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Pdlc perf

Skill kanfu-panda/pdlc-skills/skills/pdlc-perf

36 slash commands that turn Claude Code into a real PDLC workflow — PRD → TDD → implement → review → ship. Hard contracts force AI to persist artifacts, write failing tests first, and run self-checks. No more "looks done" in chat.

Install
npx -y skills add kanfu-panda/pdlc-skills --skill pdlc-perf

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 9 stars9 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

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性能优化

SKILL.md

2.4 KB, as published. Nobody here has run it

性能优化

<!-- @include templates/prompts/iron-law.md -->

对指定服务或应用进行性能分析并提出优化方案。

分析维度

后端性能

  • 数据库层: 慢查询、N+1 问题、缺失索引、全表扫描
  • 缓存层: 缓存命中率、缓存策略(过期/淘汰)、缓存穿透/击穿/雪崩
  • 接口层: 响应时间、并发处理、连接池配置
  • 代码层: 算法复杂度、内存泄漏、不必要的序列化/反序列化

前端性能

  • 加载性能: 首屏时间、资源体积、代码分割、懒加载
  • 运行时性能: 不必要的重渲染、大列表虚拟滚动、防抖/节流
  • 网络优化: 请求合并、资源压缩、CDN 配置
  • 缓存策略: 浏览器缓存、Service Worker、本地存储

工作流程

  1. 阅读代码: 分析目标服务/应用的核心逻辑
  2. 识别瓶颈: 标注可能存在性能问题的代码段
  3. 提出方案: 对每个问题给出优化方案和预期收益
  4. 实施优化: 按优先级实施优化代码
  5. 【必须创建文件】docs/07_reviews/code/ 下创建性能优化报告

⚠️ 必须创建文件,不可仅在对话中输出。

报告格式

文件名: YYYYMMDD-<服务名>-perf-report.md

文档顶部包含 PDLC 追溯头

<!-- PDLC-TRACE -->
<!-- 功能名称: <服务名> -->
<!-- 阶段: 性能优化 -->
<!-- 创建时间: <ISO 8601> -->

报告内容

序号位置问题描述影响程度优化方案预期收益

创建后验证:确认文件已存在于 docs/07_reviews/code/ 目录

要求

<!-- @include templates/prompts/output-language.md -->
  • 优化方案按投入产出比排序(性价比高的优先)
  • 给出优化前后的代码对比
  • 不要为了优化而牺牲代码可读性

优化目标: $ARGUMENTS

<!-- @include templates/prompts/handoff.md -->

本命令的 handoff 输出:

✅ 性能优化报告 完成
📦 产出:docs/04_testing/perf/<feature-id>-report.md
👉 下一步:(本次流程结束,无后续)

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.