ghuntley/how-to-build-a-coding-agent
How To Build A Coding Agent
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.
Features
- Coding Agents - Provides a reference implementation and tutorial for building an LLM-powered coding agent with filesystem and shell access.
- Autonomous Coding Agents - Builds an autonomous coding agent that decomposes tasks and automates development workflows.
- Agent Plugin Frameworks - Provides a modular plugin framework for registering and integrating specialized tools into autonomous agent systems.
- Agentic Execution Loops - Orchestrates multi-turn conversational workflows with tool calling and state management.
- Custom Tool Definitions - Ships a framework for defining custom tools with JSON input schemas to extend agent capabilities.
- Agentic Workflow Tutorials - Provides a guided tutorial and reference template for building a production-ready agentic application.
- AI Chat Interfaces - Provides a conversational interface for interacting with AI coding agents via language models.
- Interactive Agent Chat Interfaces - Provides an interactive terminal-based chat interface for real-time messaging with an AI agent that performs filesystem actions.
- Large Language Model Integration - Integrates a large language model as the core decision-making component for interpreting requests and invoking tools.
- Local File Operations - Provides local file operations including creating, modifying, and appending files as instructed.
- Sandboxed Shell Executions - Runs terminal commands in a sandboxed environment with OS-level isolation for safe automation.
- Tooling Plugin Systems - Provides a plugin architecture for adding custom tools with JSON schema specifications and handler functions.
- File Reading - Reads the full text of specified files from the local filesystem for analysis.
- AI Edit Commands - Applies AI-driven transformations to file content, enabling creation, modification, and appending of files.
- Regex-Based File Search - Searches file contents using regular expressions to enable pattern-based code queries.
- Text Pattern Search - Searches code using regular expressions to find patterns, definitions, and references.
