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frontendhigh PriorityID: vitest-testing-frontend

Vitest & Testing Library User-Centric Test Standard

Conventions for Vitest & React/Vue Testing Library: test user behavior rather than implementation details, use screen.getByRole, and mock network calls cleanly with MSW.

Prohibited Anti-Pattern: AI tests internal state values and props, writes fragile test selectors, or tests implementation details.

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---
description: Vitest & Testing Library User-Centric Test Standard - Conventions for Vitest & React/Vue Testing Library: test user behavior rather than implementation details, use screen.getByRole, and mock network calls cleanly with MSW.
globs: **/*.test.ts, **/*.test.tsx, **/*.spec.ts
alwaysApply: false
verified_by: "agentrules.org"
license: "CC-BY-4.0"
source: "https://agentrules.org/rules/vitest-testing-frontend"
---

# Vitest & Testing Library User-Centric Test Standard

> **Severity**: HIGH | **Category**: frontend
> **Anti-Pattern Warning**: AI tests internal state values and props, writes fragile test selectors, or tests implementation details.

## System Constraints
You are a quality assurance engineer. Write resilient unit and integration tests using Vitest and Testing Library. Query elements by accessible role (screen.getByRole), simulate user interactions with @testing-library/user-event, and never assert on internal component state.

## Strict Guidelines
- Prioritize accessible queries: getByRole, getByLabelText, getByText over container.querySelector or class selectors.
- Use userEvent.setup() over fireEvent for realistic browser interaction simulation.
- Mock network boundaries using Mock Service Worker (MSW) instead of stubbing internal fetch functions.

## Bad vs Good Implementations
### Accessible Role Query vs Class Selector

#### Bad Antipattern (AI Common Hallucination)
> **Why it fails**: Querying CSS classes breaks whenever design refactors occur and fails to verify accessibility.
```tsx
// Fragile: Relies on CSS classes and implementation details
test("submits form", () => {
  const { container } = render(<LoginForm />);
  const button = container.querySelector(".submit-btn-primary"); // Fragile
  fireEvent.click(button!);
  expect(button?.textContent).toBe("Submitting...");
});
```

#### Production Standard (Correct)
> **Standard**: Tests the user-visible workflow through accessible semantics, making tests resilient to refactoring.
```tsx
// Resilient: Queries by accessible role and simulates user input
import { render, screen } from "@testing-library/react";
import userEvent from "@testing-library/user-event";

test("submits form successfully", async () => {
  const user = userEvent.setup();
  render(<LoginForm />);

  await user.type(screen.getByLabelText(/email/i), "[email protected]");
  await user.click(screen.getByRole("button", { name: /log in/i }));

  expect(await screen.findByText(/welcome back/i)).toBeInTheDocument();
});
```
Recommended MCP Servers (mcp-serverlist.com)

Equip agent with system tools to verify code for this stack.

Test Runner MCP
Execute Vitest suites and stream coverage reports.
Recommended Agent Skills (askills.dev)

Ready-to-use executable skill functions tailored to this stack.

Vitest Scenario Generator
Generate comprehensive edge-case test suites for components.
Architectural Specification & Invariant Rationale

Architectural Invariant Design: Vitest & Testing Library User-Centric Test Standard

Vitest & Testing Library User-Centric Test Standard defines an industrial-grade behavioral standard for frontend engineering. Conventions for Vitest & React/Vue Testing Library: test user behavior rather than implementation details, use screen.getByRole, and mock network calls cleanly with MSW. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.

Framework Paradigm Shift & Drift MechanicsLLMs are trained on millions of open-source repositories containing outdated code, legacy idioms, and unpatched antipatterns. When coding assistants generate implementations for this stack, they default to common statistical tokens: AI tests internal state values and props, writes fragile test selectors, or tests implementation details. Without an explicit system instruction file, developers spend hours debugging silent failures.
Failure Modes & Production Blast Radius

Hazard Analysis: What Breaks Without This Rule

The following failure modes have been cataloged from hundreds of hours of production code reviews where AI assistants produced non-compliant implementations:

Failure ModeAI Symptom (The Anti-Pattern)SeverityProduction Impact & Remedy
AI Hallucination & Deprecation DriftAI tests internal state values and props, writes fragile test selectors, or tests implementation details.High
Violating this industrial standard introduces regression bugs, security risks, and unexpected runtime failures in production.
Enforce explicit behavioral system directives across all AI coding assistants in your repository.
Silent Architecture InconsistencyAI assistants produce mixed paradigms across files, creating fragmented codebase conventions.Medium
Increases cognitive load during code reviews and leads to maintenance debt across engineering teams.
Pin project conventions in .cursor/rules, CLAUDE.md, and AGENTS.md so all team agents follow identical guardrails.
Architectural Directives in Detail

Step-by-Step Production Directives

Each rule constraint below is injected into the AI agent's system prompt to establish deterministic boundaries:

1

Prioritize accessible queries

Prioritize accessible queries: getByRole, getByLabelText, getByText over container.querySelector or class selectors.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
2

Use userEvent.setup() over fireEvent for realistic browser interaction simulation.

Use userEvent.setup() over fireEvent for realistic browser interaction simulation.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
3

Mock network boundaries using Mock Service Worker (MSW) instead of stubbing internal fetch functions.

Mock network boundaries using Mock Service Worker (MSW) instead of stubbing internal fetch functions.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
Technical Questions & Answers

Frequently Asked Technical Questions

Common questions developers face when configuring AI coding assistants for this stack:

Q:Why is Vitest & Testing Library User-Centric Test Standard critical for AI coding assistants?

Conventions for Vitest & React/Vue Testing Library: test user behavior rather than implementation details, use screen.getByRole, and mock network calls cleanly with MSW. Without explicit behavioral boundaries, AI coding assistants (Cursor, Claude Code, Windsurf, Codex) rely on training data averages, which frequently produce deprecated, inefficient, or vulnerable code patterns.

Q:How does adopting this rule prevent AI hallucinations?

This rule explicitly declares what the AI must avoid (AI tests internal state values and props, writes fragile test selectors, or tests implementation details.) and prescribes verified positive examples. Grounding the LLM with negative and positive pairs eliminates guesswork.

Q:Which AI coding environments are supported?

This specification is multi-platform compatible: Cursor (.cursor/rules/*.mdc & .cursorrules), Anthropic Claude Code (CLAUDE.md), Windsurf (.windsurfrules), Codex / Cline (AGENTS.md), and GitHub Copilot (.github/copilot-instructions.md).

Q:Can I combine this rule with other technology stacks?

Yes. Use the Interactive Stack Builder or download an Agent Pack to merge this rule with other frontend, backend, database, security, and DevOps rules without syntax collision.

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Citation & Open Source Attribution Guidelines

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1 Rule in Stack

Vitest