Help Center/ CodeArts Agent/ User Guide (CLI)/ What Is CodeArts Agent CLI?
Updated on 2026-07-27 GMT+08:00
View PDF
Share

What Is CodeArts Agent CLI?

Overview

CodeArts Agent CLI is an intelligent coding assistant for developers. It provides end-to-end (E2E) intelligent capabilities, such as code writing, analysis, and optimization.

Both terminal user interface (TUI) and command-line interface (CLI) are available to seamlessly integrate into various R&D workflows and adapt to diverse development scenarios. In headless environments, TUI allows you to conveniently write and debug code in a visualized manner, while CLI allows you to quickly compile code using commands.

Table 1 Differences between TUI and CLI

Item

TUI

CLI

Interaction

Dialog box input, visual operations

Direct parameter input, one-line command execution

Scenarios

Interactive development, code writing, and debugging

Script automation and batch tasks

Typical users

New users and routine development

Developers with command line experience

Supported OSs

  • Windows: Windows 11 (x64) is recommended. For Windows 10 (x64), the version must be 2019 or later, and upgrading to the latest stable version is recommended.
  • macOS: macOS 11 or later, compatible with ARM64 (Apple Silicon)
  • Linux: Huawei Cloud EulerOS 2.0, SUSE Linux Enterprise Server 12 SP5, Ubuntu 18.04/20.04/22.04/24.04 LTS, Debian 10/11/12, CentOS 8, RHEL 8/9

Core Functions

  • Command coverage: Core commands such as models (model configuration) and sessions (session management) are provided to support full lifecycle management.
  • Script-based integration: Tasks can be directly transferred through command parameters. Alternatively, commands can be written into script files (such as shell or Python scripts) for automatic execution and batch processing of AI tasks.

Advantages

  • Dual interaction modes: Both TUI and CLI are provided to support interactive visual operations and automatic script calls, adapting to different user preferences and service scenarios.
  • Intelligent and scalable agent framework: Built-in core AI agents (such as Build and Plan) and custom agent orchestration flexibly adapt to complex project development and task decomposition needs.
  • Rich ecosystem integration: Native support for extended capabilities such as Model Context Protocol (MCP) servers, skills, and custom agents enables deep integration with various development tools and service capabilities.
  • Flexible and standardized configuration: Configuration files in JSON and JSONC formats are supported with a clear, readable structure. This streamlines local debugging, team synchronization, and repository hosting.