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Container Debugging

  • 437 installs
  • 305 repo stars
  • Updated March 4, 2026
  • aj-geddes/useful-ai-prompts

container-debugging is an agent skill that diagnoses failing Docker or Kubernetes containers using structured prompts for logs, exec shells, health probes, and image-layer inspection for developers troubleshooting produc

About

container-debugging from aj-geddes/useful-ai-prompts provides structured agent prompts for diagnosing failing Docker and Kubernetes containers. The workflow guides systematic investigation across container logs, interactive exec shells, health and readiness probe results, and image-layer inspection to isolate crash loops, OOM kills, misconfigured entrypoints, and networking faults. Developers reach for container-debugging when pods or compose services exit unexpectedly, probes fail intermittently, or deployments roll back without an obvious application stack trace. The skill fits operations and on-call contexts where kubectl and docker CLI commands must be applied in a consistent order rather than ad-hoc guessing. Expect command-shaped prompts and checklists agents can follow to narrow root cause before code changes ship.

  • Log and exit-code triage
  • docker exec inspection flows
  • Image and env validation
  • Network and volume checks

Container Debugging by the numbers

  • 437 all-time installs (skills.sh)
  • Ranked #97 of 596 Debugging skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill container-debugging

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Listed on Skillselion
Installs437
repo stars305
Last updatedMarch 4, 2026
Repositoryaj-geddes/useful-ai-prompts

How do you debug a crashing Kubernetes container?

Diagnose failing Docker or Kubernetes containers using structured prompts for logs, exec shells, health probes, and image-layer inspection.

Who is it for?

Developers on call for Docker or Kubernetes services who want agent-guided, repeatable container failure diagnosis.

Skip if: Local non-container development, initial Dockerfile authoring, or infrastructure provisioning without a failing workload to inspect.

When should I use this skill?

User reports crashing containers, failing K8s probes, pod restart loops, or needs docker/kubectl debugging guidance.

What you get

Root-cause findings from logs, probe status, exec inspection, and image-layer analysis with recommended remediation steps.

  • Diagnostic findings
  • Recommended remediation commands

Files

SKILL.mdMarkdownGitHub ↗

Container Debugging

Table of Contents

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

Related skills

How it compares

Use container-debugging for runtime failure triage; infrastructure-as-code skills address provisioning, not live pod diagnosis.

FAQ

What does container-debugging investigate?

container-debugging investigates failing Docker or Kubernetes workloads via structured prompts for logs, exec shells, health and readiness probes, and image-layer inspection to isolate crash and config faults.

When should developers invoke container-debugging?

container-debugging fits on-call scenarios with pod restart loops, probe failures, or unexpected container exits where kubectl and docker CLI steps must run in a consistent diagnostic order.

Debuggingmonitoringdeploy

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