Code Generation Prompts: Writing Modular Functions, Unit Tests, and API Integrations

AI-assisted code generation requires structured context injection. Feeding raw code snippets without operational context leads to API hallucinations, missing imports, and subtle type mismatch vulnerabilities in production codebases.

To achieve production-grade TypeScript, Python, or Go code generation, system directives must strictly enforce type annotations, error boundary wrappers, and clean unit testing patterns.

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1. Stack Trace Debugging & Bug-Fixing Directives

When dealing with complex runtime exceptions, modern LLMs perform best when context is partitioned using explicit XML tags (``, ``, ``).

```xml

Identify the root cause of runtime crash and provide an optimized, type-safe refactor.

TypeError: Cannot read properties of undefined (reading 'map')

at UserList (components/UserList.tsx:24:18)

at processChild (react-dom.development.js:14221)

export const UserList = ({ users }) => {

return (

{users.map(user => (

• {user.name}

))}

);

};

Do NOT use arbitrary optional chaining without verifying data state upstream.

Define an explicit TypeScript interface for User props.

Provide fallback UI when users array is null or empty.

```

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2. Generating Comprehensive Unit Tests (Vitest / Jest / PyTest)

High-converting code generation prompts specify the test runner, boundary conditions, and mock implementations required for robust CI/CD integration.

```typescript

// Prompt Output: Generated Vitest Suite for Async Payment Processor

import { describe, it, expect, vi, beforeEach } from 'vitest';

import { processPayment } from './paymentService';

describe('processPayment Service Unit Tests', () => {

const mockDb = { updateOrderStatus: vi.fn() };

const mockStripe = { charges: { create: vi.fn() } };

beforeEach(() => {

vi.clearAllMocks();

});

it('should successfully process valid card payment and update order status', async () => {

mockStripe.charges.create.mockResolvedValueOnce({ id: 'ch_123', status: 'succeeded' });

mockDb.updateOrderStatus.mockResolvedValueOnce(true);

const result = await processPayment({ orderId: 'ord_99', amount: 4999 }, mockStripe, mockDb);

expect(result.success).toBe(true);

expect(mockDb.updateOrderStatus).toHaveBeenCalledWith('ord_99', 'PAID');

});

it('should throw PaymentFailedException and log audit when gateway declines card', async () => {

mockStripe.charges.create.mockRejectedValueOnce(new Error('Card Declined'));

await expect(

processPayment({ orderId: 'ord_99', amount: 4999 }, mockStripe, mockDb)

).rejects.toThrow('Card Declined');

expect(mockDb.updateOrderStatus).toHaveBeenCalledWith('ord_99', 'FAILED');

});

});

```

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3. Best Practices for API Integration Prompts

1. Supply OpenAPI / Swagger Schemas: Paste target JSON endpoint schemas directly into `` tags.

2. Mandate Resilience Patterns: Direct the model to include exponential backoff retries, rate limiting handlers, and error code normalization.

3. Strict Return Types: Never allow implicit `any` return values in TypeScript code generation outputs.