/log-analysis
Analyze application and system logs to identify errors, patterns, and root causes. Use log aggregation tools and structured logging for effective debugging.
$ npx -y skills add aj-geddes/useful-ai-prompts --skill log-analysis --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/log-analysis
Context preview
The summary Claude sees to decide when to auto-load this skill.
Analyze application and system logs to identify errors, patterns, and root causes. Use log aggregation tools and structured logging for effective debugging.
SKILL.md
log-analysis.SKILL.mdname: log-analysis
description: >
Analyze application and system logs to identify errors, patterns, and root
causes. Use log aggregation tools and structured logging for effective
debugging.
Log Analysis
Table of Contents
- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#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](references/structured-logging.md) | Structured Logging | | [Log Levels & Patterns](references/log-levels-patterns.md) | Log Levels & Patterns | | [Log Analysis Tools](references/log-analysis-tools.md) | Log Analysis Tools | | [Common Log Analysis Queries](references/common-log-analysis-queries.md) | 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
Read more
name: log-analysis description: > Analyze application and system logs to identify errors, patterns, and root causes. Use log aggregation tools and structured logging for effective debugging.
Log Analysis
Table of Contents
- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#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](references/structured-logging.md) | Structured Logging | | [Log Levels & Patterns](references/log-levels-patterns.md) | Log Levels & Patterns | | [Log Analysis Tools](references/log-analysis-tools.md) | Log Analysis Tools | | [Common Log Analysis Queries](references/common-log-analysis-queries.md) | 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
488 production-ready AI prompts, all following a standardized template with validated quality gates. Transform ChatGPT, Claude, and other AI assistants into expert consultants.
Repo: aj-geddes/useful-ai-prompts
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