Generic AI code suggestions often miss project-specific conventions, causing developers to spend time refactoring output. The major AI coding tools support project-level config files that fix this: Cursor uses `.cursorrules` or `.mdc` files, GitHub Copilot reads `.github/copilot-instructions.md`, and Claude Code loads `CLAUDE.md`. The guide covers exact syntax for each format, explains how negative rules ('never use X') outperform positive ones, and provides a ready-to-use configuration library for React 19, Vue 3, Svelte 5, Next.js 14, Django REST Framework, Fastify/Prisma, Laravel 11, Rails 7, Spring Boot 3/Kotlin, Flutter, and React Native/Expo. It also covers how to measure config effectiveness via acceptance rates and CI pass rates, and how to iterate by converting repeated manual corrections into new rules.

19m read timeFrom sitepoint.com
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How to Customize AI Code Completion for Your Tech StackTable of ContentsWhy Generic AI Code Suggestions Fail Your StackUnderstanding Context Files Across ToolsWriting Effective .cursorrules FilesConfiguring GitHub Copilot Custom InstructionsSetting Up CLAUDE.md for Claude CodeStack-Specific Configuration LibraryMeasuring and Iterating on Config EffectivenessKey Takeaways
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