How do I integrate this with GitHub Actions?

The toolkit includes workflow templates for creating CI checks that fail a build if a file's slop score exceeds a defined threshold, ensuring only high-quality code is merged.

What is 'AI slop' in this context?

AI slop refers to generic, wordy, or repetitive patterns and clichés often found in AI-generated text and code, such as 'delve into' or overly generic variable names in scripts.

Does it support automated fixing?

Yes, the clean_slop.py script provides both preview and automated save modes to replace detected slop with direct, concise alternatives.

Is it safe to run on production code?

It is recommended to run detection first and review changes in preview mode. While the tool creates backups, aggressive cleanup may occasionally alter stylistic nuance.

Anti-Slop Toolkit

Name: Anti-Slop Toolkit
Author: emraher

byemraher

Developer Tools

Detects and cleans generic AI-generated content patterns from code and documentation to ensure high-quality, authentic output.

About

The Anti-Slop Toolkit is a specialized suite of detection and cleanup tools designed to identify and eliminate common AI-generated 'slop' patterns in codebases and documentation. By scanning Python, R, and Markdown files, it provides quantitative scoring for authenticity, identifies wordy or cliché phrases, and offers automated cleanup workflows. It is particularly useful for teams looking to maintain human-centric quality standards, integrate quality gates into CI/CD pipelines, or audit large projects for repetitive AI artifacts that reduce professional polish.

Key Features

0 GitHub stars
Pre-commit hooks to prevent generic AI patterns from entering the repository
Quantitative authenticity scoring (0-100) for files and directories
CI/CD integration scripts for automated quality enforcement
Automated slop detection for Python scripts and R code
Context-aware cleanup of high-risk phrases and redundant qualifiers

Use Cases

Batch cleaning documentation to remove repetitive AI-isms and buzzwords
Integrating automated quality checks into GitHub Actions or GitLab CI
Auditing a codebase for AI-generated patterns before a public release

About

Key Features

0 GitHub stars
Pre-commit hooks to prevent generic AI patterns from entering the repository
Quantitative authenticity scoring (0-100) for files and directories
CI/CD integration scripts for automated quality enforcement
Automated slop detection for Python scripts and R code
Context-aware cleanup of high-risk phrases and redundant qualifiers

Use Cases

Batch cleaning documentation to remove repetitive AI-isms and buzzwords
Integrating automated quality checks into GitHub Actions or GitLab CI
Auditing a codebase for AI-generated patterns before a public release