automated-debugging

Name: automated-debugging
Availability: InStock
Author: Jada

Detect, diagnose, and auto-fix errors in logs and source code.

Updated Aug 23, 2026

Search Tags:#automation #debugging #logs #auto-fix #diagnosis

Ready to run

npx skills add https://github.com/lofibrainwav/AFO_Kingdom --skill automated-debugging

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: automated-debugging
Source: https://github.com/lofibrainwav/AFO_Kingdom/tree/main/skills/automated-debugging
Command: npx skills add https://github.com/lofibrainwav/AFO_Kingdom --skill automated-debugging

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill orchestrates error detection, diagnosis, and automatic fixes across tools to streamline debugging workflows.

Core Features & Use Cases

error_detection: Find errors in logs and code.
auto_diagnosis: Identify root causes quickly.
auto_fix: Apply fixes automatically with quality gates.

Quick Start

result = await debugger.run_pipeline(logs=logs_data)

Frequently Asked Questions about automated-debugging

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate error detection and fixing in my logs and source code?▼

Automated debugging detects errors across logs and code, diagnoses root causes, and applies fixes automatically. This Skill orchestrates error detection, diagnosis, and patches through integration with tools like Ruff, Black, and MyPy, operating across development pipelines, CI/CD, and production monitoring.

Can I automatically fix errors detected in my CI/CD pipeline?▼

Yes. This Skill applies automatic fixes with quality gates throughout CI/CD workflows. It detects errors, classifies them, proposes patches, and auto-applies corrections while evaluating results against trinity score thresholds.

What tools does this integrate with for automated debugging?▼

The Skill integrates with Ruff for linting, Black for code formatting, MyPy for type checking, and AI analysis. These tools work together to detect errors, propose fixes, and validate patches end-to-end.

Does this work for production monitoring and error diagnosis?▼

Yes. Automated debugging operates across development, CI/CD, and production environments. It detects errors in logs and code, identifies root causes quickly, and proposes fixes applicable to production monitoring workflows.

How do I run the automated debugging pipeline on my logs?▼

Call the pipeline with your logs data: `result = await debugger.run_pipeline(logs=logs_data)`. The pipeline automates error detection, diagnosis, and fix application end-to-end with built-in quality gates.

What happens after errors are fixed—how are results validated?▼

Fixes are validated through trinity score evaluation, which assesses patch quality before and after application. Results include error classification, proposed solutions, and validation metrics.