⭐ Featured by Cursor

A curated collection of Cursor slash-command prompts that give your team reusable, version-controlled AI workflows directly inside the Cursor IDE.

🔗 Also check out Cursor Hooks - that runs after every file edit

Cursor Commands are reusable AI prompts saved as Markdown files in .cursor/commands/. When you type / in Cursor's chat input, the IDE lists every command from your project and your global library so you can insert the prompt instantly. They act like AI-driven shortcuts that automate repetitive tasks, reinforce team standards, and keep feedback consistent.

• 🚀 Quick access: Type / to surface every command without leaving your flow
• 🔄 Reusable: Standardize prompts for common tasks across the whole team
• 👥 Shareable: Store commands in git so they ship with your repository
• 🎯 Focused: Each command targets a specific workflow with clear structure
• 📝 Customizable: Edit or extend the Markdown files to match your processes

Commands can live in two places:

• Project commands: Store Markdown files in .cursor/commands inside your repository
• Global commands: Store personal commands in ~/.cursor/commands on your machine

Cursor automatically scans both directories when you type /, combines the results, and inserts the selected command into the chat ready to run.

1. Type / in Cursor's AI chat or agent input
2. Select from the available commands
3. Let the AI execute the prompt with the relevant project context

• Create a .cursor/commands directory in your project root
• Add .md files with descriptive names (for example, code-review.md, run-all-tests-and-fix.md)
• Write clear Markdown instructions describing what the command should accomplish
• Open Cursor, type /, and choose your new command to execute it immediately

Example structure:

.cursor/
└── commands/
    ├── accessibility-audit.md
    ├── add-documentation.md
    ├── add-error-handling.md
    ├── address-github-pr-comments.md
    ├── clarify-task.md
    ├── code-review.md
    ├── create-pr.md
    ├── deslop.md
    ├── docker-logs.md
    ├── database-migration.md
    ├── debug-issue.md
    ├── diagrams.md
    ├── fix-compile-errors.md
    ├── fix-git-issues.md
    ├── generate-api-docs.md
    ├── generate-pr-description.md
    ├── git-commit.md
    ├── git-push.md
    ├── light-review-existing-diffs.md
    ├── lint-fix.md
    ├── lint-suite.md
    ├── onboard-new-developer.md
    ├── optimize-performance.md
    ├── overview.md
    ├── refactor-code.md
    ├── roadmap.md
    ├── run-all-tests-and-fix.md
    ├── security-audit.md
    ├── security-review.md
    ├── setup-new-feature.md
    ├── visualize.md
    └── write-unit-tests.md

• lint-fix.md – Automatically analyze and fix linting issues in the current file
• lint-suite.md – Run project linters, apply fixes, and ensure codebase meets formatting requirements
• refactor-code.md – Improve code quality while maintaining functionality
• optimize-performance.md – Analyze and optimize code performance
• add-error-handling.md – Implement comprehensive error handling across the change set
• deslop.md – Clean up AI-generated code by removing unnecessary complexity and verbosity
• clarify-task.md – Break down ambiguous tasks into clear, actionable steps

• code-review.md – Comprehensive review checklist with structured steps and focus areas
• address-github-pr-comments.md – Process reviewer feedback and craft thoughtful responses
• light-review-existing-diffs.md – Quick pass to highlight risky diffs and cleanup items
• create-pr.md – Prepare a well-structured pull request with validation checklist
• generate-pr-description.md – Draft detailed pull-request descriptions automatically

• run-all-tests-and-fix.md – Execute the full suite, triage failures, and confirm fixes
• write-unit-tests.md – Generate focused unit tests with proper coverage
• debug-issue.md – Step-by-step debugging workflow for isolating defects
• fix-compile-errors.md – Diagnose and resolve compilation failures quickly
• docker-logs.md – Tail and monitor Docker container logs for debugging

• add-documentation.md – Capture comprehensive product or code documentation
• generate-api-docs.md – Produce rich API documentation with schemas and examples
• onboard-new-developer.md – Checklist-driven onboarding for new teammates
• setup-new-feature.md – Plan requirements, branching, and architecture for new work
• visualize.md – Generate visual diagrams and flowcharts from code or concepts
• diagrams.md – Generate Mermaid diagrams (flowcharts, sequence, class, ER, state diagrams)
• overview.md – Generate Mermaid diagrams for user journey and architecture flow
• roadmap.md – Analyze codebase and generate visual feature roadmaps

• security-audit.md – Structured security checklist for code changes
• security-review.md – Broader vulnerability and risk assessment workflow
• accessibility-audit.md – Review for WCAG compliance issues
• database-migration.md – Plan, create, and validate database migrations with rollbacks
• fix-git-issues.md – Resolve merge conflicts and repository problems safely

• git-commit.md – Create well-structured commit messages with optional issue key linking
• git-push.md – Push changes to remote with pre-push checks

1. Clone this repository or copy the .cursor/commands/ directory into your project
2. Open the project in Cursor IDE
3. Type / in the AI chat to browse available commands
4. Select a command and let Cursor execute the prompt with your code context

# Option 1: clone the repository
git clone https://github.com/hamzafer/cursor-commands.git
cd cursor-commands

# Option 2: copy commands into an existing project
cp -r cursor-commands/.cursor /path/to/your/project/

Alternatively, create the directory manually:

1. Create .cursor/commands/ in your project root
2. Copy or author the Markdown command files you need

Use the existing files as templates or start from scratch:

touch .cursor/commands/my-custom-command.md

# My Custom Command

Brief description of what this command does.

## Objective
Detailed explanation of the task and expected outcome.

## Requirements
- Specific requirements or constraints
- Coding standards to follow
- Expected formats or structures

## Output
Description of what the AI should produce.

Provide clear instructions for the AI to follow.

# Generate API Documentation

Create comprehensive API documentation for the current code. Include:

- Endpoint descriptions and HTTP methods
- Request/response schemas with examples
- Authentication requirements
- Error codes and responses
- Rate limiting information

Format as OpenAPI/Swagger specification.

# Security Audit

Perform a security audit of the current code. Check for:

- SQL injection vulnerabilities
- XSS attack vectors
- Authentication and authorization issues
- Input validation problems
- Sensitive data exposure

Provide specific remediation steps for each issue found.

• Be specific: Describe the expected outcome and acceptance criteria
• Provide context: Reference project conventions, architecture, or standards
• Set boundaries: Clarify scope, assumptions, and tooling limits
• Include examples: Show expected formats or responses when helpful
• Stay focused: Keep each command targeted to a single, clear objective
• Review together: Treat command changes like code changes and review in PRs
• Use descriptive names: Make filenames reflect the command's purpose

• Changelog – v1.6
• Docs – Custom Slash Commands
• Announcement Post 1
• Announcement Post 2

• Open an issue for feedback or requests
• Refer to this README for the command index that ships with the prompts

This project is open source and available under the MIT License.