
SuperAgent
Orchestrates multiple AI coding agents (Codex, Gemini, Continue) in parallel across different project directories with 16 specialized programming personas like backend architects and security engineers.
What it does
- Run multiple AI coding agents concurrently
- Execute tasks across different project directories
- Delegate to specialized programming personas
- List available specialized agents
- Manage parallel task execution with timeouts
Best for
Tools (4)
Run Codex CLI agent with parallel execution. Supports multiple tasks concurrently. Use 'workingDirectory' to access different project folders. Codex has full system access. Use 'agent' parameter to invoke a specific agent (run 'list-agents' to see available agents).
Run Gemini CLI agent with parallel execution. Supports multiple tasks concurrently. Use 'workingDirectory' to access different project folders. Auto-approves all actions (YOLO mode). Use 'agent' parameter to invoke a specific agent (run 'list-agents' to see available agents).
Run Continue CLI agent with parallel execution. Supports multiple tasks concurrently. Use 'workingDirectory' to access different project folders. Requires CONTINUE_CONFIG_PATH environment variable to be set. Use 'agent' parameter to invoke a specific agent (run 'list-agents' to see available agents).
List all available specialized agents for use with codex, gemini, and continue tools Available specialized agents: - backend-architect: Design reliable backend systems with focus on data integrity, security, and fault tolerance - business-panel-experts: Multi-expert business strategy panel synthesizing Christensen, Porter, Drucker, Godin, Kim & Mauborgne, Collins, Taleb, Meadows, and Doumont; supports sequential, debate, and Socratic modes. - deep-research-agent: Specialist for comprehensive research with adaptive strategies and intelligent exploration - devops-architect: Automate infrastructure and deployment processes with focus on reliability and observability - frontend-architect: Create accessible, performant user interfaces with focus on user experience and modern frameworks - general-purpose: General-purpose agent for researching complex questions, searching for code, and executing multi-step tasks with thorough analysis - learning-guide: Teach programming concepts and explain code with focus on understanding through progressive learning and practical examples - performance-engineer: Optimize system performance through measurement-driven analysis and bottleneck elimination - python-expert: Deliver production-ready, secure, high-performance Python code following SOLID principles and modern best practices - quality-engineer: Ensure software quality through comprehensive testing strategies and systematic edge case detection - refactoring-expert: Improve code quality and reduce technical debt through systematic refactoring and clean code principles - requirements-analyst: Transform ambiguous project ideas into concrete specifications through systematic requirements discovery and structured analysis - root-cause-analyst: Systematically investigate complex problems to identify underlying causes through evidence-based analysis and hypothesis testing - security-engineer: Identify security vulnerabilities and ensure compliance with security standards and best practices - socratic-mentor: Educational guide specializing in Socratic method for programming knowledge with focus on discovery learning through strategic questioning - system-architect: Design scalable system architecture with focus on maintainability and long-term technical decisions - technical-writer: Create clear, comprehensive technical documentation tailored to specific audiences with focus on usability and accessibility Use the 'agent' parameter to invoke a specific agent.