home / skills / jeremylongshore / claude-code-plugins-plus-skills / windsurf-debugging-ai

windsurf-debugging-ai skill

/plugins/saas-packs/skill-databases/windsurf/skills/windsurf-debugging-ai

This skill enables AI-assisted debugging with Cascade to analyze errors, identify root causes, and suggest fixes for faster resolution.

npx playbooks add skill jeremylongshore/claude-code-plugins-plus-skills --skill windsurf-debugging-ai

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SKILL.md

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---
name: "windsurf-debugging-ai"
description: |
  Execute 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. Use when debugging issues or troubleshooting. Trigger with phrases like "windsurf debugging ai", "windsurf ai", "windsurf".
allowed-tools: "Read,Grep,Glob,Bash(cmd:*)"
version: 1.0.0
license: MIT
author: "Jeremy Longshore <[email protected]>"
---

# Windsurf Debugging Ai

## Overview

This skill enables AI-assisted debugging within Windsurf. Cascade analyzes error messages, stack traces, and code context to identify root causes and suggest fixes. It learns from your codebase patterns to provide contextually relevant debugging assistance, reducing time spent on common errors and helping identify subtle bugs that might otherwise be missed.

## Prerequisites

- Windsurf IDE with Cascade enabled
- Application with reproducible issues
- Debug configuration set up
- Error logs accessible
- Understanding of application architecture

## Instructions

1. **Capture Error Context**
2. **Analyze with Cascade**
3. **Investigate Root Cause**
4. **Apply Fix**
5. **Document for Prevention**


See `{baseDir}/references/implementation.md` for detailed implementation guide.

## Output

- Root cause analysis
- Fix recommendations
- Debug session logs
- Prevention strategies

## Error Handling

See `{baseDir}/references/errors.md` for comprehensive error handling.

## Examples

See `{baseDir}/references/examples.md` for detailed examples.

## Resources

- [Windsurf Debugging Guide](https://docs.windsurf.ai/features/debugging)
- [AI-Assisted Debugging](https://docs.windsurf.ai/cascade/debugging)
- [Debug Configuration Reference](https://docs.windsurf.ai/reference/debug-config)

Overview

This skill provides AI-assisted debugging for Windsurf using Cascade to analyze errors, stack traces, and code context. It identifies root causes, suggests concrete fixes, and generates prevention strategies to reduce time spent on recurring and subtle bugs. Activate it with trigger phrases like "debug with ai", "cascade debug", or "windsurf debugging ai" for guided troubleshooting workflows.

How this skill works

The skill captures error context (logs, stack traces, failing inputs) and runs Cascade analysis to correlate symptoms with code paths and historical patterns in the codebase. It produces a prioritized root cause analysis, step-by-step reproduction suggestions, and targeted remediation steps you can apply or test. Outputs include debug session logs and short explanations to help you document fixes and prevent regressions.

When to use it

When you have reproducible errors or failing tests and need root cause insight
When stack traces and logs are dense and you need correlation across files
During incident response to speed up triage and propose safe mitigations
When subtle or intermittent bugs evade conventional debugging
To generate reproducible reproduction steps and test cases from failures

Best practices

Provide full error context: stack traces, recent code changes, and environment details
Attach minimal reproducible examples or failing test cases when possible
Run debugging sessions against a staging or local environment, not production
Iterate: apply suggested fixes in small steps and re-run the analyzer
Save debug session logs and remediation notes to improve future diagnostics

Example use cases

Analyze a null pointer exception with multiple entry points to find the true origin
Triage a production crash by correlating logs from different services and proposing hotfixes
Convert flaky test failures into deterministic unit tests and suggest fixes
Identify configuration mismatches that cause environment-specific bugs
Document a recurring bug with root cause and prevention strategy for the team

FAQ

What inputs does the skill need to be effective?

Provide error logs, stack traces, relevant source files, and any recent changes or failing test cases for best results.

Can I run this against production systems?

The analyzer can process production logs, but apply suggested fixes in safe environments first and follow your incident response policies.