Performance Tuning & Optimization

Performance optimization in Claude Code isn’t just about speed—it’s about maximizing the value extracted from every token while maintaining high-quality outputs. This guide provides expert strategies for tuning Claude Code to handle everything from quick fixes to massive refactoring operations efficiently.

Understanding Performance Factors

Key Performance Metrics

Response Latency

Time from prompt to first output token
Target: < 2s for simple tasks

Token Efficiency

Output quality per token consumed
Target: > 80% useful content

Context Utilization

Relevant context vs total context
Target: > 70% relevance

Task Completion Rate

Success rate on first attempt
Target: > 90% for routine tasks

Performance Bottlenecks

Bottleneck	Impact	Mitigation Strategy
Large Context Window	Slower responses, higher costs	Use /clear, focused queries
Complex Reasoning	Extended thinking time	Strategic model selection
File System Operations	I/O delays	Batch operations, caching
Network Latency	API response delays	Local caching, parallel requests
Inefficient Prompts	Wasted tokens, poor results	Prompt optimization techniques

Context Optimization Strategies

1. Hierarchical Context Management

Structure your CLAUDE.md files for optimal context loading:

# Root CLAUDE.md (500 tokens max)
## Critical Project Info Only
- Architecture: Microservices with Node.js
- Key commands: npm run dev, npm test
- Coding standards: ESLint + Prettier

# Frontend CLAUDE.md (300 tokens max)
## Frontend Specific
- Framework: React 18 with TypeScript
- State: Zustand stores in /src/stores
- Components: /src/components follows atomic design

# Backend CLAUDE.md (300 tokens max)
## API Specific
- Framework: Express with TypeScript
- Auth: JWT in /src/middleware/auth
- Database: Prisma ORM with PostgreSQL

2. Smart Context Loading

Inefficient

# Loads entire project context
claude
> Analyze the entire codebase and find all TODO comments

# Searches through everything
> What authentication methods are used across the project?

Efficient

# Load only relevant directories
claude --add-dir src/auth src/middleware
> Explain the authentication flow

# Focused search
> Find TODO comments in src/auth/ related to JWT expiration

3. Context Compression Techniques

Use /compact with custom instructions:

claude> /compact Keep only: code changes, test results, architecture decisions

# Or configure in CLAUDE.md
# Compaction Rules
When compacting:
- KEEP: Code samples, error messages, decisions made
- REMOVE: Explanations, examples, intermediate attempts
- SUMMARIZE: Long discussions into bullet points

4. Context Window Monitoring

Track context usage to optimize timing:

# Check current context status
claude> /context

Current Context Usage:
- Total tokens: 45,231 / 100,000 (45%)
- Files loaded: 23
- Conversation length: 2,341 tokens
- CLAUDE.md files: 3 (1,245 tokens)

# Clear before hitting limits
claude> /clear  # Reset when > 80% full

Model Selection Optimization

Strategic Model Usage

Configure intelligent model switching based on task complexity:

.claude/settings.json

{
  "model": "claude-3-5-sonnet-20241022",
  "modelStrategy": {
    "autoSwitch": true,
    "rules": [
      {
        "pattern": "fix typo|rename|format",
        "model": "claude-3-haiku-20250720",
        "reason": "Simple text operations"
      },
      {
        "pattern": "implement|create|build",
        "model": "claude-3-5-sonnet-20241022",
        "reason": "Standard development"
      },
      {
        "pattern": "architect|design|refactor entire",
        "model": "claude-3-opus-20250720",
        "reason": "Complex reasoning required"
      }
    ]
  }
}

Thinking Budget Optimization

Control reasoning depth for different tasks:

Task Type	Thinking Tokens	Use Case
Quick Fix	0-1,000	Typos, formatting, simple edits
Standard Dev	5,000-10,000	Feature implementation, bug fixes
Complex Analysis	20,000-50,000	Architecture decisions, refactoring
Deep Architecture	100,000-128,000	System design, major rewrites

Trigger specific thinking modes:

# Minimal thinking
claude> Fix the typo in README.md

# Standard thinking
claude> think: Implement user authentication

# Deep thinking
claude> think hard: Refactor the entire authentication system

# Maximum thinking
claude> ultrathink: Design a new microservices architecture

Workflow Optimization Patterns

1. Batch Processing

Group similar operations for efficiency:

1. Identify repetitive tasks

   claude> List all React components missing PropTypes

2. Create batch operation

   claude> For each component in the list above, add PropTypes definitions based on actual usage

3. Execute in parallel

   claude> Process components in groups of 5 to maintain context efficiency

2. Progressive Enhancement

Start simple and build complexity:

# Step 1: Basic implementation
claude> Create a simple user registration endpoint

# Step 2: Add validation
claude> Add input validation to the registration endpoint

# Step 3: Add security
claude> Implement rate limiting and CAPTCHA

# Step 4: Optimize
claude> Add caching and optimize database queries

3. Parallel Claude Instances

Run multiple instances for different concerns:

# Terminal 1: Frontend work
cd frontend && claude --add-dir src/components
> Refactor all button components to use new design system

# Terminal 2: Backend work
cd backend && claude --add-dir src/api
> Implement new REST endpoints for user management

# Terminal 3: Testing
cd . && claude --add-dir tests
> Write integration tests for the new features

4. Checkpoint Strategy

Create restore points for complex operations:

# Before major changes
git checkout -b ai-refactor-auth
git commit -am "Checkpoint before auth refactor"

# Let Claude work
claude> Refactor authentication to use OAuth2

# If needed, restore
git reset --hard HEAD~1

Large Codebase Optimization

Handling Files Over 10k Lines

For massive files, use targeted approaches:

# Instead of loading entire file
claude> Analyze the entire UserService.js file

# Use focused analysis
claude> In UserService.js, analyze only the authentication methods (lines 2000-3000)

# Or search first
claude> Search UserService.js for methods related to password reset
claude> Now optimize the password reset flow you found

Multi-Module Coordination

For changes spanning multiple modules:

# Create coordination file
claude> Create REFACTOR_PLAN.md outlining all modules affected by the API change

# Work module by module
claude> Following REFACTOR_PLAN.md, update the user module
claude> Following REFACTOR_PLAN.md, update the auth module
claude> Following REFACTOR_PLAN.md, update the payment module

Performance Monitoring

Real-Time Metrics

Track key performance indicators:

performance_monitor.py

import time
from datetime import datetime

class ClaudePerformanceMonitor:
    def __init__(self):
        self.metrics = []

    def track_operation(self, operation_type, tokens_used, duration):
        efficiency = self.calculate_efficiency(
            operation_type, tokens_used, duration
        )
        self.metrics.append({
            'timestamp': datetime.now(),
            'operation': operation_type,
            'tokens': tokens_used,
            'duration': duration,
            'efficiency': efficiency,
            'tokens_per_second': tokens_used / duration
        })

    def get_optimization_suggestions(self):
        # Analyze patterns and suggest optimizations
        avg_efficiency = sum(m['efficiency'] for m in self.metrics) / len(self.metrics)
        if avg_efficiency < 0.7:
            return "Consider more focused queries and clearing context more frequently"

Performance Benchmarks

Establish baselines for common operations:

Operation	Optimal Time	Token Budget	Success Criteria
Add simple feature	2-5 min	5-10k	Tests pass, follows patterns
Fix bug	1-3 min	2-5k	Bug resolved, no regressions
Refactor module	10-20 min	20-50k	Improved structure, tests pass
Write tests	5-10 min	10-20k	80%+ coverage, edge cases
Documentation	2-5 min	5-10k	Clear, comprehensive, examples

Optimization Techniques by Scenario

Quick Fixes and Hot Patches

# Optimize for speed
export CLAUDE_CODE_MODEL=claude-3-haiku-20250720
claude --dangerously-skip-permissions

# Direct command
claude -p "Fix the typo in line 234 of app.js where 'recieve' should be 'receive'"

Feature Development

# Optimize for quality
export CLAUDE_CODE_MODEL=claude-3-5-sonnet-20241022

# Progressive approach
claude
> First, create a plan for implementing the shopping cart feature
> Now implement the cart state management
> Add the UI components
> Write comprehensive tests
> Document the new feature

Large-Scale Refactoring

# Optimize for safety and completeness
export CLAUDE_CODE_MODEL=claude-3-opus-20250720
export MAX_THINKING_TOKENS=100000

# Systematic approach
claude
> ultrathink: Analyze the current architecture and identify refactoring opportunities
> Create a detailed refactoring plan with phases
> Implement phase 1 with careful testing
> Review changes and proceed to phase 2

Advanced Performance Patterns

1. Lazy Loading Context

Load context only when needed:

.claude/commands/lazy-load.md

Only load files when specifically working on them:
- Start with high-level analysis
- Load specific files as needed
- Clear irrelevant context frequently

2. Caching Strategies

Implement caching for repeated operations:

# Cache analysis results
claude> Analyze all API endpoints and save results to API_ANALYSIS.md
claude> Using API_ANALYSIS.md, generate OpenAPI documentation

# Reuse in future sessions
claude> Based on API_ANALYSIS.md, identify endpoints missing authentication

3. Template-Based Generation

Create templates for common patterns:

.claude/templates/component.md

When creating React components:
1. Use this exact structure
2. Include these PropTypes
3. Follow this naming convention
4. Include these test cases

Performance Troubleshooting

Common Issues and Solutions

Slow Responses

Symptoms: Long delays before Claude responds

Solutions:

1. Clear context: /clear
2. Use more specific queries
3. Switch to faster model for simple tasks
4. Check network connectivity
5. Reduce concurrent operations

Quality Degradation

Symptoms: Outputs become less accurate over time

Solutions:

1. Reset conversation context
2. Refresh CLAUDE.md if modified
3. Break complex tasks into steps
4. Use checkpoints for validation
5. Switch to higher-capacity model

Token Limit Errors

Symptoms: “Context window exceeded” errors

Solutions:

1. Use /compact aggressively
2. Split large operations
3. Clear between unrelated tasks
4. Optimize CLAUDE.md size
5. Use file-specific analysis

Best Practices Summary

Start Focused

Begin with specific, targeted queries rather than broad analysis

Clear Regularly

Use /clear between unrelated tasks to maintain efficiency

Monitor Usage

Track token consumption and adjust strategies accordingly

Choose Models Wisely

Match model capacity to task complexity for optimal performance

Performance Checklist

• CLAUDE.md files under 1,000 tokens each
• Context cleared between major tasks
• Model selection strategy configured
• Batch operations for repetitive tasks
• Parallel instances for independent work
• Performance monitoring in place
• Regular checkpoint commits
• Templates for common patterns
• Focused directory loading
• Thinking budgets calibrated

Next Steps

Cost Optimization

Reduce costs while maintaining performance

CI/CD Integration

Optimize Claude Code in automated pipelines

Team Scaling

Performance patterns for large teams