How does Superpowers compare to basic AI coding plugins?

Superpowers enforces systematic workflows like TDD and planning, whereas basic plugins often generate ad-hoc code without structured processes. It's better for teams wanting consistency, but may add overhead for simple tasks.

How to install Superpowers on Cursor?

In Cursor Agent chat, use '/add-plugin superpowers' or search the plugin marketplace. The README specifies this, and it automatically integrates skills for workflows like brainstorming and debugging.

Can Superpowers be used with VS Code without Claude?

No, Superpowers is designed for specific AI assistants like Claude Code or Cursor; VS Code alone isn't supported. You'd need a compatible agent platform listed in the installation section.

What are the system requirements for Superpowers?

It requires an AI coding assistant like Claude, Cursor, or GitHub Copilot CLI, and a Git-enabled project. The README notes platform-specific setup, but no additional hardware or software beyond the agent environment.

How to create custom skills in Superpowers?

Follow the 'writing-skills' skill included in the library, which provides guidelines for creating and testing new skills. Contribute via forking the repo and submitting PRs, as detailed in the contributing section.

Superpowers

MITShellv5.0.7

A complete agentic skills framework and software development workflow for coding agents that enforces systematic processes like TDD and subagent-driven development.

GitHub

164.6k stars14.4k forks0 contributors

What is Superpowers?

Superpowers is an agentic skills framework and software development methodology for coding agents like Claude, Cursor, and GitHub Copilot. It provides a complete workflow that ensures agents follow systematic processes including brainstorming, test-driven development, subagent-driven development, and code review automation. The framework solves the problem of ad-hoc AI code generation by enforcing structured methodologies that produce higher quality, more maintainable code.

Target Audience

Developers using AI coding assistants (Claude Code, Cursor, Codex, OpenCode, GitHub Copilot, Gemini CLI) who want to implement systematic software development practices through their agents. Teams looking to standardize AI-assisted development workflows with enforced testing and review processes.

Value Proposition

Developers choose Superpowers because it transforms coding agents from simple code generators into systematic engineering partners that enforce best practices automatically. Unlike basic AI coding tools, it provides mandatory workflows that ensure test-driven development, proper planning, and quality review processes without manual intervention.

Overview

An agentic skills framework & software development methodology that works.

Use Cases

Best For

Related Projects

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Implementing test-driven development workflows with AI coding assistants
Structuring complex feature development with systematic planning and execution
Debugging complex issues using systematic root cause analysis techniques
Managing parallel development branches and Git workflows with AI agents
Enforcing code review processes in AI-assisted development environments
Creating custom skills and extending functionality for coding agents

Not Ideal For

Developers needing quick, one-off code snippets without full TDD or planning workflows
Teams using AI coding assistants not supported by Superpowers (e.g., unsupported platforms or custom setups)
Projects with existing, highly customized development processes that conflict with Superpowers' enforced methodologies

Pros & Cons

Pros

Automated Systematic Workflows

Skills trigger automatically to enforce structured processes like brainstorming and TDD, reducing ad-hoc code generation without manual intervention, as highlighted in the README's workflow description.

Test-Driven Development Enforcement

Implements true red/green/refactor cycles and deletes code written before tests, ensuring higher code quality and adherence to TDD principles, as emphasized in the philosophy section.

Subagent-Driven Autonomy

Uses fresh subagents per task with two-stage reviews for spec compliance and code quality, enabling hours of autonomous work without deviation, as described in the subagent-driven-development skill.

Integrated Git Management

Handles isolated Git worktrees, branch creation, and merge/PR decisions automatically, streamlining version control within AI-assisted development, as detailed in the using-git-worktrees skill.

Cons

Platform-Specific Dependency

Limited to specific AI coding assistants like Claude, Cursor, and others listed in installation; unsupported tools require manual setup or may not work, as shown in the fragmented installation docs.

Overhead for Simple Tasks

Mandatory brainstorming, planning, and review phases can introduce unnecessary steps for trivial coding tasks, potentially slowing down quick fixes or minor changes.

Skill Creation Complexity

Extending functionality requires following the 'writing-skills' skill with specific guidelines, which may have a steep learning curve for users not familiar with the framework's internals.

Frequently Asked Questions

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The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

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