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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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:
- Paste the full error (including stack trace if available)
- Provide context (what were you trying to do?)
- 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:
- Immediate fix - Get it working now
- Proper fix - The right way to solve it
- 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:
- Generate error signature from the error message
- Search
.claude/error-solutions/for matching patterns - If found, apply the recorded solution
- 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:
- Comment out half the code
- If error persists, it's in the remaining half
- Repeat until you find the exact line
Pattern 2: Minimal Reproduction
Create the smallest code that reproduces the error:
- Start with empty file
- Add code piece by piece
- Stop when error appears
- That's your minimal repro case
Pattern 3: Rubber Duck Debugging
Explain the problem out loud (or to Claude):
- What should happen?
- What actually happens?
- What changed recently?
- 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 errorspython.md- Python common errorsreact.md- React/Next.js errorsdatabase.md- Database errorsdocker.md- Docker/container errorsgit.md- Git errorsnetwork.md- Network/API errors
-
analysis/ - Analysis methodologies
stack-trace.md- Stack trace parsing guideroot-cause.md- Root cause analysis techniques
-
replay/ - Replay system
solution-template.yaml- Template for recording solutions
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