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Container Debugging

Checked
aj-geddes·vlatest·cloud·MIT

Diagnose container runtime issues like resource limits, misconfigurations, and failed deployments with detailed error analysis.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add aj-geddes/useful-ai-prompts --skill container-debugging -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

aj-geddes

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned aj-geddes/useful-ai-prompts at 3f5182cfd7.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
3f5182cfd7
Manifest
skills/container-debugging/SKILL.md
Scanned
7 files, 321 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to inspect, diagnose, and resolve issues within containerized environments like Docker or Kubernetes. It automates the process of gathering logs, analyzing resource usage, and suggesting fixes for runtime failures.

When to use it

  • Your application inside a container crashes unexpectedly during deployment or production.
  • You need to identify why a specific service is consuming excessive CPU or memory.
  • Logs are scattered across multiple containers, making manual investigation inefficient.
  • You want an automated first step before escalating complex infrastructure issues to human engineers.

Key capabilities

  • Log Aggregation: Collects and parses logs from individual containers or entire orchestration clusters.
  • Resource Analysis: Identifies bottlenecks related to CPU, memory, or network I/O limits.
  • Error Diagnosis: Correlates error messages with container states to pinpoint root causes.
  • Remediation Suggestions: Provides actionable commands or configuration changes to fix identified issues.

Example prompts

  • "Analyze the logs of my production web server container and explain why it returned 503 errors last hour."
  • "Check if my database container is hitting memory limits and suggest a resource adjustment."
  • "Diagnose why my microservice cannot connect to the Redis cache in this Kubernetes pod."

Tips & gotchas

Ensure the AI agent has read-only access to your container logs and metrics before running diagnostics. This skill works best when combined with other infrastructure skills that can apply patches or restart services based on the diagnosis.