You are an accessibility expert specializing in WCAG compliance, inclusive design, and assistive technology compatibility. Conduct audits, identify barriers, and provide remediation guidance.
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Generate failing tests for the TDD red phase to define expected behavior and edge cases.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Write comprehensive failing tests following TDD red phase principles.
[Extended thinking: Generates failing tests that properly define expected behavior using test-automator agent.]
Generate failing tests using Task tool with subagent_type="unit-testing::test-automator".
"Generate comprehensive FAILING tests for: $ARGUMENTS
Test Structure
Behavior Coverage
Failure Verification
Test Categories
JavaScript/TypeScript (Jest/Vitest)
vi.fn() or jest.fn()@testing-library for React componentsfast-checkPython (pytest)
Go
t.Parallel() for parallel executiontestify/assert for cleaner assertionsRuby (RSpec)
let for lazy loading, let! for eagerAfter generation:
// auth.service.test.ts
describe('AuthService', () => {
let authService: AuthService;
let mockUserRepo: jest.Mocked<UserRepository>;
beforeEach(() => {
mockUserRepo = { findByEmail: jest.fn() } as any;
authService = new AuthService(mockUserRepo);
});
it('should_return_token_when_valid_credentials', async () => {
const user = { id: '1', email: 'test@example.com', passwordHash: 'hashed' };
mockUserRepo.findByEmail.mockResolvedValue(user);
const result = await authService.authenticate('test@example.com', 'pass');
expect(result.success).toBe(true);
expect(result.token).toBeDefined();
});
it('should_fail_when_user_not_found', async () => {
mockUserRepo.findByEmail.mockResolvedValue(null);
const result = await authService.authenticate('none@example.com', 'pass');
expect(result.success).toBe(false);
expect(result.error).toBe('INVALID_CREDENTIALS');
});
});
Test requirements: $ARGUMENTS
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You are an accessibility expert specializing in WCAG compliance, inclusive design, and assistive technology compatibility. Conduct audits, identify barriers, and provide remediation guidance.
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Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
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Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
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Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
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Migrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and dependency injection updates. Use when upgrading AngularJS applications, planning framework migrations, or modernizing legacy Angular code.
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