This repository is a reference implementation and guided tutorial for building an AI coding agent that combines conversational interaction with file system manipulation and sandboxed shell execution. The agent uses a large language model as its core decision-making component, operating within a turn-based conversational loop where it can generate responses or invoke tools, and tool results are fed back into the dialogue. It provides primitives for reading, writing, and listing files on the local filesystem, as well as searching code using regular expressions.
The agent’s capabilities are extended through a plugin-based tool system, where each tool is defined by a name, a JSON Schema input specification, and a handler function. Shell commands run inside a sandboxed environment that isolates system access and enforces resource limits, enabling safe automation. A file system abstraction layer unifies file operations across the operating system, keeping the agent platform-agnostic.
The project covers the full development workflow for an AI coding agent, including automated code editing, regex-powered code search, and a customizable tool plugin framework. The architecture is designed around a conversational agent loop, LLM integration, and a plugin-based tool system as its foundational components.
The repository includes a step-by-step guide and a complete reference template for implementing an interactive chat agent with filesystem and shell access.
