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windsurf-debugging-ai

@jeremylongshore/claude-code-plugins-plus-skills
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SKILL.md

name windsurf-debugging-ai
description Use Cascade for intelligent debugging and error analysis. Activate when users mention "debug with ai", "error analysis", "cascade debug", "find bug", or "troubleshoot code". Handles AI-assisted debugging workflows.
allowed-tools Read,Grep,Glob,Bash
version 1.0.0
license MIT
author Jeremy Longshore <jeremy@intentsolutions.io>

Windsurf Debugging AI

Leverage Cascade for intelligent debugging and rapid error resolution.

Directory Structure

project-root/
    .windsurf/
        debug/
            error-patterns.json      # Known error patterns
                # Common error signatures
                # Resolution strategies
                # Prevention recommendations

            debug-sessions/
                session-YYYY-MM-DD.json  # Debug session logs
                    # Error contexts captured
                    # AI analysis results
                    # Resolution steps taken

            breakpoint-sets/
                api-debugging.json       # API debug breakpoints
                    # Request entry points
                    # Response handlers
                    # Error boundaries

                state-debugging.json     # State management breakpoints
                    # State mutation points
                    # Effect triggers
                    # Selector evaluations

    .vscode/
        launch.json                  # Debug configurations
            # Application debug configs
            # Test debug configs
            # Attach configurations

        tasks.json                   # Debug task definitions
            # Pre-debug build tasks
            # Log clearing tasks
            # Environment setup

AI Debugging Features

Error Analysis

  • Stack trace interpretation
  • Root cause identification
  • Similar error matching
  • Fix suggestion generation

Context Gathering

  • Variable state inspection
  • Call stack analysis
  • Log correlation
  • Environment comparison

Configuration Steps

  1. Set Up Debug Environment

    • Configure launch settings
    • Set up source maps
    • Enable debug logging

  2. Train Error Patterns

    • Document common errors
    • Record resolutions
    • Build pattern library

  3. Integrate with Cascade

    • Enable error forwarding
    • Configure analysis depth
    • Set up fix suggestions

Success Criteria

  • 90% root cause identification rate
  • Fix suggestions within 3 interactions
  • 55% reduction in resolution time