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.
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Apply safe refactoring patterns to improve code structure without changing behavior. Use when cleaning up code, reducing technical debt, or improving maintainability.
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<default_to_action> When refactoring:
Safe Refactoring Cycle:
npm test # Green ✅
# Make ONE small change
npm test # Still green ✅
git commit -m "refactor: extract calculateTotal"
# Repeat
Code Smells → Refactoring:
| Smell | Refactoring |
|---|---|
| Long method (>20 lines) | Extract Method |
| Large class | Extract Class |
| Long parameter list (>3) | Introduce Parameter Object |
| Duplicated code | Extract Method/Class |
| Complex conditional | Decompose Conditional |
| Magic numbers | Named Constants |
| Nested loops | Replace Loop with Pipeline |
NEVER REFACTOR:
| Pattern | Before | After |
|---|---|---|
| Extract Method | 50-line function | 5 small functions |
| Extract Class | Class doing 5 things | 5 single-purpose classes |
| Parameter Object | fn(a,b,c,d,e,f) | fn(options) |
| Replace Conditional | if (type === 'a') {...} | Polymorphism |
| Pipeline | Nested loops | .filter().map().reduce() |
// Before: Long method
function processOrder(order) {
// 50 lines of validation, calculation, saving, emailing...
}
// After: Clear responsibilities
function processOrder(order) {
validateOrder(order);
const pricing = calculatePricing(order);
const saved = saveOrder(order, pricing);
sendConfirmationEmail(saved);
return saved;
}
// Before
let results = [];
for (let item of items) {
if (item.inStock) {
results.push(item.name.toUpperCase());
}
}
// After
const results = items
.filter(item => item.inStock)
.map(item => item.name.toUpperCase());
// Before
if (order.total > 1000 && customer.isPremium && allInStock(order)) {
return 'FREE_SHIPPING';
}
// After
function isEligibleForFreeShipping(order, customer) {
return isLargeOrder(order) &&
isPremiumCustomer(customer) &&
allInStock(order);
}
| ❌ Anti-Pattern | Problem | ✅ Better |
|---|---|---|
| Without tests | No safety net | Write tests first |
| Big bang | Rewrite everything | Small incremental steps |
| For perfection | Endless tweaking | Good enough, move on |
| Premature abstraction | Pattern not clear yet | Wait for Rule of Three |
| During feature work | Mixed changes | Separate commits |
// Detect code smells
const smells = await Task("Detect Code Smells", {
source: 'src/services/',
patterns: ['long-method', 'large-class', 'duplicate-code']
}, "qe-quality-analyzer");
// Safe refactoring with test verification
await Task("Verify Refactoring", {
beforeCommit: 'abc123',
afterCommit: 'def456',
expectSameBehavior: true
}, "qe-test-executor");
aqe/refactoring/
├── smells/* - Detected code smells
├── suggestions/* - Refactoring recommendations
├── verifications/* - Behavior preservation checks
└── history/* - Refactoring log
const refactoringFleet = await FleetManager.coordinate({
strategy: 'refactoring',
agents: [
'qe-quality-analyzer', // Identify targets
'qe-test-generator', // Add safety tests
'qe-test-executor', // Verify behavior
'qe-test-refactorer' // TDD refactor phase
],
topology: 'sequential'
});
Refactoring is NOT:
Refactoring IS:
Always have tests. Always take small steps. Always keep tests green.
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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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
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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.
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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.
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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.
中文简介正在准备中。当前显示原文说明。