[{"data":1,"prerenderedAt":93},["ShallowReactive",2],{"header-counts":3,"footer-counts":6,"prompt-performance-optimization":9},{"tools":4,"reviews":5},65,7,{"tools":4,"reviews":5,"playbooks":7,"news":8},10,8,{"id":10,"title":11,"body":12,"description":76,"extension":77,"meta":78,"navigation":79,"path":80,"seo":81,"stem":82,"tags":83,"targetTools":87,"__hash__":92},"prompts\u002Fprompts\u002Fperformance-optimization.md","性能优化 Prompt：让 AI 像性能工程师一样定位瓶颈",{"type":13,"value":14,"toc":69},"minimark",[15,19,23,27,38,41,44],[16,17,18],"h2",{"id":18},"用法",[20,21,22],"p",{},"把需要优化的代码粘进来。说明当前性能指标（耗时、内存）和目标。",[16,24,26],{"id":25},"prompt","Prompt",[28,29,35],"pre",{"className":30,"code":32,"language":33,"meta":34},[31],"language-text","你是一个性能优化专家。请分析以下代码的性能问题，并给出优化方案。\n\n## 代码\n\n{{粘贴代码}}\n\n## 当前表现\n\n- 输入规模：{{比如 10 万条数据}}\n- 耗时：{{比如 15 秒}}\n- 内存：{{比如 2GB}}\n- 目标：{{比如 1 秒内完成}}\n\n## 分析要求\n\n1. **复杂度分析**\n   - 时间复杂度（大 O 表示）\n   - 空间复杂度\n   - 瓶颈在哪里（哪一行\u002F哪个循环）\n\n2. **优化方案**\n   - 按优先级排序（收益最大的排前面）\n   - 每个方案说明预期效果（时间\u002F空间）\n   - 给出优化后的完整代码\n\n3. **权衡说明**\n   - 优化后是否有 trade-off（可读性、内存换时间等）\n   - 是否需要额外依赖\n\n## 输出格式\n\n### 复杂度分析\n- 当前：O(???)\n- 瓶颈：第 X 行的 YYY 循环\n\n### 优化方案\n\n#### 方案 1：{{方案名}}（推荐）\n- 预期效果：耗时从 15s → 0.8s\n- 原理：...\n- 代码：\n```{{语言}}\n\u002F\u002F 优化后的代码\n```\n\n#### 方案 2：{{方案名}}（备选）\n- ...\n\n### Before \u002F After 对比\n| 指标 | 优化前 | 优化后 | 提升 |\n|---|---|---|---|\n\n### 注意事项\n- 优化后需要更新的测试\n- 需要注意的 edge case\n","text","",[36,37,32],"code",{"__ignoreMap":34},[16,39,40],{"id":40},"常见优化模式",[20,42,43],{},"AI 会检查以下常见性能问题：",[45,46,47,51,54,57,60,63,66],"ul",{},[48,49,50],"li",{},"O(n²) 循环 → 哈希表降为 O(n)",[48,52,53],{},"N+1 查询 → JOIN 或批量查询",[48,55,56],{},"递归无记忆化 → 加 memo\u002Fcache",[48,58,59],{},"不必要的全量加载 → 分页\u002F懒加载",[48,61,62],{},"字符串拼接 → 用 StringBuilder \u002F join",[48,64,65],{},"重复计算 → 预计算 + 缓存",[48,67,68],{},"同步阻塞 → 异步\u002F并发",{"title":34,"searchDepth":70,"depth":70,"links":71},3,[72,74,75],{"id":18,"depth":73,"text":18},2,{"id":25,"depth":73,"text":26},{"id":40,"depth":73,"text":40},"把慢代码或慢查询粘进来，AI 分析时间复杂度、空间复杂度、瓶颈点，给出优化方案和优化后的代码，附 before\u002Fafter 对比。","md",{},true,"\u002Fprompts\u002Fperformance-optimization",{"title":11,"description":76},"prompts\u002Fperformance-optimization",[84,85,86],"性能","优化","复杂度分析",[88,89,90,91],"Claude","Cursor","ChatGPT","GLM","rP4jQ8RWR512gmYpyeGk8P34xWajAzaQUTqVg2j5VxU",1782316489339]