性能优化最佳实践

用Claude Code开发时,性能直接影响效率。响应慢让人心烦,优化后的工作流能让速度快2-5倍。下面聊聊怎么榨干Claude Code的性能。

为什么要优化性能

实际体验差异

响应时间的影响:

小于2秒: 顺手,不中断思路
2-5秒: 还行,偶尔走神
5秒: 烦人,效率降一半

钱的问题:

API按token收费,废话多就烧钱
等待的时间也是成本
重复操作浪费资源

实际对比

优化前:

重构一个React组件
├─ 读取5个文件 (20秒)
├─ 理解依赖 (15秒)
├─ 生成代码 (25秒)
├─ 修复错误 (18秒)
└─ 总计: 78秒,被打断好几次

优化后:

重构同一个组件
├─ 精确读取相关文件 (8秒)
├─ 一次性完成 (12秒)
└─ 总计: 20秒,思路连贯

省了74%的时间

加快响应速度

1. 请求要说清楚

别说模糊的话

不好的例子:

你: 帮我看看这个组件

Claude: 好的,让我先读取这个文件...
[读取了整个文件,2000行]
Claude: 这是一个大型组件,你想要我做什么呢?

你: 优化一下性能

Claude: 好的,让我分析性能问题...
[花很长时间分析整个组件]

好的例子:

你: 优化UserProfile组件性能:
1. 用React.memo包装
2. searchValue状态提到父组件
3. useMemo缓存计算结果
只改src/components/UserProfile.tsx

Claude: 明白了,针对性地优化这三点...
[直接执行]

使用明确的上下文限定

优化前:

你: 修复所有的类型错误
Claude: [扫描整个项目,分析所有文件]

优化后:

你: 修复src/api/users.ts中的类型错误
Claude: [只读取这一个文件]

性能提升: 3-5倍

2. 批量操作优化

合并相关请求

低效方式:

你: 创建Button组件
Claude: [创建Button.tsx] (10秒)

你: 添加类型定义
Claude: [添加Button.types.ts] (8秒)

你: 添加样式文件
Claude: [添加Button.module.css] (7秒)

你: 创建index导出文件
Claude: [创建index.ts] (6秒)
总计: 31秒,4次等待

高效方式:

你: 创建完整的Button组件套件,包括:
1. Button.tsx主组件
2. Button.types.ts类型定义
3. Button.module.css样式文件
4. index.ts导出文件

Claude: [一次性创建所有文件] (15秒)
总计: 15秒,1次等待

性能提升: 52%

批量文件操作

## 批量操作模板

### 批量读取
不要分多次读取文件:
❌ 你: "读取utils.ts"
❌ 你: "读取helpers.ts"
❌ 你: "读取constants.ts"

✅ 你: "同时读取这三个文件: utils.ts, helpers.ts, constants.ts"

### 批量修改
不要分多次修改相关文件:
❌ 你: "修改API配置"
❌ 你: "更新类型定义"
❌ 你: "修改调用处"

✅ 你: "重构API调用:
1. 更新src/config/api.ts的配置
2. 修改src/types/api.ts的类型
3. 更新所有使用该API的组件"

3. 利用工具的并发能力

Claude Code可以并行执行多个独立的工具调用,大幅提升效率。

并行读取文件

串行读取(慢):

Claude: [读取file1.ts]
Claude: [读取file2.ts]
Claude: [读取file3.ts]
时间: 3 + 3 + 3 = 9秒

并行读取(快):

Claude: [同时读取file1.ts, file2.ts, file3.ts]
时间: max(3, 3, 3) = 3秒

如何触发并行操作:

你: 分析以下文件的依赖关系:
- src/App.tsx
- src/components/Header.tsx
- src/components/Sidebar.tsx
- src/utils/auth.ts

Claude会在单次响应中并行读取所有文件

并行执行命令

串行执行:

你: 运行测试
[等待测试完成]

你: 运行lint
[等待lint完成]

你: 运行类型检查
[等待类型检查完成]

并行执行:

你: 同时运行以下检查:
1. npm test
2. npm run lint
3. npm run type-check

Claude会并行执行这些命令

实战示例:批量代码审查

## 并行代码审查请求模板

你: 审查以下文件的代码质量:
- src/components/UserCard.tsx
- src/components/UserList.tsx
- src/hooks/useUsers.ts
- src/api/users.ts

检查项:
1. TypeScript类型安全
2. 性能问题(不必要的重渲染)
3. 错误处理
4. 代码规范

Claude会:
1. 并行读取所有4个文件
2. 同时分析每个文件
3. 生成综合报告

时间节省: 从12秒降至4秒

减少等待时间

1. 智能使用CLAUDE.md

通过CLAUDE.md预设上下文,避免重复解释:

无CLAUDE.md时:

你: 创建一个API路由
Claude: 好的,什么类型的项目?
你: Node.js + Express
Claude: 使用什么数据库?
你: PostgreSQL + Prisma
Claude: 有编码规范吗?
你: 有的,用TypeScript,严格模式...
[多轮对话后才达成共识]

有CLAUDE.md后:

你: 创建一个用户API路由
Claude: [直接按照CLAUDE.md中的规范创建]
[一次到位,完全符合项目规范]

配置示例:

## Performance Optimization in CLAUDE.md

# Project Setup
## Technology Stack
- Framework: Express + TypeScript
- Database: PostgreSQL + Prisma
- Validation: Zod
- Testing: Jest

## API Route Pattern
When creating API routes:
```typescript
// src/routes/users.ts
import { Router } from 'express';
import { userController } from '@/controllers/userController';
import { validateRequest } from '@/middlewares/validateRequest';
import { userCreateSchema } from '@/validators/userSchemas';

const router = Router();

router.post('/users',
  validateRequest(userCreateSchema),
  userController.create
);

export { router };

Controller Pattern

// src/controllers/userController.ts
export const userController = {
  async create(req: Request, res: Response, next: NextFunction) {
    try {
      const data = UserCreateSchema.parse(req.body);
      const user = await userService.create(data);
      res.status(201).json({ success: true, data: user });
    } catch (error) {
      next(error);
    }
  }
};

### 2. 使用快捷命令和别名

#### 定义常用操作别名

在CLAUDE.md中定义快捷命令:

```markdown
## Command Aliases

### Testing
When I say "test now", run: `npm run test:watch`
When I say "full test", run: `npm test && npm run test:e2e`
When I say "coverage", run: `npm run test:coverage`

### Development
When I say "dev", run: `npm run dev`
When I say "build dev", run: `npm run build:dev`
When I say "build prod", run: `npm run build:prod`

### Code Quality
When I say "check all", run: `npm run lint && npm run type-check`
When I say "fix code", run: `npm run lint -- --fix && npm run format`

### Git
When I say "quick commit", ask for commit message then:
  1. git add .
  2. git commit -m "[message]"
  3. git push

When I say "status check", run: `git status && git log -1 --stat`

使用效果:

你: check all
Claude: [运行npm run lint和npm run type-check]
节省时间: 不用每次输入完整命令

创建任务模板

## Task Templates

### New Feature Template
When I ask to "create a feature [name]", follow these steps:
Ask for feature details if unclear
Create feature branch: `git checkout -b feature/[name]`
Create necessary files (component, hooks, types, styles)
Implement functionality
Add tests (min 80% coverage)
Run: `npm run check all`
Ask if I want to commit changes

### Bug Fix Template
When I ask to "fix bug [description]", follow these steps:
Ask for reproduction steps if unclear
Create minimal test case
Locate and fix the bug
Add regression test
Verify all tests pass
Ask if I want to commit changes

3. 上下文预热技巧

项目启动时预热

## Session Start Warmup

When starting a new session:
1. Quick project scan:
   - Read package.json for dependencies
   - Read tsconfig.json for TypeScript config
   - List project structure (ls -la)

2. Load key files:
   - CLAUDE.md
   - Main config files
   - Recent commits (git log -5)

This takes 5 seconds but saves 30+ seconds per session

实际使用:

你: /warmup
Claude: [执行预设的预热流程]
你: 现在可以快速处理任何请求了

智能缓存策略

## Caching Strategy

### Cache These in Memory
- Project structure (directory tree)
- Package.json dependencies
- Common file locations
- Coding conventions

### Invalidate Cache When
- package.json changes
- Project structure changes
- New dependencies added

上下文优化

1. 精简上下文内容

只包含必要信息

过度冗余的CLAUDE.md:

## Project Overview
This project is an e-commerce platform... [500字介绍]

## Technology Stack
We use React because it's... [300字解释]

## Architecture
Our architecture follows... [400字详细说明]

## Coding Conventions
Here are detailed explanations of every rule... [1000字]

总计: 2200字,每次请求都传输

精简高效的CLAUDE.md:

## Project
E-commerce platform (React + Next.js)

## Tech Stack
- Next.js 14, React 18, TypeScript
- Prisma + PostgreSQL
- Tailwind CSS

## Quick Rules
- Functional components only
- Use Server Components by default
- All functions need return types
- No any types

总计: 50字,信息密度高

性能影响:

冗余版本: 每次请求消耗额外2000 tokens
精简版本: 只消耗50 tokens
节省: 97.5%的上下文开销

使用引用而非复制

不好:直接复制文档

## API Documentation

Here is the complete API documentation... [复制整个API文档,5000字]

好:使用引用

## API Documentation
See: `/docs/api.md` or `http://localhost:3000/api-docs`

Key endpoints:
- POST /api/users - Create user
- GET /api/users/:id - Get user
- PUT /api/users/:id - Update user

2. 分层上下文管理

环境特定配置

## Environment-Aware Context

### Development Mode
Additional context loaded:
- Mock data locations
- Debugging tools
- Hot reload config

### Production Mode
Stripped context:
- Only production configs
- Security requirements
- Performance guidelines

### Context Loading Rules
if (NODE_ENV === 'development') {
  load('development-rules.md');
  load('debugging-tools.md');
} else if (NODE_ENV === 'production') {
  load('production-checklist.md');
  load('security-requirements.md');
}

动态上下文加载

## Dynamic Context Loading

### Task-Based Context
When working on authentication:
→ Load auth-related configs and rules
→ Exclude UI styling rules

When working on UI components:
→ Load styling guidelines
→ Exclude backend API rules

### Implementation
You can signal context needs:
"Focus on: authentication"
→ Claude loads auth-specific context

"Focus on: UI components"
→ Claude loads styling context

3. 上下文窗口优化

Token使用策略

## Token Budget Management

### Budget Allocation (Total: 200K tokens)
- CLAUDE.md: 2,000 tokens (1%)
- Current task context: 10,000 tokens (5%)
- File contents: 50,000 tokens (25%)
- Claude's response: 30,000 tokens (15%)
- Reserved for expansion: 108,000 tokens (54%)

### Optimization Rules
1. CLAUDE.md should be < 3,000 tokens
2. Avoid reading large files (>1000 lines) unless necessary
3. Use grep to search instead of reading entire files
4. Prioritize relevant files over comprehensive scans

### Token-Saving Techniques
❌ "Read all React components"
✅ "Read components related to user authentication"

❌ "Analyze the entire codebase"
✅ "Analyze src/api and src/controllers directories"

大文件处理策略

## Large File Handling

### For Files > 500 Lines
Instead of:
❌ Read the entire file

Use:
✅ Grep for specific patterns
✅ Read specific sections (with line numbers)
✅ Ask Claude to summarize first

### Example
Instead of:
"Read src/components/Dashboard.tsx" [1200 lines]

Use:
"Search for 'useEffect' in Dashboard.tsx and read surrounding context"
or
"Read lines 1-100 of Dashboard.tsx to understand the structure"
or
"Summarize the Dashboard component's main responsibilities"

并发操作

1. 多任务并行处理

并行文件读取模式

理论基础: Claude Code可以在单次响应中并行调用多个工具。理解这一点是性能优化的关键。

示例:跨文件引用分析

你: 分析AuthService在哪些文件中被使用
Claude:
[并行执行]
- Grep: "AuthService" in src/
- Read: src/services/AuthService.ts
- Read: src/services/index.ts

[综合分析后报告]
Found in 12 files:
- src/components/LoginForm.tsx (imports)
- src/middleware/auth.ts (uses)
...

性能对比:

串行方式: 3 + 3 + 3 = 9秒
并行方式: max(3, 3, 3) = 3秒
节省: 67%时间

批量代码生成

## Parallel Code Generation Template

### Scenario: Create CRUD for a Resource
Instead of:
❌ "Create User model"
❌ "Create User controller"
❌ "Create User routes"
❌ "Create User validators"

Use:
✅ "Create complete CRUD for User resource:
1. Prisma schema model
2. Controller with create/read/update/delete
3. Express routes with validation
4. Zod validation schemas
5. TypeScript types
6. Unit tests"

Claude will:
1. Read related files in parallel (schema, existing controllers)
2. Generate all files
3. Ensure consistency across files

Time: One request instead of 6

2. 独立任务并发

测试+构建并行

你: 准备发布前的完整检查
Claude:
[并行执行]
1. npm test
2. npm run lint
3. npm run type-check
4. npm run build
5. git status

[汇总所有结果]

为什么更快?

这些任务相互独立
并行执行 = 总时间 = max(各任务时间)
串行执行 = 总时间 = sum(各任务时间)

实际时间对比:

串行: 30s + 15s + 20s + 45s + 2s = 112秒
并行: max(30s, 15s, 20s, 45s, 2s) = 45秒
节省: 60%

代码审查+文档生成

## Concurrent Review and Documentation

Request:
"Review src/api/users.ts and generate usage documentation"

Claude will:
1. Read the API file
2. Analyze code quality
3. Find usage examples in codebase
4. Generate README documentation

All done in parallel where possible

3. 流水线优化

智能任务依赖管理

## Pipeline Optimization

### Independent Tasks → Parallel
✅ Run tests + Lint + Type-check (no dependencies)
✅ Read multiple files (no dependencies)
✅ Search multiple patterns (no dependencies)

### Dependent Tasks → Sequential
⚠️ Build then Test (need build artifacts)
⚠️ Migrate then Seed (need schema changes)
⚠️ Generate then Commit (need files created)

### Mixed Pipeline
Example workflow:
1. Parallel: Read all config files
2. Sequential: Analyze dependencies (needs config)
3. Parallel: Generate all components
4. Sequential: Create index.ts (needs components)
5. Parallel: Run tests + lint
6. Sequential: Commit (needs all changes)

Optimized: 45s vs Sequential: 90s

实战:完整功能开发流水线

## Complete Feature Pipeline

### Request
"Create user profile feature with:
- Profile viewing
- Profile editing
- Avatar upload
- Include tests and documentation"

### Optimized Execution
Phase 1 (Parallel):
  - Read existing user routes
  - Read upload configuration
  - Read database schema

Phase 2 (Sequential):
  - Design API endpoints
  - Plan component structure

Phase 3 (Parallel):
  - Create API routes
  - Create React components
  - Create validation schemas

Phase 4 (Parallel):
  - Write API tests
  - Write component tests

Phase 5 (Parallel):
  - Generate documentation
  - Run full test suite

### Time Breakdown
Phase 1: 3s (parallel reads)
Phase 2: 5s (planning)
Phase 3: 12s (parallel generation)
Phase 4: 15s (parallel testing)
Phase 5: 8s (docs + tests)
Total: 43s

### Sequential Alternative
3 + 5 + 12 + 15 + 8 + (overhead) = 60s+

Savings: 28%

缓存利用

1. 文件系统缓存

理解缓存机制

Claude Code会缓存读取的文件内容,避免重复读取:

第一次读取:

你: 读取package.json
Claude: [从磁盘读取,耗时1秒]

后续读取:

你: 再次读取package.json
Claude: [从缓存读取,几乎瞬时]

利用缓存的策略

## Cache Utilization Strategy

### Batch File Reads
❌ Bad: Spread reads across multiple requests
Request 1: "Read file A"
Request 2: "Read file B"
Request 3: "Read file C"

✅ Good: Read all files in one request
Request 1: "Read files A, B, and C"

Benefit:
- All files cached in one operation
- Subsequent requests use cache
- Faster overall

### Working Set Strategy
Identify your "working set" - files you frequently work with

Example: Frontend Developer
Working Set:
- src/components/ (all components)
- src/hooks/ (custom hooks)
- src/types/ (type definitions)

Strategy: Read entire working set once at start of session
"Read all TypeScript files in src/components and src/hooks"
→ All files cached
→ Subsequent operations are instant

2. 模式匹配缓存

智能搜索策略

## Pattern Matching Cache

### Grep Results Are Cached
First search:
"Grep for 'useState' in src/components/"
→ Scans all files, results cached

Second search:
"Grep for 'useState' in src/components/"
→ Returns cached results instantly

### Strategy: Broad Searches First
❌ Bad: Narrow searches, then broad
"Grep for 'useState' in components/Button.tsx"
"Grep for 'useState' in components/Input.tsx"
"Grep for 'useState' in components/Form.tsx"

✅ Good: Broad search once
"Grep for 'useState' in src/components/"
→ Results cached
→ Filter mentally or ask Claude to filter

### Example Workflow
You: "Find all components using Redux"
Claude: [Grep entire src/, results cached]

You: "Which of these use useSelector?"
Claude: [Filters cached results]
→ Instant response, no re-scan

3. 项目级缓存策略

初始化缓存

## Session Initialization

### Warmup Strategy
Start each session with cache warmup:

"Warmup: Read and cache these directories:
1. src/config/ - all configuration files
2. src/types/ - all type definitions
3. CLAUDE.md - project context
4. package.json - dependencies"

Time: 5 seconds
Benefit: All subsequent operations are faster

### Progressive Loading
Don't load everything at once

Phase 1 (Session Start):
- Load project structure
- Load CLAUDE.md
- Load config files

Phase 2 (When Needed):
- Load component files (when working on UI)
- Load API files (when working on backend)

Benefit:
- Fast session start
- Still cache relevant files
- Avoid unnecessary loading

缓存失效处理

## Cache Invalidation

### Automatic Invalidation
Claude automatically invalidates cache when:
- Files are modified (via Edit tool)
- New files are created
- Files are deleted

### Manual Refresh
If you modify files outside Claude:
"Refresh: package.json has been updated"
→ Claude reloads file
→ Cache updated

### Working with External Tools
When using other editors (VS Code, etc.):

Before asking Claude to analyze:
1. Save changes in external editor
2. Tell Claude: "I've updated X file externally, please reload"
3. Claude refreshes cache
4. Proceed with analysis

4. 会话状态缓存

对话历史利用

## Conversation Context Caching

### Claude Remembers Within Session
First occurrence:
You: "We use TypeScript strict mode"
Claude: [Noted for this session]

Later in same session:
You: "Create a new component"
Claude: [Creates with strict mode compliance]
→ No need to repeat instructions

### Establish Patterns Early
At start of session:
"Session setup:
- We're working on authentication feature
- Focus on security and error handling
- Use TypeScript strict mode
- All functions need return types"

Benefit: Subsequent requests follow these patterns automatically

### Reset When Needed
If switching contexts:
"Reset: Now working on UI styling, different from auth feature"
→ Claude adjusts expectations
→ Previous patterns don't interfere

性能监控

1. 响应时间追踪

建立性能基线

## Performance Baseline

### Measure Your Operations
Track these metrics:

1. File Read Operations
   - Small file (<100 lines): should be <2s
   - Medium file (100-500 lines): should be <3s
   - Large file (>500 lines): should be <5s

2. Code Generation
   - Simple component: <5s
   - Complex feature: <15s
   - Multi-file refactor: <30s

3. Analysis Tasks
   - Single file analysis: <5s
   - Multi-file analysis: <10s
   - Codebase search: <8s

### Tracking Template
Maintain a performance log:

| Operation | Expected | Actual | Notes |
|-----------|----------|--------|-------|
| Read component | 2s | 1.5s | ✓ Good |
| Generate feature | 15s | 25s | ✗ Slow, investigate |
| Search codebase | 8s | 20s | ✗ Large project, narrow scope |

识别性能瓶颈

## Bottleneck Identification

### Common Bottlenecks

1. **Excessive Context**
   Symptom: Requests take >10s for simple tasks
   Cause: CLAUDE.md too large or reading unnecessary files
   Solution: Simplify CLAUDE.md, be specific about files to read

2. **Vague Requests**
   Symptom: Claude asks many clarifying questions
   Cause: Request lacks specificity
   Solution: Provide detailed requirements upfront

3. **Large File Scans**
   Symptom: Reading large files takes >10s
   Cause: Reading entire file when only need part
   Solution: Use grep or specify line ranges

4. **Sequential Operations**
   Symptom: Total time is sum of all operations
   Cause: Not leveraging parallel execution
   Solution: Combine related requests

### Diagnosis Checklist
If performance is slow:
- [ ] Is CLAUDE.md concise (<2000 tokens)?
- [ ] Are requests specific and detailed?
- [ ] Am I reading only necessary files?
- [ ] Can operations be done in parallel?
- [ ] Am I repeating information Claude already knows?

2. Token使用监控

追踪Token消耗

## Token Usage Tracking

### Why Monitor Tokens?
- Cost efficiency (API calls are paid)
- Context window limits
- Performance indicator

### Token Budget by Task Type

1. **Simple Questions** (<500 tokens)
   - "What does this function do?"
   - "How do I use this component?"

2. **Code Analysis** (500-2000 tokens)
   - "Review this file for bugs"
   - "Explain this code structure"

3. **Code Generation** (2000-5000 tokens)
   - "Create a new feature"
   - "Refactor this component"

4. **Large Refactors** (5000-10000 tokens)
   - "Update entire codebase to new pattern"
   - "Migrate to new framework"

### Monitoring Strategy
After each complex operation:
"Show me token usage for last operation"
→ Claude reports tokens used
→ Track patterns over time

### Optimization Targets
- Simple tasks: <1000 tokens
- Medium tasks: <3000 tokens
- Complex tasks: <8000 tokens
- If consistently over: Optimize CLAUDE.md or request structure

Token优化技术

## Token Optimization Techniques

### 1. Precise File Selection
❌ "Read all components in src/components/"
(10 files × 500 tokens = 5000 tokens)

✅ "Read UserCard and UserList components"
(2 files × 500 tokens = 1000 tokens)
Savings: 80%

### 2. Grep Over Read
❌ "Find all API calls" [Reads entire codebase]
(50,000+ tokens)

✅ "Grep for 'fetch(' in src/"
(~500 tokens for results)
Savings: 99%

### 3. Incremental Context
❌ Repeat entire project context every request
(2000 tokens per request)

✅ Reference established context
"I'm still working on the auth feature we discussed"
(~100 tokens)
Savings: 95%

### 4. Focused Requests
❌ "Analyze everything about this component"
(6000 tokens for deep analysis)

✅ "Check for TypeScript errors in this component"
(1000 tokens for focused analysis)
Savings: 83%

3. 效率指标

定义成功指标

## Efficiency Metrics

### Key Performance Indicators (KPIs)

1. **First-Time Success Rate**
   Target: >80%
   Meaning: Percentage of tasks completed correctly on first try
   How to improve: Better CLAUDE.md, more specific requests

2. **Average Response Time**
   Target: <5s for simple tasks
   Target: <15s for medium tasks
   How to improve: Optimize context, use parallel operations

3. **Token Efficiency**
   Target: <2000 tokens per simple task
   Target: <5000 tokens per complex task
   How to improve: Precise file selection, focused requests

4. **Rework Rate**
   Target: <20%
   Meaning: Percentage of tasks requiring revision
   How to improve: Clear requirements, better examples

### Measuring Success
Weekly review:
- This week I completed 50 tasks with Claude
- First-time success: 42/50 (84%) ✓
- Avg response time: 4.2s ✓
- Avg tokens per task: 1800 ✓
- Rework needed: 8/50 (16%) ✓
Overall: Excellent performance

持续改进

## Continuous Improvement

### Performance Review Template

#### Weekly Review
**Tasks Completed:** [number]
**Avg Response Time:** [time]
**First-Time Success:** [percentage]
**Common Bottlenecks:**
1. [bottleneck 1]
2. [bottleneck 2]

**Improvement Actions:**
- [ ] Action to address bottleneck 1
- [ ] Action to address bottleneck 2

#### Monthly Review
**Trends:**
- Response time: Improving/Stable/Worsening
- Token usage: Decreasing/Stable/Increasing
- Success rate: Improving/Stable/Worsening

**Actions Taken:**
- [x] Updated CLAUDE.md (date)
- [x] Optimized request patterns (date)
- [x] Added command aliases (date)

**Next Month's Focus:**
1. [Priority 1]
2. [Priority 2]

实用技巧和最佳实践

1. 请求优化清单

发送请求前的检查

## Pre-Request Checklist

Before sending a request to Claude:

### Context Preparation
- [ ] Have I established the context? (Is this a new topic?)
- [ ] Is the context in CLAUDE.md or should I provide it?
- [ ] Can I reference previous work instead of repeating?

### Request Clarity
- [ ] Is my request specific and detailed?
- [ ] Have I provided examples of expected output?
- [ ] Have I specified constraints (files to include/exclude)?

### Optimization Opportunities
- [ ] Can I combine multiple related requests?
- [ ] Can operations be done in parallel?
- [ ] Am I reading only necessary files?

### Token Efficiency
- [ ] Is CLAUDE.md concise and relevant?
- [ ] Am I avoiding redundant information?
- [ ] Can I use grep instead of reading large files?

### Quality Assurance
- [ ] Have I specified the expected format?
- [ ] Have I mentioned relevant coding standards?
- [ ] Have I provided necessary file paths?

### Expected Results
After checking all items:
- Faster responses (30-50% improvement)
- Higher first-time success rate (80%+)
- Lower token usage (40-60% reduction)

请求模板库

## Request Templates

### Template 1: Code Generation

Create [feature/component/function] with these requirements:

Purpose: [What it should do] Location: [File path] Tech Stack: [Relevant technologies] Specifications:

[Requirement 1]
[Requirement 2]
[Requirement 3]

Constraints:

[Constraint 1]
[Constraint 2]

Expected Output:

[Output format/structure]

Follow project coding conventions in CLAUDE.md.


### Template 2: Bug Investigation

Investigate this issue: Symptom: [What's happening] Expected: [What should happen] Location: [Where it occurs] Steps to Reproduce:

[Step 1]
[Step 2]
[Step 3]

Context:

Related files: [list]
Recent changes: [description]

Please:

Identify the root cause
Propose a fix
Suggest regression tests


### Template 3: Refactoring

Refactor [component/module]: Current Issues:

[Issue 1]
[Issue 2]

Goals:

[Goal 1]
[Goal 2]

Files to Modify:

[File 1]
[File 2]

Constraints:

Maintain backward compatibility
Don't break existing tests
Follow project conventions

Please analyze, plan, and implement the refactoring.


### Template 4: Code Review

Review [file/component] for:

TypeScript type safety
Performance issues
Security vulnerabilities
Code convention compliance
Error handling

Context:

Purpose: [What it does]
Dependencies: [What it uses]

Please provide:

List of issues found
Severity levels (Critical/High/Medium/Low)
Specific recommendations
Code examples for fixes

2. 高级工作流

迭代开发模式

## Iterative Development Workflow

### Phase 1: Planning (Quick)
You: "Help me plan user authentication feature:
- Login with email/password
- JWT tokens
- Password reset
- Session management"

Claude: [Analyzes requirements, creates task list]
→ Output: Structured plan with steps
→ Time: 10-15s

### Phase 2: Implementation (Parallel)
You: "Implement Phase 1: Login endpoint:
1. POST /api/auth/login
2. Validate email/password with Zod
3. Generate JWT
4. Return token + user info
Create:
- src/routes/auth.ts
- src/controllers/authController.ts
- src/validators/authSchemas.ts
- src/types/auth.ts"

Claude: [Creates all files in parallel]
→ Time: 15-20s

### Phase 3: Testing (Automated)
You: "Create tests for login endpoint:
- Unit tests for controller
- Integration tests for API
- Cover success and error cases"

Claude: [Generates comprehensive tests]
→ Time: 10-15s

### Phase 4: Verification (Quick)
You: "Run all tests and linting"
Claude: [Parallel execution]
→ Time: 5-10s

### Total Time: 40-60s for complete feature
### Traditional approach: 5-10 minutes
### Speed improvement: 5-10x

调试工作流

## Debugging Workflow

### Step 1: Isolate (2s)
You: "I have an error in user login. Error: 'Invalid credentials'
But I'm sure the password is correct.
Location: src/controllers/authController.ts line 25"

Claude: [Reads specific file and location]
→ Immediate context loaded

### Step 2: Reproduce (5s)
You: "Show me the login flow and where it might fail"

Claude: [Analyzes the flow]
→ Points out:
  - Password comparison logic
  - Database query
  - Error handling

### Step 3: Diagnose (3s)
You: "Check if password hashing is correct"

Claude: [Grep for password-related code]
→ Finds: Registration uses bcrypt(10)
→ Finds: Login uses bcrypt.compare()
→ Discovers: Comparison is async but not awaited

### Step 4: Fix (2s)
You: "Fix the issue"

Claude: [Adds await to bcrypt.compare()]
→ Fixed

### Step 5: Test (5s)
You: "Add regression test for this bug"

Claude: [Creates test case]
→ Prevents future recurrence

### Total Time: 17s
### Manual debugging: 5-15 minutes
### Speed improvement: 20-50x

3. 团队协作优化

共享性能实践

## Team Performance Optimization

### Shared CLAUDE.md Configuration

Create a team-standard CLAUDE.md template:

```markdown
# Team CLAUDE.md Standard

## Required Sections
1. Project Overview (max 100 words)
2. Technology Stack (list only)
3. Quick Rules (bullet points, 10 items max)
4. Common Commands (grouped by purpose)
5. File Structure (key directories only)

## Token Budget
- CLAUDE.md max: 2000 tokens
- Aim for 1000-1500 tokens typically

## Review Process
- Tech Lead reviews CLAUDE.md changes
- Update frequency: Monthly or after major changes
- Team vote on significant additions

Performance Standards

Establish team performance baselines:

File Operations:

Single file read: under 2s
Multi-file read (3-5 files): under 5s
Grep search: under 3s

Code Generation:

Simple component: under 5s
Complex feature: under 20s
Multi-file refactor: under 30s

Quality Targets:

First-time success: >80%
TypeScript errors: under 5% of generated code
Lint errors: under 5% of generated code

Team Training

Onboard new members with performance focus:

Week 1: Basics

How to write effective requests
CLAUDE.md overview
Common command aliases

Week 2: Optimization

Token efficiency
Parallel operations
Request templates

Week 3: Advanced

Complex workflows
Debugging strategies
Performance monitoring

Ongoing:

Monthly performance reviews
Share optimization tips
Maintain team request library

#### 知识共享

```markdown
## Knowledge Sharing System

### Request Library

Maintain a library of proven effective requests:

```markdown
## Team Request Library

### Authentication
Login endpoint creation:
[Copy proven request template]

Password reset flow:
[Copy proven request template]

### Frontend Components
Form component with validation:
[Copy proven request template]

Data table with sorting:
[Copy proven request template]

### Backend APIs
CRUD API generation:
[Copy proven request template]

Error handling middleware:
[Copy proven request template]

Performance Tips Log

Team members contribute tips:

From Sarah: "Use 'Focus on X' to limit context scope. Improved my response time by 40%."

From Mike: "Batch file reads at start of session. Saved me 10+ minutes per day."

From Lisa: "Always include expected output format. Reduced rework from 30% to 10%."

Team meeting agenda:

Performance metrics review
Success stories share
New techniques demo
Q&A and troubleshooting

### 4. 故障排除

#### 常见性能问题

```markdown
## Troubleshooting Performance Issues

### Problem 1: Slow Responses

**Symptoms:**
- Simple requests taking >10 seconds
- Claude seems "stuck" or "thinking" too long
- Intermittent slowness

**Diagnosis:**
1. Check CLAUDE.md size (target: <2000 tokens)
2. Review request clarity
3. Check if reading unnecessary files
4. Verify internet connection

**Solutions:**
- Trim CLAUDE.md to essentials
- Be more specific in requests
- Use grep instead of reading large files
- Combine related requests

### Problem 2: High Token Usage

**Symptoms:**
- Reaching context limits quickly
- High API costs
- Requests being truncated

**Diagnosis:**
1. Track token usage per request
2. Identify patterns of high usage
3. Check for redundant information

**Solutions:**
- Reduce CLAUDE.md size
- Read only necessary files
- Use grep for searching
- Reference established context
- Be selective about code examples

### Problem 3: Low First-Time Success

**Symptoms:**
- Frequent need for revisions
- Claude misunderstands requirements
- Generated code doesn't match expectations

**Diagnosis:**
1. Review request clarity
2. Check if context is complete
3. Verify expectations are communicated

**Solutions:**
- Provide detailed requirements upfront
- Include examples of expected output
- Specify constraints explicitly
- Reference CLAUDE.md conventions
- Use request templates

### Problem 4: Repetitive Explanations

**Symptoms:**
- Repeating same information across requests
- Claude forgetting context
- Inconsistent responses

**Diagnosis:**
1. Check if information is in CLAUDE.md
2. Review session context usage
3. Verify cache is being utilized

**Solutions:**
- Add recurring info to CLAUDE.md
- Reference previous discussions
- Use command aliases
- Establish session context early

性能恢复策略

## Performance Recovery

### When Performance Degrades

**Immediate Actions:**
1. Clear the air: "Let me reset context. We're working on [X]"
2. Simplify CLAUDE.md (temporarily)
3. Use more focused requests
4. Break large tasks into smaller ones

**Session Reset:**

"Session reset:

Clear previous context
Current focus: [specific task]
Relevant files: [list only what's needed]
Constraints: [key constraints only]"

**Starting Fresh:**
If performance is consistently poor:
1. End current session
2. Review and optimize CLAUDE.md
3. Start new session with clean context
4. Re-establish working set gradually

### Prevention Strategies

**Daily Practices:**
- Start session with context warmup
- Use request templates
- Monitor token usage
- Take breaks for long sessions

**Weekly Practices:**
- Review CLAUDE.md for bloat
- Clean up request templates
- Update performance metrics
- Share learnings with team

**Monthly Practices:**
- Major CLAUDE.md revision
- Performance baseline review
- Process optimization
- Team training updates

总结与行动指南

核心原则回顾

性能优化的五个核心原则:

精确性优先
- 明确的请求 > 模糊的请求
- 具体的文件范围 > 广泛的扫描
- 清晰的约束 > 开放的问题
并行思维
- 识别独立操作
- 批量文件读取
- 并行任务执行
上下文管理
- 精简CLAUDE.md
- 智能缓存利用
- 分层上下文加载
持续监控
- 追踪响应时间
- 监控token使用
- 测量成功率
迭代改进
- 建立性能基线
- 识别瓶颈
- 逐步优化

立即可行的优化

今天就可以做的(5分钟)

## Quick Wins (5 Minutes)

### 1. Trim CLAUDE.md
- Remove redundant explanations
- Use bullet points instead of paragraphs
- Keep only essential information
→ Expected: 30-50% token reduction

### 2. Create Request Template
Copy this template and save it:

Create [what] with these specs:

Purpose: [why]
Location: [where]
Tech: [stack]
Requirements: [list]
Constraints: [limits]

→ Expected: 40% faster request formulation

### 3. Set Up Performance Tracking
Create a simple log:

Date | Task | Time | Tokens | Success?

→ Expected: Identify improvement areas

### 4. Learn Command Aliases
Add to CLAUDE.md:

When I say "test", run: npm test When I say "check", run: npm run lint && npm run type-check

→ Expected: Save 10+ seconds per command

本周可以做的(30分钟)

## This Week (30 Minutes)

### Monday: CLAUDE.md Optimization (10 min)
- Review entire CLAUDE.md
- Remove outdated information
- Consolidate redundant sections
- Add missing critical info
- Measure token count (target: <2000)

### Tuesday: Request Patterns (10 min)
- Identify your 3 most common request types
- Create templates for each
- Test templates with actual tasks
- Refine based on results

### Wednesday: Batch Operations (10 min)
- Identify tasks you do sequentially
- Plan how to combine them
- Test parallel execution
- Measure time saved

### Thursday: Cache Strategy (10 min)
- Identify your working set files
- Create warmup routine
- Test cache effectiveness
- Adjust as needed

### Friday: Performance Review (10 min)
- Review week's performance log
- Identify top 3 bottlenecks
- Plan fixes for next week
- Celebrate improvements!

持续改进计划

## Continuous Improvement Plan

### Month 1: Foundation
**Goal:** Establish performance baselines

Week 1:
- Optimize CLAUDE.md
- Create request templates
- Set up tracking

Week 2:
- Learn parallel operations
- Implement batch workflows
- Measure improvements

Week 3:
- Optimize caching strategy
- Create command aliases
- Share with team

Week 4:
- Review metrics
- Identify patterns
- Plan Month 2

**Expected Results:**
- 40% faster responses
- 60% less token usage
- 80% first-time success rate

### Month 2: Advanced
**Goal:** Master advanced techniques

Focus areas:
- Complex workflow optimization
- Team collaboration
- Performance monitoring
- Advanced troubleshooting

### Month 3: Mastery
**Goal:** Team-wide optimization

Focus areas:
- Knowledge sharing
- Process documentation
- Team training
- Continuous optimization culture

性能目标清单

使用此清单跟踪你的优化进度:

## Performance Optimization Checklist

### CLAUDE.md Optimization
- [ ] Size < 2000 tokens
- [ ] Contains all critical info
- [ ] No redundant content
- [ ] Clear and concise
- [ ] Team-reviewed (if applicable)

### Request Quality
- [ ] Always provide clear requirements
- [ ] Specify expected output format
- [ ] Mention relevant constraints
- [ ] Include file paths when applicable
- [ ] Use request templates

### Parallel Operations
- [ ] Batch file reads
- [ ] Combine related requests
- [ ] Execute independent tasks in parallel
- [ ] Use concurrent tool calls
- [ ] Optimize task dependencies

### Context Management
- [ ] Working set identified
- [ ] Cache warmed up at session start
- [ ] Context refreshed when needed
- [ ] Unnecessary context excluded
- [ ] Session reset when switching topics

### Performance Monitoring
- [ ] Response time tracked
- [ ] Token usage monitored
- [ ] Success rate measured
- [ ] Bottlenecks identified
- [ ] Improvements documented

### Continuous Improvement
- [ ] Weekly performance reviews
- [ ] Monthly CLAUDE.md updates
- [ ] Regular optimization of workflows
- [ ] Team knowledge sharing
- [ ] Staying updated with best practices

最终建议

记住这些关键点:

优化是渐进的 - 不要试图一次优化所有东西
测量是关键 - 无法测量的东西就无法改进
模式很重要 - 识别并重用高效的工作模式
共享倍增价值 - 与团队分享你的发现
持续迭代 - 性能优化永远在路上

立即行动:

选择一个优化领域开始
测量当前性能
实施改进
测量结果
迭代改进

最终目标: 让Claude Code成为你最高效的编程伙伴,而不是最昂贵的聊天工具。

为什么要优化性能​

实际体验差异​

实际对比​

加快响应速度​

1. 请求要说清楚​

别说模糊的话​

使用明确的上下文限定​

2. 批量操作优化​

合并相关请求​

批量文件操作​

3. 利用工具的并发能力​

并行读取文件​

并行执行命令​

实战示例:批量代码审查​

减少等待时间​

1. 智能使用CLAUDE.md​

Controller Pattern​

创建任务模板​

3. 上下文预热技巧​

项目启动时预热​

智能缓存策略​

上下文优化​

1. 精简上下文内容​

只包含必要信息​

使用引用而非复制​

2. 分层上下文管理​

环境特定配置​

动态上下文加载​

3. 上下文窗口优化​

Token使用策略​

大文件处理策略​

并发操作​

1. 多任务并行处理​

并行文件读取模式​

批量代码生成​

2. 独立任务并发​

测试+构建并行​

代码审查+文档生成​

3. 流水线优化​

智能任务依赖管理​

实战:完整功能开发流水线​

缓存利用​

1. 文件系统缓存​

理解缓存机制​

利用缓存的策略​

2. 模式匹配缓存​

智能搜索策略​

3. 项目级缓存策略​

初始化缓存​

缓存失效处理​

4. 会话状态缓存​

对话历史利用​

性能监控​

1. 响应时间追踪​

建立性能基线​

识别性能瓶颈​

2. Token使用监控​

追踪Token消耗​

Token优化技术​

3. 效率指标​

定义成功指标​

持续改进​

实用技巧和最佳实践​

1. 请求优化清单​

发送请求前的检查​

请求模板库​

2. 高级工作流​

迭代开发模式​

调试工作流​

3. 团队协作优化​

共享性能实践​

Performance Standards​

Team Training​

Performance Tips Log​

Monthly Performance Sharing​

性能恢复策略​

总结与行动指南​

核心原则回顾​

立即可行的优化​

今天就可以做的(5分钟)​