How does the Anti-Slop dispatcher work?

It automatically analyzes the file extension you are working on (e.g., .py, .R, .md) and invokes the corresponding domain-specific quality rules without requiring manual selection.

Can I use specific language rules directly?

Yes, you can directly call sub-skills like python/anti-slop or r/anti-slop if you want to focus exclusively on a specific domain's deep-dive requirements.

Is this skill suitable for automated pipelines?

Yes, it includes a toolkit with detection scripts (e.g., detect_slop.py) designed for CI/CD integration to gate-keep code and documentation quality.

Does it support data science workflows?

Absolutely. It includes specialized rules for Quarto, R, Julia, and design visualizations to ensure reproducible and professional research output.

What is 'slop' in the context of AI development?

'Slop' refers to generic, verbose, or repetitive patterns typical of AI models, such as using 'delve into', generic variable names like 'df' or 'result', and missing type hints.

Anti-Slop Quality Guard

Name: Anti-Slop Quality Guard
Author: emraher

byemraher

0•

Developer Tools

Enforces high-quality standards and eliminates generic AI-generated patterns across codebases, documentation, and design files.

Anti-Slop acts as a central meta-skill for quality control, automatically detecting file types and applying domain-specific best practices to ensure your output is production-ready. It bridges the gap between raw AI generation and professional human-grade results by enforcing strict naming conventions, type safety, and direct language while purging common AI buzzwords and 'slop' across R, Python, C++, Julia, and technical documentation. Whether you are refactoring a complex repository or polishing a research paper, this skill ensures your work maintains a professional, intentional, and non-generic character.

Key Features

01Automatic domain detection and routing based on file extension

02Multi-language code quality enforcement for Python, R, C++, and Julia

03Prevention of generic AI 'slop' and repetitive language patterns

04Technical writing optimization for clarity, directness, and precision

050 GitHub stars

06Integrated toolkit for automated quality checks and CI/CD integration

Use Cases

01Auditing multi-language projects for consistent quality and reproducibility standards

02Refactoring AI-generated code to follow production-grade type-safety and naming conventions

03Cleaning technical documentation to remove AI buzzwords and meta-commentary

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add emraher/eerskills anti-slop

For use in Claude.ai and ChatGPT

Download Skill