Agent skill
deployment-automation
Automate deployment to Vercel platform. Manages deployment configuration, environment setup, and CI/CD integration.
Install this agent skill to your Project
npx add-skill https://github.com/qodex-ai/ai-agent-skills/tree/main/skills/deployment-automation
SKILL.md
Vercel Production Deploy Loop
Instructions
When requested to deploy to Vercel production with automatic error fixing:
-
Initial Deployment Attempt
- Run
vercel --prodto start production deployment - Wait for deployment to complete
- Run
-
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
- CRITICAL: Use Vercel MCP tool to fetch detailed logs:
-
Error Fixing
- Make minimal, targeted fixes to resolve the specific error
-
Retry Deployment
- Run
vercel --prodagain with the fixes applied - Repeat steps until deployment succeeds
- Run
-
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
- Once deployment succeeds, report:
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
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