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claude-codeopenclaw

Awesome-openclaw-skills docker-pro-diagnostic

Advanced log analysis for Docker containers using signal extraction.

install
source · Clone the upstream repo
git clone https://github.com/sundial-org/awesome-openclaw-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/docker-pro-diagnostic" ~/.claude/skills/sundial-org-awesome-openclaw-skills-docker-pro-diagnostic && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/docker-pro-diagnostic" ~/.openclaw/skills/sundial-org-awesome-openclaw-skills-docker-pro-diagnostic && rm -rf "$T"
manifest: skills/docker-pro-diagnostic/SKILL.md
source content

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