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。
Conduct context-driven code reviews focusing on quality, testability, and maintainability. Use when reviewing code, providing feedback, or establishing review practices.
中文简介正在准备中。当前显示原文说明。
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
<default_to_action> When reviewing code or establishing review practices:
Quick Review Checklist:
Critical Success Factors:
| Level | Icon | Meaning | Action |
|---|---|---|---|
| Blocker | 🔴 | Bug/security/crash | Must fix before merge |
| Major | 🟡 | Logic issue/test gap | Should fix before merge |
| Minor | 🟢 | Style/naming | Nice to fix |
| Suggestion | 💡 | Alternative approach | Consider for future |
| Lines Changed | Recommendation |
|---|---|
| < 200 | Single review session |
| 200-400 | Review in chunks |
| > 400 | Request PR split |
| ✅ Review | ❌ Skip |
|---|---|
| Logic correctness | Formatting (use linter) |
| Security risks | Naming preferences |
| Test coverage | Architecture debates |
| Performance issues | Style opinions |
| Error handling | Trivial changes |
🔴 **BLOCKER: SQL Injection Risk**
This query is vulnerable to SQL injection:
```javascript
db.query(`SELECT * FROM users WHERE id = ${userId}`)
Fix: Use parameterized queries:
db.query('SELECT * FROM users WHERE id = ?', [userId])
Why: User input directly in SQL allows attackers to execute arbitrary queries.
### Major (Should Fix)
```markdown
🟡 **MAJOR: Missing Error Handling**
What happens if `fetchUser()` throws? The error bubbles up unhandled.
**Suggestion:** Add try/catch with appropriate error response:
```javascript
try {
const user = await fetchUser(id);
return user;
} catch (error) {
logger.error('Failed to fetch user', { id, error });
throw new NotFoundError('User not found');
}
### Minor (Nice to Fix)
```markdown
🟢 **minor:** Variable name could be clearer
`d` doesn't convey meaning. Consider `daysSinceLastLogin`.
💡 **suggestion:** Consider extracting this to a helper
This validation logic appears in 3 places. A `validateEmail()` helper would reduce duplication. Not blocking, but might be worth a follow-up PR.
Reviews must meet a minimum weighted finding score of 3.0 (CRITICAL=3, HIGH=2, MEDIUM=1, LOW=0.5, INFORMATIONAL=0.25). If the initial review falls short, run the qe-devils-advocate agent as a meta-reviewer to find additional observations. Every review should have at least 3 actionable observations.
// Comprehensive code review
await Task("Code Review", {
prNumber: 123,
checks: ['security', 'performance', 'testability', 'maintainability'],
feedbackLevels: ['blocker', 'major', 'minor'],
autoApprove: { maxBlockers: 0, maxMajor: 2 }
}, "qe-quality-analyzer");
// Security-focused review
await Task("Security Review", {
prFiles: changedFiles,
scanTypes: ['injection', 'auth', 'secrets', 'dependencies']
}, "qe-security-scanner");
// Test coverage review
await Task("Coverage Review", {
prNumber: 123,
requireNewTests: true,
minCoverageDelta: 0
}, "qe-coverage-analyzer");
aqe/code-review/
├── review-history/* - Past review decisions
├── patterns/* - Common issues by team/repo
├── feedback-templates/* - Reusable feedback
└── metrics/* - Review turnaround time
const reviewFleet = await FleetManager.coordinate({
strategy: 'code-review',
agents: [
'qe-quality-analyzer', // Logic, maintainability
'qe-security-scanner', // Security risks
'qe-performance-tester', // Performance issues
'qe-coverage-analyzer' // Test coverage
],
topology: 'parallel'
});
| ✅ Do | ❌ Don't |
|---|---|
| "Have you considered...?" | "This is wrong" |
| Explain why it matters | Just say "fix this" |
| Acknowledge good code | Only point out negatives |
| Suggest, don't demand | Be condescending |
| Review < 400 lines | Review 2000 lines at once |
Prioritize feedback: 🔴 Blocker → 🟡 Major → 🟢 Minor → 💡 Suggestion. Focus on bugs and security, not style. Ask questions, don't command. Review < 400 lines at a time. Fast feedback (< 24h) beats thorough feedback.
With Agents: Agents automate security, performance, and coverage checks, freeing human reviewers to focus on logic and design. Use agents for consistent, fast initial review.
/security-testing for security-focused review/qe-coverage-analysis on changed files/qe-quality-assessment还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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。