sc

This directory contains slash commands that are installed to `~/.claude/commands/sc/` when users run `superclaude install`.

name: sc:agent

Comprehensive code analysis across quality, security, performance, and architecture domains

Interactive requirements discovery through Socratic dialogue and systematic exploration

Build, compile, and package projects with intelligent error handling and optimization

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Systematically clean up code, remove dead code, and optimize project structure

Design system architecture, APIs, and component interfaces with comprehensive specifications

Generate focused documentation for components, functions, APIs, and features

Provide development estimates for tasks, features, or projects with intelligent analysis

Provide clear explanations of code, concepts, and system behavior with educational clarity

Git operations with intelligent commit messages and workflow optimization

List all available /sc:sc commands and their functionality

Feature and code implementation with intelligent persona activation and MCP integration

Apply systematic improvements to code quality, performance, and maintainability

Repository Indexing - 94% token reduction (58K → 3K)

Generate comprehensive project documentation and knowledge base with intelligent organization

Session lifecycle management with Serena MCP integration for project context loading

Project Manager Agent - Default orchestration agent that coordinates all sub-agents and manages workflows seamlessly

Ultra-intelligent command recommendation engine - recommends the most suitable SuperClaude commands for any user input

Task reflection and validation using Serena MCP analysis capabilities

Deep web research with adaptive planning and intelligent search

Session lifecycle management with Serena MCP integration for session context persistence

SuperClaude command dispatcher - Use /sc:sc [command] to access all SuperClaude features

Intelligent MCP tool selection based on complexity scoring and operation analysis

Meta-system task orchestration with intelligent breakdown and delegation

Multi-expert specification review and improvement using renowned specification and software engineering experts

Execute complex tasks with intelligent workflow management and delegation

Execute tests with coverage analysis and automated quality reporting

Diagnose and resolve issues in code, builds, deployments, and system behavior

Generate structured implementation workflows from PRDs and feature requirements

Interactive MCP server setup wizard

Verify MCP server installation and configuration status

4つのContext Engineeringエージェントの詳細仕様を作成しました:

このディレクトリには、SuperClaudeフレームワークのコンテキストエンジニアリング機能を実装する4つの新エージェントが含まれています。

Implement sophisticated memory systems and RAG (Retrieval Augmented Generation) pipelines for long-term context retention and intelligent information retrieval.

Automatically generate and maintain comprehensive technical documentation, tutorials, and knowledge bases to improve transparency and developer onboarding.

Implement systematic evaluation pipeline to measure, track, and optimize SuperClaude's performance across all dimensions using Context Engineering principles.

Transform SuperClaude outputs into machine-readable, validated formats for seamless integration with CI/CD pipelines, automation tools, and downstream systems.

This directory contains agent definition files for specialized AI agents.

Design reliable backend systems with focus on data integrity, security, and fault tolerance

Multi-expert business strategy panel synthesizing Christensen, Porter, Drucker, Godin, Kim & Mauborgne, Collins, Taleb, Meadows, and Doumont; supports sequential, debate, and Socratic modes.

Specialist for comprehensive research with adaptive strategies and intelligent exploration

Adaptive research specialist for external knowledge gathering

Automate infrastructure and deployment processes with focus on reliability and observability

Create accessible, performant user interfaces with focus on user experience and modern frameworks

Teach programming concepts and explain code with focus on understanding through progressive learning and practical examples

Optimize system performance through measurement-driven analysis and bottleneck elimination

Self-improvement workflow executor that documents implementations, analyzes mistakes, and maintains knowledge base continuously

Deliver production-ready, secure, high-performance Python code following SOLID principles and modern best practices

Ensure software quality through comprehensive testing strategies and systematic edge case detection

Improve code quality and reduce technical debt through systematic refactoring and clean code principles

Repository indexing and codebase briefing assistant

Transform ambiguous project ideas into concrete specifications through systematic requirements discovery and structured analysis

Systematically investigate complex problems to identify underlying causes through evidence-based analysis and hypothesis testing

Identify security vulnerabilities and ensure compliance with security standards and best practices

Post-implementation validation and reflexion partner

Educational guide specializing in Socratic method for programming knowledge with focus on discovery learning through strategic questioning

Design scalable system architecture with focus on maintainability and long-term technical decisions

Create clear, comprehensive technical documentation tailored to specific audiences with focus on usability and accessibility