DennisTraub/aws-bench
aws-bench measures how well AI agents and model combinations perform on real AWS work — diagnosing misconfigurations, provisioning infrastructure, and operating live cloud environments.
Research Engineering, Agentic Developer Experience at AWS
aws-bench measures how well AI agents and model combinations perform on real AWS work — diagnosing misconfigurations, provisioning infrastructure, and operating live cloud environments.
Official Claude Code compound engineering plugin
Framework for evaluating and improving agents
Feedback-first writing review skills for stress-testing drafts.
an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
Bootstrap AI agent companies from modular templates.
Open-source orchestration for zero-human companies
A system for autonomous creation and optimization.
PREVIEW: the new terminal experience for AgentCore
This MCP server provides documentation about Strands Agents to your GenAI tools, so you can use your favorite AI coding assistant to vibe-code Strands Agents.
Python functions powered by AI agents - with runtime post-conditions for reliable agentic workflows.
Natural language workflows that enable AI agents to perform complex, multi-step tasks with consistency and reliability.
A model-driven approach to building AI agents in just a few lines of code.
Agentic AI Infrastructure for magnifying HUMAN capabilities.
AWS MCP Proxy Server
Sample implementations of AI Agents and MCP Servers running on AWS Serverless compute
Educational code examples demonstrating Amazon Bedrock usage across Python, Java, JavaScript, C#, and PHP. Complete, documented examples of InvokeModel, Converse, and ConverseStream APIs for building generative AI applications in your preferred programming language.
Educational examples demonstrating how to enhance AI capabilities by connecting Amazon Bedrock to real-world data and services. From basic LLMs to context-aware, dynamic AI solutions.
React components for Cloudscape Design System
The 500 AI Agents Projects is a curated collection of AI agent use cases across various industries. It showcases practical applications and provides links to open-source projects for implementation, illustrating how AI agents are transforming sectors such as healthcare, finance, education, retail, and more.
Download files from GitHub repository folders while maintaining directory structure. Features include recursive folder traversal, SHA-based file tracking to avoid redundant downloads, and a SQLite database for efficient caching. Available both as a Python library for integration into other tools and as a standalone CLI application.