A comprehensive debugging companion that automates log analysis, suggests strategic breakpoints, and maps execution flows to identify root causes.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install openclaw-debugger
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 openclaw-debugger 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 Debugging Assistant?
The Debugging Assistant is a robust tool designed to accelerate the troubleshooting process within the Openclaw Skills framework. It serves as a bridge between raw error logs and actionable fixes by performing deep analysis on stack traces, identifying common error patterns, and providing structural insights into application behavior. By integrating this skill, developers can move from manual inspection to an automated diagnostic workflow that covers everything from simple syntax errors to complex database connection issues.
This skill is particularly valuable for maintaining code quality and system reliability. It doesn't just point to an error; it explains the underlying reason, suggests the best places to pause execution for inspection, and visualizes the call hierarchy to prevent future regressions. Whether you are dealing with a critical production crash or an elusive performance bottleneck, this component of Openclaw Skills provides the technical clarity needed to resolve issues efficiently.
Debugging Assistant Use Cases
- Analyzing complex Python tracebacks to pinpoint the exact line and function causing a database connection failure.
- Generating a list of high-priority breakpoint locations before performing major refactoring on legacy codebases.
- Visualizing the call graph of a specific API request handler to identify missing error handling in downstream functions.
- Screening large log files for specific error patterns like KeyError or TimeoutError using automated Openclaw Skills scripts.
- Troubleshooting performance bottlenecks by tracing execution paths through slow endpoints.
How Debugging Assistant Works
- The user provides a raw error log or a path to a log file to the analyze-error command, which identifies the exception type and severity.
- The assistant scans the associated source code to determine the root cause, such as a closed database connection or an unhandled null value.
- For structural debugging, the tool analyzes the file's logic to suggest breakpoints at entry points, conditional branches, and external API calls.
- The tracer generates a call graph for the specified function, showing the hierarchy of internal and external calls to reveal potential failure points.
- All findings are summarized with actionable suggestions, including specific code fixes and health check implementations.
Debugging Assistant Setup
To start using this tool within your Openclaw Skills environment, ensure you have the necessary scripts located in your project directory.
# Analyze a specific error message directly from the CLI
python3 scripts/main.py analyze-error "Traceback (most recent call last):..."
# Analyze an error log file for deeper diagnostics
python3 scripts/main.py analyze-error --file path/to/error.log
# Get recommended breakpoint locations for a specific file
python3 scripts/main.py suggest-breakpoints --file src/logic.py
# Trace the execution flow of a specific function
python3 scripts/main.py trace --file src/app.py --function process_data
Debugging Assistant Data Schema & Taxonomy
The Debugging skill organizes its logic and configuration through a structured set of files and JSON schemas to ensure compatibility with other Openclaw Skills.
| File | Purpose | Data Type |
|---|---|---|
.debugging.json |
Global configuration for breakpoint logic and error filtering. | JSON |
error_analyzer.py |
Core engine for parsing tracebacks and identifying root causes. | Python |
tracer.py |
Handles call graph generation and execution path mapping. | Python |
SKILL.md |
Documentation and technical specifications for the skill. | Markdown |
Configuration Schema (.debugging.json):
breakpoints: Controls when suggestions are triggered (e.g., before external calls).error_patterns: Allows users to ignore specific warnings or highlight critical security errors.
Debugging Assistant Advanced Features
- Customizable error pattern recognition that allows users to define high-priority alerts for specific security or data loss exceptions.
- Automated call graph visualization to simplify the understanding of deeply nested function calls and dependencies.
- Logic-aware breakpoint suggestions that prioritize entry points and external service interactions to maximize debugging efficiency.
- Seamless integration with existing Openclaw Skills workflows to provide a unified troubleshooting interface for multi-agent systems.
SKILL.md
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