A collection of rules and guidance for the Cursor environment, designed to help streamline development workflows and enforce consistent patterns across your codebase.
This repository hosts a set of rule files (typically in .mdc format) under .cursor/rules, intended for use with the Cursor IDE (or similar AI-assisted development environments). These rules define project-wide or module-specific instructions such as coding standards, architecture guidelines, workflow automations, and more.
By embedding rules into your project:
- Your AI assistant (via Cursor) has contextual, version-controlled guidance specific to your project.
- You enforce consistency across team workflows, coding style, architecture decisions.
- You reduce repetitive decision-making by codifying best practices and patterns.
- You make onboarding smoother: new contributors inherit the same rule set from day one.
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Clone this repository (or add it as a submodule) into your projectโs
.cursor/rulesdirectory:git clone https://github.com/dobryakov/cursor-rules.git /anywhere/you/want
then make a symlink.
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Make sure your project structure and rule-paths align with how your Cursor environment expects rules to be found.
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Inspect or adapt the rule files to fit your projectโs specifics (naming conventions, file patterns, workflows).
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Commit the rules into version control so the whole team uses the same guidance.
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In Cursor, confirm the rules are being recognized and applied (often via โRulesโ or context settings in the UI).
This repository hosts a set of rule files (typically in .mdc format) under .cursor/rules, intended for use with the Cursor IDE (or similar AI-assisted development environments). These rules define project-wide or module-specific instructions such as coding standards, architecture guidelines, workflow automations, and more.
By embedding rules into your project:
- Your AI assistant (via Cursor) has contextual, version-controlled guidance specific to your project.
- You enforce consistency across team workflows, coding style, architecture decisions.
- You reduce repetitive decision-making by codifying best practices and patterns.
- You make onboarding smoother: new contributors inherit the same rule set from day one.
- Add or remove rule files as needed โ keep them focused, actionable, and scoped (good rules tend to be < 500 lines).
- For new domains or frameworks, create a new subdirectory (e.g.,
framework/python/,domain/analytics/). - Document clearly in each rule: what it enforces, why it exists, and how to use/adhere to it (include examples and anti-patterns).
- Use metadata (globs, alwaysApply flags) to control when a rule is applied or triggered.
Contributions are welcome! Hereโs how you can help:
- Fork this repository and create a branch for your feature or rule improvement.
- Add a new
.mdcfile (or update an existing one) with clear description, scope, and examples. - Ensure your changes align with the existing naming and structuring conventions.
- Submit a pull request with a meaningful commit message describing the ruleโs purpose or modification.