Container debugging focuses on issues within Docker/Kubernetes environments including resource constraints, networking, and application runtime problems.
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add aj-geddes/useful-ai-prompts --skill container-debuggingCompatible with
Supported agents
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncontainer-debuggingExecute the skills CLI command in your project's root directory to begin installation:
epx add aj-geddes/useful-ai-prompts --skill container-debuggingFetches container-debugging from aj-geddes/useful-ai-prompts and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/container-debugging
Restart Cursor to activate container-debugging. Access via /container-debuggingin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
root-cause-analysis
aj-geddes/useful-ai-prompts · Productivity · same repo
ansible-automation
aj-geddes/useful-ai-prompts · Productivity · same repo
accessibility-testing
aj-geddes/useful-ai-prompts · Testing · same repo
accessibility-compliance
aj-geddes/useful-ai-prompts · Productivity · same repo
llm-council
am-will/codex-skills · AI/ML · same category
aiogram-framework
narumiruna/telegram-bot · AI/ML · same category
container-debugging fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
container-debugging reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend container-debugging for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
container-debugging has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in container-debugging — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added container-debugging from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend container-debugging for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
container-debugging reduced setup friction for our internal harness; good balance of opinion and flexibility.
container-debugging is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: container-debugging is focused, and the summary matches what you get after install.
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