docker-pro-diagnostic

Advanced log analysis for Docker containers using signal extraction.

533 stars

Best use case

docker-pro-diagnostic is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Advanced log analysis for Docker containers using signal extraction.

Teams using docker-pro-diagnostic should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/docker-pro-diagnostic/SKILL.md --create-dirs "https://raw.githubusercontent.com/sundial-org/awesome-openclaw-skills/main/skills/docker-pro-diagnostic/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/docker-pro-diagnostic/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How docker-pro-diagnostic Compares

Feature / Agentdocker-pro-diagnosticStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Advanced log analysis for Docker containers using signal extraction.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Docker Pro Diagnostic

When a user asks "Why is my container failing?" or "Analyze the logs for [container]", follow these steps:

1.  **Run Extraction:** Call `python3 {{skillDir}}/log_processor.py <container_name>`.
2.  **Analyze:** Feed the output (which contains errors and context) into your reasoning engine.
3.  **Report:** Summarize the root cause. If it looks like a code error, suggest a fix. If it looks like a resource error (OOM), suggest increasing Docker memory limits.

## Example Command
`python3 log_processor.py api_gateway_prod`

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