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Systematic error diagnosis and resolution using first-principle analysis. Use when encountering any error message, stack trace, or unexpected behavior. Supports replay functionality to record and reuse solutions.

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SKILL.md

name Error Resolver
description Systematic error diagnosis and resolution using first-principle analysis. Use when encountering any error message, stack trace, or unexpected behavior. Supports replay functionality to record and reuse solutions.

Error Resolver

A first-principle approach to diagnosing and resolving errors across all languages and frameworks.

Core Philosophy

The 5-step Error Resolution Process:

1. CLASSIFY  ->  2. PARSE  ->  3. MATCH  ->  4. ANALYZE  ->  5. RESOLVE
     |              |             |             |              |
  What type?    Extract key    Known       Root cause      Fix +
               information    pattern?     analysis       Prevent

Quick Start

When you encounter an error:

  1. Paste the full error (including stack trace if available)
  2. Provide context (what were you trying to do?)
  3. Share relevant code (the file/function involved)

Error Classification Framework

Primary Categories

Category Indicators Common Causes
Syntax Parse error, Unexpected token Typos, missing brackets, invalid syntax
Type TypeError, type mismatch Wrong data type, null/undefined access
Reference ReferenceError, NameError Undefined variable, scope issues
Runtime RuntimeError, Exception Logic errors, invalid operations
Network ECONNREFUSED, timeout, 4xx/5xx Connection issues, wrong URL, server down
Permission EACCES, PermissionError File/directory access, sudo needed
Dependency ModuleNotFound, Cannot find module Missing package, version mismatch
Configuration Config error, env missing Wrong settings, missing env vars
Database Connection refused, query error DB down, wrong credentials, bad query
Memory OOM, heap out of memory Memory leak, large data processing

Secondary Attributes

  • Severity: Fatal / Error / Warning / Info
  • Scope: Build-time / Runtime / Test-time
  • Origin: User code / Framework / Third-party / System

Analysis Workflow

Step 1: Classify

Identify the error category by examining:

  • Error name/code (e.g., ENOENT, TypeError)
  • Error message keywords
  • Where it occurred (compile, runtime, test)

Step 2: Parse

Extract key information:

- Error code: [specific code if any]
- File path: [where the error originated]
- Line number: [exact line if available]
- Function/method: [context of the error]
- Variable/value: [what was involved]
- Stack trace depth: [how deep is the call stack]

Step 3: Match Patterns

Check against known error patterns:

  • See patterns/ directory for language-specific patterns
  • Match error signatures to known solutions
  • Check replay history for previous solutions

Step 4: Root Cause Analysis

Apply the 5 Whys technique:

Error: Cannot read property 'name' of undefined
  Why 1? -> user object is undefined
  Why 2? -> API call returned null
  Why 3? -> User ID doesn't exist in database
  Why 4? -> ID was from stale cache
  Why 5? -> Cache invalidation not implemented

Root Cause: Missing cache invalidation logic

Step 5: Resolve

Generate actionable solution:

  1. Immediate fix - Get it working now
  2. Proper fix - The right way to solve it
  3. Prevention - How to avoid in the future

Output Format

When resolving an error, provide:

## Error Diagnosis

**Classification**: [Category] / [Severity] / [Scope]

**Error Signature**:
- Code: [error code]
- Type: [error type]
- Location: [file:line]

## Root Cause

[Explanation of why this error occurred]

**Contributing Factors**:
1. [Factor 1]
2. [Factor 2]

## Solution

### Immediate Fix
[Quick steps to resolve]

### Code Change
[Specific code to add/modify]

### Verification
[How to verify the fix works]

## Prevention

[How to prevent this error in the future]

## Replay Tag

[Unique identifier for this solution - for future reference]

Replay System

The replay system records successful solutions for future reference.

Recording a Solution

After resolving an error, record it:

# Create solution record in project
mkdir -p .claude/error-solutions

# Solution file format: [error-type]-[hash].yaml

Solution Record Format

# .claude/error-solutions/[error-signature].yaml
id: "nodejs-module-not-found-express"
created: "2024-01-15T10:30:00Z"
updated: "2024-01-20T14:22:00Z"

error:
  type: "dependency"
  category: "ModuleNotFound"
  language: "nodejs"
  pattern: "Cannot find module 'express'"
  context: "npm project, missing dependency"

diagnosis:
  root_cause: "Package not installed or node_modules corrupted"
  factors:
    - "Missing npm install after git clone"
    - "Corrupted node_modules directory"
    - "Package not in package.json"

solution:
  immediate:
    - "Run: npm install express"
  proper:
    - "Check package.json has express listed"
    - "Run: rm -rf node_modules && npm install"
  code_change: null

verification:
  - "Run the application again"
  - "Check express is in node_modules"

prevention:
  - "Add npm install to project setup docs"
  - "Use npm ci in CI/CD pipelines"

metadata:
  occurrences: 5
  last_resolved: "2024-01-20T14:22:00Z"
  success_rate: 1.0
  tags: ["nodejs", "npm", "dependency"]

Replay Lookup

When encountering an error:

  1. Generate error signature from the error message
  2. Search .claude/error-solutions/ for matching patterns
  3. If found, apply the recorded solution
  4. If new, proceed with full analysis and record the solution

Error Signature Generation

signature = hash(
  error_type +
  error_code +
  normalized_message +  # remove specific values
  language +
  framework
)

Example transformations:

  • Cannot find module 'express' -> Cannot find module '{module}'
  • TypeError: Cannot read property 'name' of undefined -> TypeError: Cannot read property '{prop}' of undefined

Debug Commands

Useful commands during debugging:

Node.js

# Verbose error output
NODE_DEBUG=* node app.js

# Memory debugging
node --inspect app.js

# Check installed packages
npm ls [package-name]

# Verify package.json
npm ls --depth=0

Python

# Debug mode
python -m pdb script.py

# Check installed packages
pip show [package-name]
pip list

General

# Check file permissions
ls -la [file]

# Check port usage
lsof -i :[port]
netstat -an | grep [port]

# Check environment variables
env | grep [VAR_NAME]
printenv [VAR_NAME]

# Check disk space
df -h

# Check memory
free -m  # Linux
vm_stat  # macOS

Common Debugging Patterns

Pattern 1: Binary Search

When the error location is unclear:

  1. Comment out half the code
  2. If error persists, it's in the remaining half
  3. Repeat until you find the exact line

Pattern 2: Minimal Reproduction

Create the smallest code that reproduces the error:

  1. Start with empty file
  2. Add code piece by piece
  3. Stop when error appears
  4. That's your minimal repro case

Pattern 3: Rubber Duck Debugging

Explain the problem out loud (or to Claude):

  1. What should happen?
  2. What actually happens?
  3. What changed recently?
  4. What assumptions am I making?

Pattern 4: Git Bisect

Find which commit introduced the bug:

git bisect start
git bisect bad  # current commit is bad
git bisect good [last-known-good-commit]
# Git will checkout commits for you to test
git bisect good/bad  # mark each as good or bad
git bisect reset  # when done

Reference Files

  • patterns/ - Language-specific error patterns

    • nodejs.md - Node.js common errors
    • python.md - Python common errors
    • react.md - React/Next.js errors
    • database.md - Database errors
    • docker.md - Docker/container errors
    • git.md - Git errors
    • network.md - Network/API errors
  • analysis/ - Analysis methodologies

    • stack-trace.md - Stack trace parsing guide
    • root-cause.md - Root cause analysis techniques
  • replay/ - Replay system

    • solution-template.yaml - Template for recording solutions