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Description
Superpowers is an agentic software development framework that provides coding agents with a complete methodology for building software more carefully and consistently. The framework is built around composable skills that automatically guide agents through the right workflow at each stage of development. Instead of immediately generating code, an agent using Superpowers first clarifies the user’s goal, develops a specification, and presents the design in readable sections for approval. Once the design is approved, the agent creates a detailed implementation plan with small tasks, exact file paths, verification steps, and testing expectations. Superpowers strongly emphasizes true test-driven development, including writing failing tests first, making them pass, refactoring, and committing only after verification. The framework can use subagents to complete tasks, inspect work, review implementation quality, and continue progressing through a structured plan. It includes skills for brainstorming, writing plans, executing plans, systematic debugging, code review, git worktrees, and finishing development branches. Superpowers supports multiple coding environments, including Claude Code, Codex, Gemini CLI, OpenCode, Cursor, Factory Droid, and GitHub Copilot CLI. Superpowers helps software teams reduce agentic mistakes, improve code quality, and make AI-assisted development more predictable.
Description
TensorFlow Agents (TF-Agents) is an extensive library tailored for reinforcement learning within the TensorFlow framework. It streamlines the creation, execution, and evaluation of new RL algorithms by offering modular components that are both reliable and amenable to customization. Through TF-Agents, developers can quickly iterate on code while ensuring effective test integration and performance benchmarking. The library features a diverse range of agents, including DQN, PPO, REINFORCE, SAC, and TD3, each equipped with their own networks and policies. Additionally, it provides resources for crafting custom environments, policies, and networks, which aids in the development of intricate RL workflows. TF-Agents is designed to work seamlessly with Python and TensorFlow environments, presenting flexibility for various development and deployment scenarios. Furthermore, it is fully compatible with TensorFlow 2.x and offers extensive tutorials and guides to assist users in initiating agent training on established environments such as CartPole. Overall, TF-Agents serves as a robust framework for researchers and developers looking to explore the field of reinforcement learning.
API Access
Has API
No
API Access
Has API
Yes
Screenshots View All
No images available
Integrations
Claude Code
Yes
Codex CLI
Yes
Cursor
Yes
Factory
Yes
Gemini CLI
Yes
GitHub Copilot CLI
Yes
Grok Build
Yes
OpenAI Codex
Yes
OpenCode
Yes
Python
No
Integrations
Claude Code
No
Codex CLI
No
Cursor
No
Factory
No
Gemini CLI
No
GitHub Copilot CLI
No
Grok Build
No
OpenAI Codex
No
OpenCode
No
Python
Yes
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
Superpowers
Website
github.com/obra/superpowers
Vendor Details
Company Name
Tensorflow
Founded
2015
Country
United States
Website
www.tensorflow.org/agents