Cursor Rules Template: SaaS Churn Dashboard for SaaS SMEs

Overview

Cursor rules configuration for building churn prediction dashboards tailored to SaaS SMEs using a modern full-stack with Next.js, PostgreSQL, and Prisma. This template includes a complete, copyable .cursorrules block and stack-specific guidance to ensure consistent, secure dashboards and trustworthy churn insights. Direct answer: configure data ingestion, feature engineering, model scoring, and dashboard rendering in a disciplined Cursor workflow.

When to Use These Cursor Rules

• Building a churn analytics dashboard for a SaaS SME with monthly recurring revenue (MRR).
• Standardizing data access patterns across API, UI, and analytics layers.
• Ensuring security, auditing, and governance for customer data in dashboards.
• Automating the generation of dashboards from event streams and database aggregates.

Copyable .cursorrules Configuration

cursor_rules_template:
  framework: Next.js with TypeScript
  stack: [Next.js, PostgreSQL, Prisma, React]
  description: Cursor rules for churn dashboards in SaaS SMEs

# Framework Role & Context
role_and_context:
  role: Cursor Rules Engineer
  context: You are building a churn dashboard for SaaS SMEs using Cursor AI in a Next.js app with PostgreSQL and Prisma.

# Code Style and Style Guides
coding_standards:
  language: TypeScript
  lint: ESLint + Prettier
  tsconfig:
    strict: true
    noImplicitAny: true

# Architecture & Directory Rules
architecture:
  - apps/dashboard
  - prisma
  - lib/db
  - src/pages/api
  - src/components

# Authentication & Security Rules
security:
  auth:
    type: JWT RS256
    refresh: true
    audience: dashboard.api
    csrf_protect: true
  secrets:
    env: true

# Database and ORM patterns
database:
  orm: Prisma
  db: PostgreSQL
  migrations: true
  indexing: [idx_churn_score, idx_event_created_at]
  patterns: [read_replica, db_connection_pool]

# Testing & Linting Workflows
testing:
  unit: Jest + React Testing Library
  e2e: Playwright
  ci: GitHub Actions: lint, test, build, deploy

# Prohibited Actions and Anti-patterns
anti_patterns:
  - Do not access DB directly from React components
  - Do not embed secrets in frontend
  - Do not bypass ORM for business logic
  - Do not store PII in logs
  - Do not rely on client-side caching for accurate metrics

Recommended Project Structure

/apps/dashboard
  /src
    /pages
    /components
    /styles
  /public
  /utils
  /hooks
  /layouts
/prisma
  schema.prisma
  migrations/
/lib
  /db
  /services

Core Engineering Principles

• Principle of least privilege for data access.
• Separation of concerns between API, UI, and analytics layers.
• Idempotent migrations and reproducible environments.
• Explicit typing and strict validation for data at rest and in transit.
• Observability: structured logs, metrics, and tracing for dashboards.

Code Construction Rules

• Use Prisma migrations for schema changes; seed data via prisma/seed.ts.
• Frontend pages use server-side data fetching for initial churn metrics to avoid hydration gaps.
• All API routes implement proper input validation and output sanitizer.
• Feature flags gate experimental charts and model features in UI.
• Do not fetch large datasets on client; paginate and stream where possible.

Security and Production Rules

• Store secrets in Vault or platform secret management; never commit to repo.
• Use RS256 for JWTs and refresh tokens; rotate keys regularly.
• Protect endpoints with CSRF tokens for mutating actions; adopt per-request rate limiting.

Testing Checklist

• Unit tests for data transformation and utility functions.
• Integration tests for API routes with Prisma and DB mocks.
• End-to-end tests for dashboard flows using Playwright.
• Static analysis: TypeScript type checks and linting in CI.
• Performance tests for large event streams and rolling-window aggregations.

Common Mistakes to Avoid

• Exposing DB credentials or secret keys to the frontend.
• Over-fetching data in API responses; underutilizing Prisma includes.
• Skipping migrations or relying on ad-hoc DB changes in production.
• Ignoring data privacy when building churn dashboards (PII handling).

Related implementation resources: AI Agent Use Case for Call Centers Using Conversation Transcripts to Monitor Service Quality and Skill files for production-grade admin dashboards.

FAQ

What stack does this Cursor Rules Template target?

The template targets a Next.js (TypeScript) frontend with PostgreSQL as the database and Prisma as the ORM, designed for SaaS churn dashboards. It aligns Cursor AI instructions to secure data flow, observable metrics, and reproducible deployments.

How do I use the copyable .cursorrules block?

Place the copied .cursorrules block in your project root as .cursorrules. Cursor AI will apply the defined roles, architecture, security, and testing practices to scaffold and validate your churn dashboard stack.

What security practices are included?

JWT RS256 authentication, CSRF protection, secrets management, and least-privilege access policies are enforced. Endpoints should validate tokens, and sensitive data must never be exposed to the client.

What tests should be included for dashboards?

Include unit tests for UI and data transformations, integration tests for API endpoints with Prisma, and Playwright-based end-to-end tests for dashboard flows and user interactions.

What is the recommended project structure?

A clear separation: apps/dashboard for Next.js UI, prisma for ORM/migrations, lib/db for DB utilities, and modules for components and utilities to enable maintainable dashboards.