Advanced log analysis for Docker containers using signal extraction.
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Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install docker-diagOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install docker-diagβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/docker-diag/π‘Extract and place the folder at the path above, then restart your agent.
Category
π»Developer & DevOpsPlatforms
What Docker Diag can do for your AI workflow
Advanced log analysis directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
Trusted by 3,057+ developers worldwide
One-command installation β no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing Docker Diag
Help me get started with Docker Diag
Explains what Docker Diag does, walks through the setup, and runs a quick demo based on your current project
Use Docker Diag to advanced log analysis for Docker containers using signal extraction
Invokes Docker Diag with the right parameters and returns the result directly in the conversation
What can I do with Docker Diag in my developer & devops workflow?
Lists the top use cases for Docker Diag, with example commands for each scenario
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Docker Diag extends your AI assistant with the ability to advanced log analysis for Docker containers using signal extraction. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly β and it will take care of the task end-to-end, using Docker Diag as its underlying capability.
Docker Diag works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) β an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install Docker Diag once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.
Docker Diag installs like any other MCP skill: drop the folder into `~/.claude/skills/docker-diag/` for global access, or `.claude/skills/docker-diag/` to keep it scoped to one project. After a quick restart of Claude, you can trigger it explicitly with `/docker-diag`, or let the AI decide when it's the right tool for your request.
Docker Diag has been installed 3,057 times, making it one of the more actively used skills in the Developer & DevOps category. The install rate suggests it solves a real, recurring need rather than a niche edge case. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.
Place the skill folder at ~/.claude/skills/docker-diag/ for personal use (all projects), or .claude/skills/docker-diag/ for project-specific use. Restart your AI client, then invoke with /docker-diag or let the AI discover it automatically.
Docker Diag supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Docker Diag is free to install. Check the repository for licensing information.
Advanced log analysis for Docker containers using signal extraction.
Automate my developer & devops tasks using Docker Diag
Identifies repetitive steps in your workflow and sets up Docker Diag to handle them automatically
Docker Diag is categorized under Developer & DevOps. These skills help AI agents perform specialized tasks in this domain.
Generate and edit various types of diagrams (drawio, mermaid, excalidraw). Supports common chart types such as flow charts, sequence diagrams, class diagrams, ER diagrams, mind maps, architecture diagrams, and network topology diagrams. Ability to create new diagrams based on natural language descriptions, as well as read and modify existing drawio/mermaid/excalidraw files. Use an independent MCP server (mcp-diagram-generator) to generate diagram files to reduce token consumption and ensure output consistency. Supports automatic configuration management. The default output path is diagrams/{format}/ in the project directory. Custom paths and automatically created directories are supported.