Log Analyzer

What it does

The Log Analyzer skill helps AI agents analyze application logs to diagnose issues, track errors, and understand system behavior. It supports log searching, pattern detection, structured logging, and integration with monitoring tools. The skill emphasizes using structured logs with relevant metadata and appropriate severity levels for effective troubleshooting and performance monitoring.

When to use it

• Troubleshooting application errors (e.g., "Database connection failed").
• Identifying unexpected but handled events (e.g., "Retry succeeded after failure").
• Tracking normal operational milestones (e.g., "User signed up").
• Understanding detailed diagnostic information during debugging (e.g., “Query executed in 50ms”).
• Analyzing log data to correlate events across different services.

Key capabilities

• Log searching and pattern detection
• Support for structured logging formats (Winston, Pino)
• Recognition of standard log levels: ERROR, WARN, INFO, DEBUG, TRACE
• Emphasis on including context with log entries (e.g., user ID, email, service name)
• Ability to log errors with stack traces

Example prompts

• "Analyze the logs for any database connection errors."
• "Show me all 'INFO' level logs related to user signups."
• "Find patterns in the logs that correlate payment failures with provider issues."

Tips & gotchas

• The skill works best when applications use structured logging formats like Winston or Pino.
• Ensure log levels are used consistently and appropriately for accurate analysis.
• Providing context within log entries (e.g., user ID, request ID) significantly improves the effectiveness of the analysis.