abase-ubs

Detect AI-introduced bugs and security vulnerabilities in code before commit.

Updated Feb 16, 2026

Search Tags:#code quality #static analysis #security scanning #bug detection #ai coding #pre-commit hook

Ready to run

npx skills add https://github.com/mikegogulski/abase-django-blog-integration-test --skill abase-ubs

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: abase-ubs
Source: https://github.com/mikegogulski/abase-django-blog-integration-test/tree/main/.agents/skills/abase-ubs
Command: npx skills add https://github.com/mikegogulski/abase-django-blog-integration-test --skill abase-ubs

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the common issue of AI-generated code introducing subtle bugs and security vulnerabilities that can slip through traditional checks, ensuring higher quality and more reliable AI-assisted development.

Core Features & Use Cases

Pre-commit Static Analysis: Scans code for common AI-introduced errors like null safety issues, async/await problems, security holes, and memory leaks across multiple languages.
Fast & Efficient: Provides quick scans (< 1 second for specific files) and comprehensive project scans, with options for CI/CD integration.
Use Case: Before committing code written with AI assistance, run UBS to automatically catch potential bugs, preventing them from reaching production and saving debugging time.

Quick Start

Run the abase-ubs skill to scan staged files for critical issues before committing.

Frequently Asked Questions about abase-ubs

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

FAQPage Schema

How do I catch AI-introduced bugs before committing code?▼

To catch AI-introduced bugs before committing code, run a pre-commit static analysis scan on staged files. This process detects null safety issues, async/await problems, and security vulnerabilities across multiple programming languages.

What is static analysis for AI-generated code quality gates?▼

Static analysis for AI-generated code quality gates is an automated pre-commit process that scans source files for security vulnerabilities and common AI-introduced bugs. It acts within CI/CD pipelines and Git hooks to prevent flawed code from reaching production.

Does pre-commit static analysis work with my CI/CD pipelines and Git hooks?▼

Pre-commit static analysis integrates directly with CI/CD pipelines and Git hooks. This integration allows automated quality gates to scan staged files quickly, preventing AI-introduced security vulnerabilities and memory leaks from being committed.

How fast is static analysis scanning for specific files in a project?▼

Static analysis scanning for specific files in a project is fast, completing in under one second. Comprehensive project scans are also available to detect broader quality issues, security holes, and memory leaks across multiple languages.

What types of security vulnerabilities and bugs can pre-commit static analysis detect?▼

Pre-commit static analysis can detect security vulnerabilities and bugs across 18 detection categories. These include null safety, async/await problems, memory leaks, and common AI-introduced quality issues across multiple programming languages.

Do I need additional dependencies to run automated code quality gates in CI/CD?▼

No additional dependencies are required to run automated code quality gates in CI/CD. The static analysis operates independently with scripts and references to detect AI-introduced bugs, null safety issues, and security vulnerabilities.