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skills/qodex-ai/ai-agent-skills/deployment-automation

deployment-automation

SKILL.md

Vercel Production Deploy Loop

Instructions

When requested to deploy to Vercel production with automatic error fixing:

  1. Initial Deployment Attempt

    • Run vercel --prod to start production deployment
    • Wait for deployment to complete
  2. Error Detection & Analysis

    • CRITICAL: Use Vercel MCP tool to fetch detailed logs:
      • The MCP logs provide much more detail than CLI output
    • Analyze the build logs to identify root cause:
      • Build errors (TypeScript, ESLint, compilation)
      • Runtime errors
      • Environment variable issues
      • Dependency problems
      • Configuration issues
    • Extract specific error messages
  3. Error Fixing

    • Make minimal, targeted fixes to resolve the specific error
  4. Retry Deployment

    • Run vercel --prod again with the fixes applied
    • Repeat steps until deployment succeeds
  5. Success Confirmation

    • Once deployment succeeds, report:
      • Deployment URL
      • All errors that were fixed
      • Summary of changes made
    • Ask if user wants to commit/push the fixes

Loop Exit Conditions

  • ✅ Deployment succeeds
  • ❌ SAME error occurs 5+ times (suggest manual intervention)
  • ❌ User requests to stop

Best Practices

  • Make incremental fixes rather than large refactors
  • Preserve user's code style and patterns when fixing

Example Flow

User: "Deploy to production and fix any errors"

  • Vercel MCP build logs are the PRIMARY source of error information
  • CLI output alone is insufficient for proper error diagnosis
  • Always wait for deployment to complete before fetching logs
  • If errors require user input (like API keys), prompt user immediately
Weekly Installs
19
First Seen
Jan 22, 2026
Installed on
claude-code14
gemini-cli13
trae13
opencode13
antigravity12
codex12