Goated Agents simplifies building sophisticated AI-driven autonomous systems in Go. By embedding chain-of-thought processing directly in the language runtime, developers can implement multi-step reasoning with transparent intermediate reasoning logs. The library offers a tool definition API, allowing agents to call external services, databases, or custom code modules. Memory management support enables persistent context across interactions. Plugin architecture facilitates extending core capabilities such as tool wrappers, logging, and monitoring. Goated Agents leverages Go’s performance and static typing to deliver efficient, reliable agent execution. Whether constructing chatbots, automation pipelines, or research prototypes, Goated Agents provides the building blocks to orchestrate complex reasoning flows and integrate LLM-driven intelligence seamlessly into Go applications.

llm-ReAct implements the ReAct (Reasoning and Acting) architecture for large language models, enabling seamless integration of chain-of-thought reasoning with external tool execution and memory storage. Developers can configure a toolkit of custom tools—such as web search, database queries, file operations, and calculators—and instruct the agent to plan multi-step tasks, invoking tools as needed to retrieve or process information. The built-in memory module preserves conversational state and past actions, supporting more context-aware agent behaviors. With modular Python code and support for OpenAI APIs, llm-ReAct simplifies experimentation and deployment of intelligent agents that can adaptively solve problems, automate workflows, and provide context-rich responses.

micro-agent provides a minimalistic yet powerful set of abstractions for creating autonomous AI agents. Built in TypeScript, it runs seamlessly in both browser and Node.js contexts, allowing you to define agents with custom prompt templates, decision logic, and extensible tool integrations. Agents can leverage chain-of-thought reasoning, interact with external APIs, and maintain conversational or task-specific memory. The library includes utilities for handling API responses, error management, and session persistence. With micro-agent, developers can prototype and deploy agents for a range of tasks—such as automating workflows, building conversational interfaces, or orchestrating data-processing pipelines—without the overhead of larger frameworks. Its modular design and clear API surface make it easy to extend and integrate into existing applications.