Agent skill
log-analysis
Analyze application and system logs to identify errors, patterns, and root causes. Use log aggregation tools and structured logging for effective debugging.
Install this agent skill to your Project
npx add-skill https://github.com/aj-geddes/useful-ai-prompts/tree/main/skills/log-analysis
SKILL.md
Log Analysis
Table of Contents
- Overview
- When to Use
- Quick Start
- Reference Guides
- Best Practices
Overview
Logs are critical for debugging and monitoring. Effective log analysis quickly identifies issues and enables root cause analysis.
When to Use
- Troubleshooting errors
- Performance investigation
- Security incident analysis
- Auditing user actions
- Monitoring application health
Quick Start
Minimal working example:
// Good: Structured logs (machine-readable)
logger.info({
level: 'INFO',
timestamp: '2024-01-15T10:30:00Z',
service: 'auth-service',
user_id: '12345',
action: 'user_login',
status: 'success',
duration_ms: 150,
ip_address: '192.168.1.1'
});
// Bad: Unstructured logs (hard to parse)
console.log('User 12345 logged in successfully in 150ms from 192.168.1.1');
// JSON Format (Elasticsearch friendly)
{
"@timestamp": "2024-01-15T10:30:00Z",
"level": "ERROR",
"service": "api-gateway",
"trace_id": "abc123",
"message": "Database connection failed",
"error": {
"type": "ConnectionError",
"code": "ECONNREFUSED"
// ... (see reference guides for full implementation)
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| Structured Logging | Structured Logging |
| Log Levels & Patterns | Log Levels & Patterns |
| Log Analysis Tools | Log Analysis Tools |
| Common Log Analysis Queries | Common Log Analysis Queries |
Best Practices
✅ DO
- Follow established patterns and conventions
- Write clean, maintainable code
- Add appropriate documentation
- Test thoroughly before deploying
❌ DON'T
- Skip testing or validation
- Ignore error handling
- Hard-code configuration values
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