Anti-Slop: Polyglot Code Quality Audit

Detect and fix patterns that make code look machine-generated, over-abstracted, unnecessarily verbose, or fluently wrong. The goal is code that reads like a competent human wrote it - minimal, intentional, grounded, and clear.

This skill covers: TypeScript/JavaScript, Python, Bash/Shell, Rust, Docker/Containers, and Infrastructure as Code (Terraform, Ansible, Helm, Kubernetes manifests). The universal patterns apply everywhere; language-specific sections add targeted checks.

When to use

• Reviewing code that feels machine-generated, bloated, or oddly generic
• Simplifying code after an AI-heavy implementation pass
• Auditing comment noise, naming quality, over-abstraction, and dependency creep
• Looking for "ugly but technically works" code that still hurts readability or maintainability
• Looking for AI-native tells: hallucinated APIs, schema drift, fallback laundering, and tests that only ratify the implementation

The Three Axes of Slop

Every finding falls into one of three categories:

1. Noise - bulk without value (redundant comments, boilerplate, unnecessary types/annotations)