Cursor Rules Template: React-Node-PostgreSQL Skills Matrix with AI Recommendations | Suhas Bhairav

Overview

Cursor rules configuration for building a scalable skills matrix and workforce planning tool using a React frontend, Node.js backend, and PostgreSQL data store. This template is meant for developers who want a copyable Cursor AI instruction block that guides structure, data model, and AI-driven recommendations within a production-grade stack.

Direct answer: Paste the included .cursorrules block into your project root to configure Cursor AI to assist with building and maintaining the skills matrix, certifications lifecycle, and AI-based workforce guidance on a React-Node-PostgreSQL stack.

When to Use These Cursor Rules

Kick off a new workforce-planning tool that tracks skills, certifications, and training needs for employees or contractors.
Enforce consistent architecture, security, and testing practices across the stack.
Auto-generate AI-driven recommendations for skill gaps and certification paths based on role hierarchies.
Provide a repeatable, auditable rule set for CI/CD and governance in HR tech tooling.

Copyable .cursorrules Configuration

Paste this inside your project root as .cursorrules to enable Cursor AI-driven development for the React-Node-PostgreSQL stack.

Framework: React-Node-PostgreSQL
Context: You are Cursor AI tasked with helping a development team implement a scalable skills matrix and workforce planning tool that tracks certifications, training gaps, and AI-based recommendations. Target environment: web app with a REST/GraphQL API, PostgreSQL database, and JWT-based auth.
CodeStyle: TypeScript + ESLint + Prettier
Architecture: Monorepo with apps/web, services/api, libs/core, libs/ui
DirectoryRules: apps/web/, services/api/, libs/core/, libs/ui/
AuthenticationSecurity: JWTs; RBAC; httpOnly cookies; CSRF
DatabaseORM: PostgreSQL; use repository/service pattern; avoid concatenated SQL; parameterized queries
TestingLinting: Jest + RTL; Cypress; GitHub Actions
ProhibitedActions: Do not bypass auth; do not generate raw SQL on the client; do not expose secrets in code; do not expose credentials in logs; do not skip linting or tests in CI

Recommended Project Structure

apps/
  web/          # Next.js/React frontend
services/
  api/          # Node.js API layer (REST/GraphQL)
libs/
  core/         # Domain models and rules
  ui/           # Shared UI components for dashboards and charts
tools/
  migrations/   # DB migrations and seed data

Core Engineering Principles

Respect strong typing and clear contracts across frontend/backend boundaries.
Favor modular, testable components and services.
Prefer explicit data models and explicit access controls.
Maintain a single source of truth for skills, certifications, and coaching data.
Automate validation, CI, and deployment of HR tooling.

Code Construction Rules

Define a strict data model for skills, roles, and certifications with clear relationships.
Implement repository/service patterns to isolate data access from business logic.
Guard against orphaned certifications and expired credentials with scheduled jobs.
Validate role-based access for all endpoints and UI actions.
Document every rule and data flow for compliance and audits.

Security and Production Rules

Use JWT-based auth with RBAC and encrypted tokens; enforce least privilege.
Store secrets in a secure vault; rotate credentials regularly.
Apply CSP, CSRF protection, and secure cookies in the web app.
Validate inputs and parameterize all queries to avoid SQL injection.
Monitor with structured logging and anomaly detection in production.

Testing Checklist

Unit tests for data models and services; integration tests for API endpoints.
End-to-end tests for user workflows: add employee, assign skills, enroll in certs.
Linting and formatting enforced in CI; pre-commit hooks for code quality.
Performance checks for heavy join queries and caching strategies.

Common Mistakes to Avoid

Overly coupled UI to API contracts; breaking frontend changes with backend updates.
Skipping authentication checks on critical routes; exporting raw credentials in logs.
Ignoring data privacy when collecting employee skill data; failing to implement role checks.

Related Cursor rules templates

Explore adjacent Cursor rules templates for similar stacks, workflows, and production constraints.

FAQ

What is the purpose of this Cursor Rules Template?

This template provides a ready-to-paste Cursor AI configuration to guide the development of a skills matrix and workforce planning tool using React for the frontend, Node.js for the API, and PostgreSQL for data storage. It ensures consistent architecture, security, and testing practices while enabling AI-driven recommendations.

How should certifications and training gaps be modeled?

Certifications have issuers, issue dates, and renewal workflows. Training gaps compare employee skill profiles to required roles, prioritizing certifications that close critical gaps. The template emphasizes data integrity and auditable change history.

Can Cursor AI generate actionable recommendations?

Yes. The rules include guidance to derive AI-driven recommendations from skills data, role hierarchies, and training histories. It surfaces suggested trainings, certifications, and workforce shifts aligned with business goals and compliance.

What security practices are enforced by the rules?

JWT-based authentication with RBAC, secure cookies, CSRF protection, and input validation are enforced. Secrets live in a vault, and all access is audited. Database interactions use parameterized queries to prevent injections.

What should I test in this stack?

Unit tests for models and services, integration tests for API routes, and end-to-end tests for critical user journeys (adding employees, assigning skills, and cert tracking). CI should fail on linting or test failures to maintain quality.

Cursor Rules Template: React-Node-PostgreSQL Skills Matrix with Certifications and AI Recommendations

Target User

Use Cases