I Analyzed 500 AI Coding Mistakes and Built an ESLint Plugin to Catch Them

This article discusses the development of eslint-plugin-llm-core, a plugin designed to catch and prevent coding patterns that large language models (LLMs) commonly get wrong, even if these patterns are technically valid TypeScript. The key points covered in the article include:

Introduction

The introduction highlights how modern AI tools like Copilot can generate syntactically correct but logically flawed code, leading to issues such as silent error swallowing and incorrect async flow.

Problem Description

• Silent Error Swallowing: LLMs often use catch blocks without handling errors properly.
• Incorrect Async Flow: Using async functions in array methods incorrectly can lead to unexpected behavior.
• Unmaintainable Constants: Hardcoding numbers instead of defining constants makes the code less maintainable.

Solution: eslint-plugin-llm-core

This plugin aims to address these issues by providing rules that catch problematic patterns and offer educational error messages to help both developers and AI tools improve their coding practices.

Rule Examples

1. no-async-array-callbacks: Prevents using async functions in array methods without proper handling.
2. no-empty-catch: Ensures errors are not silently swallowed by requiring proper error handling

Read the full article at DEV Community

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