Can this skill help with performance issues?

Yes, by flagging blocking I/O in asynchronous paths and discouraging global state, it helps maintain the high-performance requirements of document processing engines.

Does it provide guidance on dependency management?

Yes, it mandates the use of lock files like Cargo.lock and pnpm-lock.yaml to ensure reproducible builds and secure dependency tracking.

How does this skill improve Rust code safety?

It actively discourages the use of 'unwrap' and 'panic' in production code, instead promoting the use of exhaustive matching and Result types.

Why does the skill recommend against class-based tests in Python?

It favors function-based tests with pytest fixtures to ensure better modularity, easier mocking, and a more idiomatic Python testing experience.

Which programming languages are supported by this skill?

This skill provides specific guidance for Rust, Python, and TypeScript, focusing on common pitfalls in these ecosystems.

Code Anti-Pattern Guardrails

Name: Code Anti-Pattern Guardrails
Author: kreuzberg-dev

bykreuzberg-dev

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569

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Seguridad y Pruebas

Enforces cross-language best practices and prevents common architectural errors in Python, Rust, and TypeScript.

The Code Anti-Pattern Guardrail skill provides a robust set of universal coding standards designed to improve software reliability and maintainability. It specifically targets high-risk patterns in polyglot environments, such as preventing blocking I/O in asynchronous code, enforcing Result types over panics in Rust, and discouraging global state in favor of dependency injection. This skill is essential for developers working on high-performance document processing tools who need to ensure their code is production-ready, testable, and compliant with modern engineering standards.

Características Principales

01Architectural linting for composition-based design and structured logging

02Guidance on asynchronous I/O to maintain high-performance streaming paths

03Cross-language detection of dangerous coding patterns in Python, Rust, and TypeScript

04Enforcement of Result-based error handling to prevent production crashes

05Testing strategy optimization favoring pytest fixtures and real object injection

06569 GitHub stars

Casos de Uso

01Refactoring legacy Python test suites from class-based to fixture-based patterns

02Transitioning from inheritance-heavy architectures to modular composition-based systems

03Automating code reviews to flag 'unwrap' calls or 'any' types before merging

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add kreuzberg-dev/html-to-markdown anti-patterns

For use in Claude.ai and ChatGPT

Download Skill