → 4 顺序执行 【禁止行为】: - 禁止不读 SKILL.md 就开始分析项目 - 禁止跳过 STEP 0 用户确认 - 禁止直接在 30_Resources 创建(先到 00_Inbox/AI/) - 禁止自作主张决定输出位置

obsidian-helper

242
from aiskillstore/marketplace

Obsidian 智能笔记助手。当用户提到 obsidian、日记、笔记、知识库、capture、review 时激活。 【激活后必须执行】: 1. 先完整阅读本 SKILL.md 文件 2. 理解 AI 写入三条硬规矩(00_Inbox/AI/、追加式、白名单字段) 3. 按 STEP 0 → STEP 1 → ... 顺序执行 4. 不要跳过任何步骤,不要自作主张 【禁止行为】: - 禁止不读 SKILL.md 就开始工作 - 禁止跳过用户确认步骤 - 禁止在非 00_Inbox/AI/ 位置创建新笔记(除非用户明确指定)

internationalizing-websites

242
from aiskillstore/marketplace

Adds multi-language support to Next.js websites with proper SEO configuration including hreflang tags, localized sitemaps, and language-specific content. Use when adding new languages, setting up i18n, optimizing for international SEO, or when user mentions localization, translation, multi-language, or specific languages like Japanese, Korean, Chinese.

google-official-seo-guide

242
from aiskillstore/marketplace

Official Google SEO guide covering search optimization, best practices, Search Console, crawling, indexing, and improving website search visibility based on official Google documentation

github-release-assistant

242
from aiskillstore/marketplace

Generate bilingual GitHub release documentation (README.md + README.zh.md) from repo metadata and user input, and guide release prep with git add/commit/push. Use when the user asks to write or polish README files, create bilingual docs, prepare a GitHub release, or mentions release assistant/README generation.

doc-sync-tool

242
from aiskillstore/marketplace

自动同步项目中的 Agents.md、claude.md 和 gemini.md 文件,保持内容一致性。支持自动监听和手动触发。

deploying-to-production

242
from aiskillstore/marketplace

Automate creating a GitHub repository and deploying a web project to Vercel. Use when the user asks to deploy a website/app to production, publish a project, or set up GitHub + Vercel deployment.