How does this skill prevent 'AI slop' in C++ code?

It intercepts generic AI patterns—like manual pointers or C-style arrays—and replaces them with memory-safe RAII containers and Rcpp-specific optimizations.

Will this help with memory leaks in my R package?

Absolutely. By enforcing the use of Rcpp containers and smart pointers instead of manual new/delete operations, it significantly reduces the risk of memory leaks.

Does this skill work for general-purpose C++ development?

While the coding standards are beneficial for all C++ projects, this skill is specifically tailored for developers writing R extensions using the Rcpp framework.

Can I use this for linear algebra optimization?

Yes, the skill includes specific workflows for integrating RcppArmadillo to handle high-performance matrix calculations efficiently.

C++ Anti-Slop for Rcpp

Name: C++ Anti-Slop for Rcpp
Author: emraher

byemraher

Data Science & ML

Optimizes Rcpp and C++ extensions by enforcing memory safety, const-correctness, and high-performance vectorized patterns.

About

The C++ Anti-Slop skill is specifically designed to refine and secure AI-generated C++ code intended for R extensions. It prevents common pitfalls like manual memory management and inefficient C-style loops by mandating the use of RAII, Rcpp containers, and Rcpp sugar for vectorized performance. This skill ensures that code is not only high-performing but also adheres to modern C++ standards and R-friendly error handling, making it essential for developers building robust, low-level algorithms for the R ecosystem.

Key Features

Optimizes performance using Rcpp sugar for vectorized operations
Standardizes R-friendly error handling using Rcpp::stop()
0 GitHub stars
Guides the implementation of RcppArmadillo for linear algebra tasks
Promotes const-correctness to minimize unnecessary object copies
Enforces RAII and Rcpp container usage to eliminate manual memory leaks

Use Cases

Refactoring generic AI-generated C++ into production-ready Rcpp code
Optimizing performance-critical R functions with memory-safe C++ extensions
Modernizing legacy Rcpp codebases to follow modern C++11/14+ standards

About

Key Features

Optimizes performance using Rcpp sugar for vectorized operations
Standardizes R-friendly error handling using Rcpp::stop()
0 GitHub stars
Guides the implementation of RcppArmadillo for linear algebra tasks
Promotes const-correctness to minimize unnecessary object copies
Enforces RAII and Rcpp container usage to eliminate manual memory leaks

Use Cases

Refactoring generic AI-generated C++ into production-ready Rcpp code
Optimizing performance-critical R functions with memory-safe C++ extensions
Modernizing legacy Rcpp codebases to follow modern C++11/14+ standards