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:
| 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
// 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'
});
With Agents: Agents validate requirements testability, generate tests from specs, and select optimal regression suites. Use agents to implement shift-left practices consistently.
/tdd-london-chicago for specific TDD guidance/qe-test-generation for AI-powered test generation/cicd-pipeline-qe-orchestrator for pipeline setupまだレビューはありません。使ってみた感想をお寄せください。
ログインなしで書き込めます。使ってみた感想、質問、動かなかった環境などを気軽にどうぞ。
まだコメントはありません。最初のコメントを書いてみませんか。
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。