Production-ready slash commands for Claude Code that accelerate development through intelligent automation.
52 commands organized as:
- 🤖 Workflows: Multi-subagent orchestration for complex tasks
- 🔧 Tools: Single-purpose utilities for specific operations
These commands work with the Claude Code Subagents for orchestration capabilities.
cd ~/.claude
git clone https://github.com/wshobson/commands.git
git clone https://github.com/wshobson/agents.git # Required for subagent orchestration- 🤖 Workflows - Orchestrate multiple subagents for complex tasks
- 🔧 Tools - Single-purpose commands for specific operations
/api-scaffold user management with authentication
/security-scan check for vulnerabilities
/feature-development implement chat functionalityClaude Code automatically suggests relevant commands based on context.
Multi-subagent orchestration for complex tasks:
- feature-development - Backend, frontend, testing, and deployment subagents build complete features
- full-review - Multiple review subagents provide comprehensive code analysis
- smart-fix - Analyzes issues and delegates to appropriate specialist subagents
- git-workflow - Implements effective Git workflows with branching strategies and PR templates
- improve-agent - Enhances subagent performance through prompt optimization
- legacy-modernize - Modernizes legacy codebases using specialized subagents
- ml-pipeline - Creates ML pipelines with data and ML engineering subagents
- multi-platform - Builds cross-platform apps with coordinated subagents
- workflow-automate - Automates CI/CD, monitoring, and deployment workflows
- full-stack-feature - Multi-platform features with backend, frontend, and mobile subagents
- security-hardening - Security-first implementation with specialized subagents
- data-driven-feature - ML-powered features with data science subagents
- performance-optimization - End-to-end optimization with performance subagents
- incident-response - Production incident resolution with ops subagents
- ai-assistant - Build production-ready AI assistants and chatbots
- ai-review - Specialized review for AI/ML codebases
- langchain-agent - Create LangChain/LangGraph agents with modern patterns
- ml-pipeline - Create end-to-end ML pipelines with MLOps
- prompt-optimize - Optimize AI prompts for performance and quality
- code-explain - Generate detailed explanations of complex code
- code-migrate - Migrate code between languages, frameworks, or versions
- refactor-clean - Refactor code for maintainability and performance
- tech-debt - Analyze and prioritize technical debt
- data-pipeline - Design scalable data pipeline architectures
- data-validation - Implement comprehensive data validation systems
- db-migrate - Advanced database migration strategies
- deploy-checklist - Generate deployment configurations and checklists
- docker-optimize - Advanced container optimization strategies
- k8s-manifest - Production-grade Kubernetes deployments
- monitor-setup - Set up comprehensive monitoring and observability
- slo-implement - Implement Service Level Objectives (SLOs)
- workflow-automate - Automate development and operational workflows
- api-mock - Create realistic API mocks for development and testing
- api-scaffold - Generate production-ready API endpoints with complete implementation stack
- test-harness - Create comprehensive test suites with framework detection
- accessibility-audit - Comprehensive accessibility testing and fixes
- compliance-check - Ensure regulatory compliance (GDPR, HIPAA, SOC2)
- security-scan - Comprehensive security scanning with automated remediation
- debug-trace - Advanced debugging and tracing strategies
- error-analysis - Deep error pattern analysis and resolution strategies
- error-trace - Trace and diagnose production errors
- issue - Create well-structured GitHub/GitLab issues
- config-validate - Validate and manage application configuration
- deps-audit - Audit dependencies for security and licensing
- deps-upgrade - Safely upgrade project dependencies
- doc-generate - Generate comprehensive documentation
- git-workflow - Implement effective Git workflows
- pr-enhance - Enhance pull requests with quality checks
- cost-optimize - Optimize cloud and infrastructure costs
- onboard - Set up development environments for new team members
- multi-agent-review - Multi-perspective code review with specialized subagents
- smart-debug - Deep debugging with debugger and performance subagents
- multi-agent-optimize - Full-stack optimization with multiple subagents
- context-save - Save project context using context-manager subagent
- context-restore - Restore saved context for continuity
- Production-ready implementations
- Framework auto-detection
- Security best practices
- Built-in monitoring and testing
- Commands work together seamlessly
Total: 52 production-ready slash commands organized into:
- Feature Development & Review (3 commands)
- Development Process Automation (6 commands)
- Subagent-Orchestrated Workflows (5 commands)
- AI & Machine Learning (5 commands)
- Architecture & Code Quality (4 commands)
- Data & Database (3 commands)
- DevOps & Infrastructure (6 commands)
- Development & Testing (3 commands)
- Security & Compliance (3 commands)
- Debugging & Analysis (4 commands)
- Dependencies & Configuration (3 commands)
- Documentation & Collaboration (1 command)
- Onboarding & Setup (1 command)
- Subagent-Specific Tools (5 commands)
# Implement a complete feature
/feature-development Add user authentication with OAuth2
# Comprehensive code review
/full-review Review the authentication module
# Smart issue resolution
/smart-fix Fix performance degradation in API response times
# Modernize legacy system
/legacy-modernize Migrate monolithic Java app to microservices
# Build comprehensive multi-platform feature
/full-stack-feature User authentication with social login across web and mobile
# Implement security-first architecture
/security-hardening Harden API endpoints and implement zero-trust security model
# Create data-driven ML feature
/data-driven-feature Build recommendation engine with real-time personalization
# Optimize entire application stack
/performance-optimization Improve response times and reduce infrastructure costs
# Respond to production incident
/incident-response High CPU usage causing service degradation in production# Create a user management API
/api-scaffold user CRUD operations with JWT auth and role-based access
# Review microservices architecture
/multi-agent-review analyze our microservices for coupling and scalability issues
# Optimize LLM chat application
/prompt-optimize reduce latency for customer support chatbot while maintaining accuracy
# Create fraud detection pipeline
/data-pipeline real-time fraud detection with feature store and monitoring
# Debug production issue
/error-trace analyze high memory usage in production pods
# Secure container images
/security-scan scan and fix vulnerabilities in Docker images
# Generate API documentation
/doc-generate create OpenAPI docs with examples for REST endpoints
# Onboard new developer
/onboard Setup development environment for React/Node.js project
# Multi-perspective code review
/multi-agent-review Review authentication module
# Deep debugging
/smart-debug Investigate memory leak in production workers
# Full-stack optimization
/multi-agent-optimize Optimize checkout flow for better conversion
# Save project context
/context-save Save current project state and architectural decisions
# Restore project context
/context-restore Load context from last week's sprintComprehensive security scanning with automated remediation.
- Multi-Tool Scanning: Bandit, Safety, Trivy, Semgrep, ESLint Security, Snyk
- Automated Fixes: Common vulnerabilities auto-remediated
- CI/CD Integration: Security gates for GitHub Actions/GitLab CI
- Container Scanning: Image vulnerability analysis
- Secret Detection: GitLeaks and TruffleHog integration
Advanced container optimization strategies.
- Smart Optimization: Analyzes and suggests improvements
- Multi-Stage Builds: Framework-specific optimized Dockerfiles
- Modern Tools: BuildKit, Bun, UV for faster builds
- Security Hardening: Distroless images, non-root users
- Cross-Command Integration: Works with /api-scaffold outputs
Production-grade Kubernetes deployments.
- Advanced Patterns: Pod Security Standards, Network Policies, OPA
- GitOps Ready: FluxCD and ArgoCD configurations
- Observability: Prometheus ServiceMonitors, OpenTelemetry
- Auto-Scaling: HPA, VPA, and cluster autoscaler configs
- Service Mesh: Istio/Linkerd integration
Advanced database migration strategies.
- Multi-Database: PostgreSQL, MySQL, MongoDB, DynamoDB
- Zero-Downtime: Blue-green deployments, rolling migrations
- Event Sourcing: Kafka/Kinesis integration for CDC
- Cross-Platform: Handles polyglot persistence
- Monitoring: Migration health checks and rollback
The real power comes from combining workflows and tools for complete development cycles:
# 1. Use a workflow to implement the feature with multiple subagents
/feature-development Add real-time chat feature with WebSocket support
# 2. Use tools for specific enhancements
/test-harness Add integration tests for WebSocket connections
/security-scan Check for WebSocket vulnerabilities
/docker-optimize Optimize container for WebSocket connections
# 3. Use a workflow for comprehensive review
/full-review Review the entire chat feature implementation# 1. Start with the modernization workflow
/legacy-modernize Migrate Express.js v4 app to modern architecture
# 2. Use specific tools for cleanup
/deps-upgrade Update all dependencies to latest versions
/refactor-clean Remove deprecated patterns and dead code
/test-harness Ensure 100% test coverage
# 3. Optimize and deploy
/docker-optimize Create multi-stage production build
/k8s-manifest Deploy with zero-downtime strategyCommands can be used individually or combined in powerful patterns:
# Build → Test → Secure → Deploy pipeline
/api-scaffold user management API
/test-harness comprehensive test suite for user API
/security-scan check user API for vulnerabilities
/k8s-manifest deploy user API to production# Multiple perspectives on the same codebase
/multi-agent-review comprehensive architecture and code review
/security-scan audit security posture
/performance-optimization identify and fix bottlenecks
# Then consolidate findings# Start broad, then narrow focus
/feature-development implement payment processing
/security-scan focus on payment security
/compliance-check ensure PCI compliance
/test-harness add payment-specific tests# Frontend + Backend + Infrastructure
/api-scaffold backend payment API
/multi-agent-optimize optimize payment flow performance
/docker-optimize containerize payment service
/monitor-setup payment metrics and alerts- Problem-solving: Analyze and fix issues adaptively
- Multiple perspectives: Coordinate specialist subagents
- Complex tasks: Multi-step processes across domains
- Unknown solutions: Let subagents determine approach
- Infrastructure setup: Configure environments
- Code generation: Create specific implementations
- Analysis: Generate reports without fixes
- Domain tasks: Highly specialized operations
Examples:
- "Implement user authentication system" →
/feature-development - "Fix performance issues across the stack" →
/smart-fix - "Modernize legacy monolith" →
/legacy-modernize
- Specific expertise needed - Clear, focused task in one domain
- Precise control desired - Want to direct specific implementation details
- Part of manual workflow - Integrating into existing processes
- Deep specialization required - Need expert-level implementation
- Building on existing work - Enhancing or refining previous outputs
Examples:
- "Create Kubernetes manifests" →
/k8s-manifest - "Scan for security vulnerabilities" →
/security-scan - "Generate API documentation" →
/doc-generate
Slash commands are simple markdown files where:
- The filename becomes the command name (e.g.,
api-scaffold.md→/api-scaffold) - The file content is the prompt/instructions executed when invoked
- Use
$ARGUMENTSplaceholder for user input
- Let Claude Code suggest automatically - Analyzes context and selects optimal commands
- Use workflows for complex tasks - Subagents coordinate multi-domain implementations
- Use tools for focused tasks - Apply specific commands for targeted improvements
- Provide comprehensive context - Include tech stack, constraints, and requirements
- Chain commands strategically - Workflows → Tools → Refinements
- Build on previous outputs - Commands are designed to work together
- Create
.mdfile inworkflows/ortools/ - Use lowercase-hyphen-names
- Include
$ARGUMENTSfor user input
Command not found: Check files are in ~/.claude/commands/
Workflows slow: Normal - they coordinate multiple subagents
Generic output: Add more specific context about your tech stack
Integration issues: Verify file paths and command sequence
Command Selection:
- Workflows: Multi-subagent coordination for complex features
- Tools: Single-purpose operations for specific tasks
- Simple edits: Stay with main agent
Optimization:
- Start with tools for known problems
- Provide detailed requirements upfront
- Build on previous command outputs
- Let workflows complete before modifications
- Focus on subagent orchestration and delegation logic
- Specify which specialized subagents to use and in what order
- Define coordination patterns between subagents
- Include complete, production-ready implementations
- Structure content with clear sections and actionable outputs
- Include examples, best practices, and integration points
- Claude Code Documentation
- Slash Commands Documentation
- Subagents Documentation
- Claude Code GitHub
- Claude Code Subagents Collection - Specialized subagents used by these commands