Deep Debug

What it does

The deep-debug skill enables AI agents to perform advanced debugging tasks by analyzing code errors, stack traces, and logs. It helps identify root causes of failures and suggests targeted fixes for complex issues in software development workflows.

When to use it

• You encounter cryptic error messages or unhandled exceptions in your application.
• You need to trace the origin of a bug across multiple layers of code logic.
• Your team requires automated analysis of CI/CD pipeline failure logs.
• You want an AI agent to generate hypotheses for why a specific feature is malfunctioning.

Key capabilities

• Parses and interprets detailed stack traces and error logs.
• Correlates disparate log entries to reconstruct execution flow.
• Identifies potential root causes based on context and code patterns.
• Suggests concrete remediation steps or code patches.

Example prompts

• "Analyze this Node.js crash log and explain why the server is exiting unexpectedly."
• "Review the provided Python traceback and suggest a fix for the recursion depth error."
• "Debug this failing unit test by examining the stack trace and proposing a code change."

Tips & gotchas

Ensure you provide full context, including relevant code snippets and complete error logs, to maximize accuracy. Avoid sharing sensitive production data or credentials within your prompts.