Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
日本語の概要は準備中です。原文の説明を表示しています。
Move testing activities earlier in the development lifecycle to catch defects when they're cheapest to fix. Use when implementing TDD, CI/CD, or early quality practices.
日本語の概要は準備中です。原文の説明を表示しています。
実行スコア 未検証
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
<default_to_action> When implementing early testing practices:
Quick Shift-Left Levels:
Critical Success Factors:
| Phase | Relative Cost | Example |
|---|---|---|
| Requirements | 1x | Fix doc: 30 min |
| Design | 5x | Redesign: few hours |
| Development | 10x | Code fix: 1 day |
| Testing | 20x | Fix + retest: 2 days |
| Production | 100x | Hotfix + rollback + investigation |
/\ E2E (10%) - Critical user journeys
/ \
/ \ Integration (20%) - Component interactions
/ \
/________\ Unit (70%) - Fast, isolated, comprehensive
| Level | Practice | When |
|---|---|---|
| 1 | Unit tests in PR | Before merge |
| 2 | TDD | Before implementation |
| 3 | BDD/Example Mapping | During refinement |
| 4 | Risk Analysis | During design |
# CI pipeline - tests run on every commit
name: CI
on: [push, pull_request]
jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- run: npm ci
- run: npm run test:unit
- run: npm run test:integration
- run: npm run lint
quality-gate:
needs: test
steps:
- name: Coverage Check
run: npx coverage-check --min 80
- name: No New Warnings
run: npm run lint -- --max-warnings 0
// Red: Write failing test first
test('calculates discount for orders over $100', () => {
const order = new Order([{ price: 150 }]);
expect(order.discount).toBe(15); // 10% off
});
// Green: Minimal implementation
class Order {
get discount() {
return this.total > 100 ? this.total * 0.1 : 0;
}
}
// Refactor: Improve while keeping green
# Example mapping before coding
Feature: Loyalty Discount
Scenario: Gold member gets 15% discount
Given a customer with "gold" membership
When they checkout with $200 in cart
Then discount applied is $30
And order total is $170
Scenario: New customer gets no discount
Given a customer with no membership
When they checkout with $200 in cart
Then no discount is applied
// During architecture review
await Task("Risk Analysis", {
phase: 'design',
component: 'payment-service',
questions: [
'What happens when payment gateway times out?',
'How do we handle duplicate submissions?',
'What if inventory changed during checkout?'
]
}, "qe-requirements-validator");
// Output: Testability requirements, failure mode tests
// Validate requirements testability
await Task("Requirements Validation", {
requirements: userStories,
check: ['INVEST-criteria', 'testability', 'ambiguity'],
generateBDD: true
}, "qe-requirements-validator");
// Generate tests from requirements
await Task("Generate Tests", {
source: 'requirements',
types: ['unit', 'integration', 'e2e'],
coverage: 'comprehensive'
}, "qe-test-generator");
// Smart test selection for changes
await Task("Select Regression Tests", {
changedFiles: prFiles,
algorithm: 'risk-based',
targetReduction: 0.7 // 70% time savings
}, "qe-regression-risk-analyzer");
aqe/shift-left/
├── requirements/* - Validated requirements
├── generated-tests/* - Auto-generated tests
├── coverage-targets/* - Coverage goals by component
└── pipeline-results/* - CI/CD test history
const shiftLeftFleet = await FleetManager.coordinate({
strategy: 'shift-left',
agents: [
'qe-requirements-validator', // Level 3-4
'qe-test-generator', // Level 2
'qe-regression-risk-analyzer' // Smart selection
],
topology: 'sequential'
});
Earlier = Cheaper. Requirements defects cost 1x; production defects cost 100x. Test pyramid: 70% unit, 20% integration, 10% E2E. Every commit runs tests. TDD builds quality in.
With Agents: Agents validate requirements testability, generate tests from specs, and select optimal regression suites. Use agents to implement shift-left practices consistently.
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Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
日本語の概要は準備中です。原文の説明を表示しています。
WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
日本語の概要は準備中です。原文の説明を表示しています。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
日本語の概要は準備中です。原文の説明を表示しています。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
日本語の概要は準備中です。原文の説明を表示しています。