affaan-m/benchmark
docs/zh-CN/skills/benchmark/SKILL.md
使用此技能测量性能基线，检测PR前后的回归，并比较堆栈替代方案。
$ install --global
skillsauthnpx skillsauth add affaan-m/everything-claude-code benchmarkInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: May 16, 2026, 3:51 AM149.5s1 file scanned
SKILL.md
- name:
- benchmark
- description:
- 使用此技能测量性能基线，检测PR前后的回归，并比较堆栈替代方案。
- origin:
- ECC
基准测试 — 性能基线及回归检测
使用场景
- 在 PR 前后测量性能影响
- 为项目建立性能基线
- 用户反馈"感觉变慢"时
- 发布前确保达到性能目标
- 对比不同技术栈的性能表现
工作原理
模式 1：页面性能
通过浏览器 MCP 测量真实浏览器指标：
1. 导航至每个目标 URL
2. 测量核心网页指标：
- LCP（最大内容绘制）— 目标 < 2.5 秒
- CLS（累积布局偏移）— 目标 < 0.1
- INP（与下一次绘制的交互）— 目标 < 200 毫秒
- FCP（首次内容绘制）— 目标 < 1.8 秒
- TTFB（首字节时间）— 目标 < 800 毫秒
3. 测量资源大小：
- 页面总重量（目标 < 1MB）
- JS 包大小（目标 < 200KB gzip 压缩后）
- CSS 大小
- 图片重量
- 第三方脚本重量
4. 统计网络请求数量
5. 检查阻塞渲染的资源
模式 2：API 性能
对 API 端点进行基准测试：
1. 每个端点请求 100 次
2. 测量：p50、p95、p99 延迟
3. 追踪：响应大小、状态码
4. 负载测试：10 个并发请求
5. 与 SLA 目标进行对比
模式 3：构建性能
测量开发反馈循环效率：
1. 冷构建时间
2. 热重载时间 (HMR)
3. 测试套件执行时间
4. TypeScript 检查时间
5. 代码检查时间
6. Docker 构建时间
模式 4：前后对比
在变更前后运行以测量影响：
/benchmark baseline # 保存当前指标
# ... 进行更改 ...
/benchmark compare # 与基线进行比较
输出结果：
| Metric | Before | After | Delta | Verdict |
|--------|--------|-------|-------|---------|
| LCP | 1.2s | 1.4s | +200ms | WARNING: WARN |
| Bundle | 180KB | 175KB | -5KB | ✓ BETTER |
| Build | 12s | 14s | +2s | WARNING: WARN |
输出
将基线数据以 JSON 格式存储在 .ecc/benchmarks/ 中。通过 Git 追踪，便于团队共享基线。
集成
- CI：在每个 PR 上运行
/benchmark compare - 配合
/canary-watch进行部署后监控 - 配合
/browser-qa完成发布前完整检查清单
Related Skills
affaan-m/unified-memory
development
VerifiedTrustedCommunity
Share durable, inspectable context and handoffs between Claude, Codex, Hermes, Cursor, OpenCode, and other agents through the local ECC Memory Vault. Use when an agent must save work state, transfer context, resume another agent's task, or search shared project knowledge.
234,238SKILL.mdUpdated Jul 28, 2026
affaan-m/contract-first
development
VerifiedTrustedCommunity
Use when multiple consumers and providers must evolve an API or event schema without field drift, integration surprises, or one side silently redefining the interface.
234,238SKILL.mdUpdated Jul 28, 2026
affaan-m/ito-compute
tools
VerifiedTrustedCommunity
Query live GPU inventory, submit an authenticated Itô fixed-rate RFQ, inspect RFQ or procurement status, and run explicitly gated node qualification through the separately installed canonical CLI. Use when a user asks to find H100/H200 capacity, request a fixed compute rate, check Itô compute status, or validate GPU nodes.
234,238SKILL.mdUpdated Jul 24, 2026
affaan-m/continuous-learning-v2
data-ai
VerifiedTrustedCommunity
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
234,238SKILL.mdUpdated Mar 27, 2026