Insurance Policy Cursor Rules Template for Insurance Coverage Comparison Tools

Overview


Direct answer: This Cursor rules template provides a complete, copyable configuration for building insurance coverage comparison tools from policy documents on a Node.js + TypeScript + PostgreSQL stack using Cursor AI. It equips you to parse policy clauses, normalize coverage terms, and run safe AI-assisted reasoning that feeds precise, auditable results into your API and UI.



When to Use These Cursor Rules



  - Convert diverse policy language into a unified coverage schema for side-by-side comparison.

  - Guide Cursor AI to extract terms such as deductibles, limits, exclusions, riders, and conditions from PDFs or text.

  - Enforce stack-specific architecture with a Node.js + TypeScript API and PostgreSQL data store using TypeORM patterns.

  - Ensure security, data privacy, and auditability for policy data and user interactions.

  - Automate unit and integration checks for policy term parsing and mapping logic.



Copyable .cursorrules Configuration


FrameworkRoleAndContext
  Node.js + TypeScript + PostgreSQL + TypeORM
  You are Cursor AI configured to build a policy parsing and coverage comparison tool.
  Your goal is to keep the codebase secure, testable, and deterministic.

CodeStyleAndGuides
  Use TypeScript strict mode with explicit types
  ESLint with recommended rules and @typescript-eslint plugin
  Prettier formatting on save

ArchitectureAndDirectoryRules
  Monorepo layout at project root
  Packages: api, domain, infra, common, tests
  api/src/controllers, routes, services
  domain/entities, models, dtos
  infra/db/migrations, repositories, adapters
  common/utils, adapters, constants

AuthenticationAndSecurityRules
  JWT-based auth with short-lived access tokens
  OAuth2 for partner integrations
  Secrets stored in vault or environment with rotation
  Validate all inputs; sanitize outputs; avoid sensitive data leakage

DatabaseAndORMPatterns
  PostgreSQL as the data store
  TypeORM as ORM; migrations under infra/db/migrations
  Entities under domain/entities; repositories under infra/repositories
  Use parameterized queries via repository methods; avoid raw string concatenation

TestingAndLintingWorkflows
  Jest with ts-jest for TypeScript tests
  Seed test data; unit tests for domain logic; integration tests for DB
  CI: lint, test, build on push; coverage thresholds enforced

ProhibitedActionsAndAntiPatterns
  Do not build raw SQL with string concatenation
  Do not bypass authentication or authorization checks
  Do not bypass type safety or use any in production code
  Do not mutate policy data in memory without persisting to DB

Recommended Project Structure


project-root/
  src/
    api/
      controllers/
      routes/
      services/
      middleware/
      app.ts
    domain/
      entities/
      models/
      dtos/
    infra/
      db/
        migrations/
        ormconfig.ts
      repositories/
      adapters/
    common/
      utils/
      constants/
    tests/
      unit/
      integration/
  package.json
  tsconfig.json
  .eslintrc.json
  .prettierrc.json

Core Engineering Principles



  - Clear separation of concerns between API, domain, and infrastructure

  - Strong typing and explicit interfaces for all data shapes

  - Deterministic Cursor AI guidance with auditable decisions

  - Security by default: proper validation, least privilege, and secret management

  - Test-driven approach with unit, integration, and CI checks



Code Construction Rules



  - All business logic lives in domain/services and is accessed via API layer

  - Use repository pattern for data access; never query DB from services directly

  - DTOs for request/response shaping; avoid leaking domain models to API

  - TypeORM entities define schema; migrations under infra/db/migrations

  - Cursor AI prompts must reference the exact stack: Node.js, TypeScript, PostgreSQL, TypeORM

  - Environment variables for config; default values controlled by env or config files

  - Do not hard-code secrets; use a vault or secret manager in all environments



Security and Production Rules



  - Enforce TLS for all external endpoints; enable secure cookies

  - Rotate secrets and keep credentials out of source control

  - Validate all input; apply schema validation to policy data before processing

  - Audit trails for policy data changes and AI-assisted actions

  - Limit rate and implement anomaly detection for policy queries



Testing Checklist



  - Unit tests for domain logic and data transformations

  - Integration tests for API endpoints and database interactions

  - End-to-end tests simulating policy document flow and UI outputs

  - CI checks for linting, type checks, and test coverage thresholds



Common Mistakes to Avoid



  - Introducing ad hoc SQL in services; bypassing repository boundaries

  - Ignoring data privacy when parsing policy documents

  - Overusing any and bypassing TypeScript types

  - Skipping migrations or mixing migration states across environments

  - Failing to seed realistic test data for integration tests



Related implementation resources: AI Agent Use Case for Environmental Consultants Using Field Notes to Generate Regulatory Reports and Implementing Parameterized Testing Matrices for Wide Input Coverage in Production AI.





FAQ


What is a Cursor Rules Template for insurance tooling?


A Cursor Rules Template provides a copyable .cursorrules configuration that guides Cursor AI to operate within a specific stack. For insurance tooling, it models policy document parsing, term normalization, and comparison logic in a Node.js + TypeORM environment, with a focus on security and auditability.


Which stack does this template target?


This template targets Node.js with TypeScript, PostgreSQL as the data store, and TypeORM as the ORM. It assumes an Express-like API structure and a monorepo layout to separate domain, API, and infra concerns.


How do I adapt policy documents into the tool?


Use the Cursor AI prompts to extract clauses such as coverage limits, deductibles, exclusions, and rider terms. Map extracted data to a unified coverage schema and persist it via controlled repositories for comparison UIs.


How should I test Cursor AI outputs?


Test domain logic with unit tests for transformation rules, test repository interactions with integration tests, and validate AI-generated outputs against known policy data in a CI pipeline with coverage guarantees.


Can I adapt this template to a different database?


Yes. The template is designed for PostgreSQL with TypeORM but the architecture supports swapping the ORM or database. Update migrations, entities, repositories, and connection options accordingly, keeping API and domain logic intact.