/setup-monitoring

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🚨 EXECUTION NOTICE FOR CLAUDE

When you invoke this command via SlashCommand, the system returns THESE INSTRUCTIONS below.

YOU are the executor. This is NOT an autonomous subprocess.

• ✅ The phases below are YOUR execution checklist
• ✅ YOU must run each phase immediately using tools (Bash, Read, Write, Edit, TodoWrite)
• ✅ Complete ALL phases before considering this command done
• ❌ DON't wait for "the command to complete" - YOU complete it by executing the phases
• ❌ DON't treat this as status output - it IS your instruction set

Immediately after SlashCommand returns, start executing Phase 0, then Phase 1, etc.

See @CLAUDE.md section "SlashCommand Execution - YOU Are The Executor" for detailed explanation.

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Security Requirements

CRITICAL: All generated files must follow docs/security/SECURITY-RULES.md Never hardcode API keys. Use placeholders: your_service_key_here

Arguments: $ARGUMENTS

Goal: Set up production monitoring and observability for deployed applications

Core Principles:

• Capture errors and exceptions automatically
• Monitor performance and availability
• Set up alerts for critical issues
• Support multiple monitoring platforms

Phase 1: Discovery

Goal: Understand project structure and detect framework

Actions:

• Get project name from directory or package.json:
  • !{bash basename $(pwd)}
  • @package.json (extract name field if exists)
• Detect project type and framework:
  • !{bash ls -1 package.json requirements.txt pyproject.toml go.mod 2>/dev/null}
  • Check for Next.js: !{bash grep -q "next" package.json 2>/dev/null && echo "nextjs" || echo ""}
  • Check for React: !{bash grep -q "react" package.json 2>/dev/null && echo "react" || echo ""}
  • Check for Python: !{bash test -f requirements.txt && echo "python" || echo ""}
  • Check for FastAPI: !{bash grep -q "fastapi" requirements.txt 2>/dev/null && echo "fastapi" || echo ""}
  • Check for Django: !{bash grep -q "django" requirements.txt 2>/dev/null && echo "django" || echo ""}
• Store detected platform for later use
• Display: "Detected platform: [Next.js|React|Python|etc]"

Phase 2: Platform Selection

Goal: Choose monitoring platform and verify setup

Actions:

• If $ARGUMENTS is "sentry", proceed with Sentry setup
• If $ARGUMENTS is "datadog", proceed with DataDog setup
• Otherwise, use AskUserQuestion:
  • Which platform? (Sentry recommended, DataDog, New Relic)
  • Note: Sentry has MCP integration for automatic setup

Phase 3: Sentry Project Setup via MCP (Sentry Only)

Goal: Use Sentry MCP to find or create project

Actions: CRITICAL: Use MCP tools to automate Sentry setup

1. List Sentry organizations via MCP:

   • Use mcp__plugin_deployment_sentry__find_organizations
   • If multiple orgs, ask user to select one
   • If only one org, use it automatically

2. Check if project already exists via MCP:

   • Use mcp__plugin_deployment_sentry__find_projects with org slug
   • Search for project matching current project name
   • If found: Display "✓ Project exists: [project-name]"
   • If not found: Proceed to create project

3. Map detected framework to Sentry platform:

   • Next.js → "javascript-nextjs"
   • React → "javascript-react"
   • Python + FastAPI → "python-fastapi"
   • Python + Django → "python-django"
   • Python (generic) → "python"
   • Node.js → "node"
   • Go → "go"
   • Default → Ask user for platform

4. Create Sentry project via MCP (if doesn't exist):

   • Use mcp__plugin_deployment_sentry__create_project
   • Parameters: organizationSlug, name, platform
   • Display: "✓ Sentry project created: [project-name]"

5. Get project DSN via MCP:

   • Use mcp__plugin_deployment_sentry__find_dsns
   • Parameters: organizationSlug, projectSlug
   • Store DSN for Phase 4
   • Display: "✓ DSN retrieved"

Phase 4: Execute Monitoring Setup via Agent

Goal: Install dependencies, configure Doppler, integrate code, setup Sentry CLI

Actions:

• Invoke monitoring-setup-executor agent with parameters:
  • project_name: from Phase 1
  • project_platform: from Phase 1
  • monitoring_platform: from Phase 2
  • sentry_org_slug: from Phase 3 (if Sentry)
  • sentry_project_slug: from Phase 3 (if Sentry)
  • sentry_dsn: from Phase 3 (if Sentry)
• Agent will:
  • Install monitoring SDK dependencies
  • Configure Doppler storage for secrets
  • Create .env.example with placeholders
  • Integrate monitoring into application code
  • Install and configure Sentry CLI
  • Create alert configuration
  • Add CI/CD integration steps

Use Task() to invoke agent:

Task(agent="monitoring-setup-executor", parameters={
  "project_name": "<project_name>", "project_platform": "<platform>", "monitoring_platform": "<sentry|datadog>", "sentry_org_slug": "<org_slug>", "sentry_project_slug": "<project_slug>", "sentry_dsn": "<dsn>"
})

Phase 5: Summary

Goal: Report setup status and next steps

Actions:

• Parse agent response JSON

• Display monitoring setup summary:

  ✅ Monitoring Setup Complete
  
  Platform: <Sentry|DataDog|etc>
  Dependencies: <Installed SDK packages>
  Doppler Secrets: <List of secrets configured>
  Integration: <Modified entry points>
  Sentry CLI: <Installed|Not applicable>
  CI/CD: <Integration added|Not configured>
  

• List required environment variables:

  • For Sentry: SENTRY_DSN, SENTRY_AUTH_TOKEN, SENTRY_ORG_SLUG, SENTRY_PROJECT_SLUG
  • For DataDog: DD_API_KEY, DD_APP_KEY, DD_SITE
  • All: MONITORING_ENVIRONMENT (production/staging)

• Provide next steps:

  1. Generate auth token (if Sentry):

     • Visit: https://sentry.io/settings/account/api/auth-tokens/
     • Create token with: project:releases, project:write

  2. Add secrets to Doppler:

     doppler secrets set SENTRY_AUTH_TOKEN="<your-token>" --config production
     doppler secrets set SENTRY_DSN="<dsn>" --config production
     doppler secrets set SENTRY_ORG_SLUG="<org>" --config production
     doppler secrets set SENTRY_PROJECT_SLUG="<project>" --config production
     

  3. Test locally with Doppler: doppler run -- npm run dev

  4. Deploy application to trigger monitoring

  5. Verify Sentry MCP: "Show me the latest errors"

  6. Test Sentry CLI: sentry-cli releases list

• Display integration summary:

  • MCP Server: Query issues, create alerts (via .mcp.json)
  • Sentry CLI: Create releases, upload source maps, track deploys
  • SDK: Capture errors and performance in application code
  • All three use same Doppler-managed credentials ✓

• If agent returned errors:

  • Display error details
  • Provide troubleshooting steps
  • Suggest manual setup if automation failed