An AI-driven debugging companion that analyzes error logs, explains stack traces, and provides instant fix suggestions across eight programming languages.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ai-debug-assistant
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 ai-debug-assistant 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 Debug Assistant?
Debug Assistant is a sophisticated diagnostic tool designed for developers who want to streamline their troubleshooting workflow within the Openclaw Skills ecosystem. By leveraging evolink.ai and advanced models like Claude, it transforms cryptic terminal errors into clear, actionable intelligence. Whether you are dealing with a Node.js crash or a complex Rust backtrace, this skill provides the context needed to resolve issues quickly.
This utility acts as a bridge between raw log data and human-readable solutions. It goes beyond simple error searching by providing deep root-cause analysis and step-by-step remediation instructions, making it a cornerstone for anyone building with Openclaw Skills.
Debug Assistant Use Cases
- Automatically analyzing complex server crash logs to identify underlying database or SSL failures.
- Explaining ambiguous JavaScript runtime errors to provide immediate context and potential quick fixes.
- Parsing multi-language stack traces to find the exact origin and call chain of an exception.
- Generating corrected code snippets for buggy Python or Go handlers based on specific error messages.
- Accessing rapid debugging cheatsheets for languages like Rust, Java, and Git during active development.
How Debug Assistant Works
- The user initiates a command via the terminal, passing an error message, log file, or stack trace as an argument.
- For AI-based analysis, the skill securely sends the content to the evolink.ai API using the configured environment variables.
- The backend processes the input using specialized models to identify patterns, error chains, and known bugs.
- The skill receives a structured response containing a summary, root cause analysis, and suggested fix steps.
- The output is rendered directly in the terminal for the user to review and implement.
- For local info commands, the skill retrieves pre-defined language cheatsheets without requiring network access.
Debug Assistant Setup
To integrate this tool into your Openclaw Skills setup, follow these configuration steps:
- Obtain an API key from evolink.ai and export it to your environment:
export EVOLINK_API_KEY="your-key-here"
- Ensure your system has the necessary dependencies installed:
# Verify python3 and curl are available
python3 --version
curl --version
- Run your first analysis to confirm setup:
bash scripts/debug.sh explain "ECONNREFUSED 127.0.0.1:5432"
Debug Assistant Data Schema & Taxonomy
The Debug Assistant skill organizes its operational data into clear categories to ensure efficient processing within the Openclaw Skills framework:
| Component | Type | Description |
|---|---|---|
| AI Analysis | Remote | Dynamic payloads sent to api.evolink.ai for processing. |
| Cheatsheets | Local | Static reference data for 8 languages including Python, Go, and Rust. |
| Config | Env Var | Uses EVOLINK_API_KEY and EVOLINK_MODEL for behavior customization. |
| Temp Files | Local | Temporary files used for API payload construction, deleted after use. |
Supported technical domains include high-level languages (Java, JavaScript), systems languages (Rust, Go), and infrastructure tools (Network, Git, CSS).
Debug Assistant Advanced Features
- Multi-language support providing specialized debugging commands for environments ranging from Node.js to JVM.
- Automated Git bisect integration for pinpointing breaking changes in large codebases.
- Deep stack trace decomposition that extracts the root cause from long, nested error chains.
- Customizable AI model selection allowing users to toggle between different versions of Claude for analysis.
- Comprehensive network diagnostic support utilizing tools like curl, dig, and netstat for connectivity troubleshooting.
SKILL.md
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