An intelligent diagnostic tool that performs advanced log analysis and signal extraction to identify Docker container failures.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install docker-diag
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install docker-diag using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Docker Pro Diagnostic?
Docker Pro Diagnostic is a specialized utility designed to bridge the gap between complex container logs and actionable intelligence. By utilizing advanced signal extraction via a dedicated log processor, this tool enables developers to instantly understand why a container is failing without manually sifting through thousands of log lines. It provides a structured approach to debugging that leverages AI reasoning to identify patterns in container behavior.
This skill is a vital component of the Openclaw Skills library, specifically tailored for environments where uptime and rapid recovery are critical. It transforms raw log output into clear insights, distinguishing between code-level exceptions and infrastructure-level resource constraints like memory exhaustion.
Docker Pro Diagnostic Use Cases
- Troubleshooting container crashes or unexpected exits in production and development.
- Automating the identification of Out of Memory (OOM) kills within Docker environments.
- Extracting specific error signals from high-volume log streams for faster debugging.
- Generating automated remediation suggestions for common Docker configuration errors.
How Docker Pro Diagnostic Works
- The AI agent initiates the diagnostic process by targeting a specific container name.
- The system executes the log_processor script which interfaces with the Docker daemon to pull recent logs.
- Signal extraction algorithms isolate critical error messages, stack traces, and system warnings from the raw data.
- The filtered data is processed by the reasoning engine to determine the most likely root cause.
- A comprehensive report is generated, offering a fix for code errors or infrastructure adjustments for resource issues.
Docker Pro Diagnostic Setup
To utilize this skill, ensure that both python3 and docker are installed and accessible in your environment path. The skill requires the log_processor.py script to be present in the skill directory.
# Run the diagnostic tool against a specific container
python3 log_processor.py <container_name>
Docker Pro Diagnostic Data Schema & Taxonomy
The skill processes data by extracting log signals and organizing them for AI interpretation. The output format follows this structure:
| Attribute | Description |
|---|---|
| Container Name | The target container identifier for the analysis session. |
| Extracted Signals | A collection of high-priority error logs and context markers. |
| Root Cause Summary | The identified primary reason for container failure (e.g., Runtime Error, OOM). |
| Suggested Resolution | Actionable steps or code changes recommended to resolve the issue. |
Docker Pro Diagnostic Advanced Features
- Signal extraction logic that filters out operational noise to focus on critical failure points.
- Multi-category diagnostic support for identifying both application bugs and environment misconfigurations.
- Seamless integration with the Openclaw Skills ecosystem for automated agent-led recovery workflows.
- Lightweight execution using standard Python and Docker CLI binaries.
SKILL.md
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