Container Debugging

SkillCloud & infra

Debug Docker containers and containerized applications. Diagnose deployment issues, container lifecycle problems, and resource constraints.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Container Debugging skill

What this skill tells your AI

The instructions your AI receives, as published by aj-geddes/useful-ai-prompts in skills/container-debugging/SKILL.md and read by ahel’s review.

Table of Contents

  • Overview
  • When to Use
  • Quick Start
  • Reference Guides
  • Best Practices

Overview

Container debugging focuses on issues within Docker/Kubernetes environments including resource constraints, networking, and application runtime problems.

When to Use

  • Container won't start
  • Application crashes in container
  • Resource limits exceeded
  • Network connectivity issues
  • Performance problems in containers

Quick Start

Minimal working example:

# Check container status
docker ps -a
docker inspect <container-id>
docker stats <container-id>

# View container logs
docker logs <container-id>
docker logs --follow <container-id>  # Real-time
docker logs --tail 100 <container-id>  # Last 100 lines

# Connect to running container
docker exec -it <container-id> /bin/bash
docker exec -it <container-id> sh

# Inspect container details
docker inspect <container-id> | grep -A 5 "State"
docker inspect <container-id> | grep -E "Memory|Cpu"

# Check container processes
docker top <container-id>

# View resource usage
docker stats <container-id>
# Shows: CPU%, Memory usage, Network I/O

// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

GuideContents
Docker Debugging BasicsDocker Debugging Basics
Common Container IssuesCommon Container Issues
Container OptimizationContainer Optimization
Debugging ChecklistDebugging Checklist

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

Signals

GitHub stars
339
Forks
55
Last commit
Mar 2026
Advanced
Catalog kind
skill
Gateway key
container-debugging
Source
github.com/aj-geddes/useful-ai-prompts