cursor-best-practices
Guidance for maximizing Cursor productivity through planning, context management, and effective agent workflows.
Works with
What it does
Start with Plan Mode for complex tasks and manage context by letting the agent find relevant code, starting fresh conversations when needed
Extend agent capabilities using Rules for static context and Skills for dynamic, reusable operations
Adopt test-driven development, use the agent to explore codebases, automate git operations, and run parallel agents for comparison
Installation Guide
How to use cursor-best-practices on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
cursor-best-practices
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches cursor-best-practices from siviter-xyz/dot-agent and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate cursor-best-practices. Access via /cursor-best-practices in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
Cursor Best Practices
Best practices for working with Cursor to maximize productivity and code quality.
Core Principles
- Start with plans - Use Plan Mode (Shift+Tab) for complex tasks
- Manage context effectively - Let agent find context, start new conversations when needed
- Extend the agent - Use Rules for static context, Skills for dynamic capabilities
- Review carefully - AI-generated code needs review like human code
Key Workflows
- Test-driven development - Write tests first, iterate until passing
- Codebase understanding - Use agent to explore and learn codebases
- Git workflows - Automate common git operations with commands
- Parallel agents - Run multiple agents simultaneously for comparison
References
For detailed guidance, see:
references/planning.md- Plan mode and starting with plansreferences/context.md- Managing context and conversationsreferences/extending.md- Rules vs Skills, extending agentreferences/workflows.md- TDD, codebase understanding, git workflowsreferences/reviewing.md- Code review strategiesreferences/parallel-agents.md- Running agents in parallel
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Use Cases
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale