Ralph TUI is an open-source terminal user interface and task orchestrator for AI coding agents, developed by subsy and hosted on GitHub with mirrors on SourceForge. It shifts the AI workflow away from standard conversational chat windows into a structured, queue-driven execution engine designed to operate like a build tool. In practice, Ralph TUI manages a backlog of engineering tasks directly in the terminal. The orchestrator executes a disciplined loop: selecting the highest-priority task, assembling the necessary prompt and context, triggering the agent process, monitoring the run for completion criteria, and progressing through the pipeline. It also supports reusable behavioral definitions ("skills") to standardize how agents approach planning, implementation, and code review stages. Ralph TUI differs from standard conversational coding assistants by focusing on harness-level orchestration, state tracking, and repeatable multi-step workflows. Instead of requiring constant manual prompt-and-response cycles, it handles task dependencies and lifecycle state transitions within a consolidated terminal view. The project is open source under the MIT License and developed in TypeScript, supporting Linux and Unix-like terminal environments.
Terminal Task Queue Management — Organizes and runs agent-driven development workflows through a dedicated terminal UI. - Priority-Based Task Loop — Selects next-in-line tasks based on user-defined priority and progresses automatically upon completion. - Completion Detection & State Tracking — Monitors agent activity and enforces completion criteria before advancing the pipeline. - Reusable Skill Behaviors — Configures modular prompts and standardized routines for planning, execution, and review. - Multi-Step Workflow Support — Coordinates interdependent tasks with explicit state transitions and execution history.
Use cases
Use Case: Multi-Step Feature Implementation Developers break down a complex feature into an ordered task queue within the TUI, allowing the orchestrator to execute planning, file creation, and testing stages iteratively.
Use Case: Batch Refactoring Pipelines Engineers configure a series of discrete refactoring steps across a codebase, letting Ralph TUI cycle through each task and verify completion without continuous manual re-prompting.
Use Case: Standardized Team Workflow Automation Teams define standardized skill configurations for routine code generation and review tasks, ensuring consistent agent behavior across different project environments.
Who it is for
Ralph TUI is designed for developers, DevOps engineers, and technical leads who prefer automated task queues and terminal-based workflows over conversational web or IDE chat interfaces. It is less suited for developers seeking interactive, single-prompt conversational assistants or tight visual IDE integration.
Install guide
Installation Clone the source repository and install project dependencies using Node.js/npm: bash git clone https://github.com/subsy/ralph-tui.git cd ralph-tui npm install npm run build(Note: Binary releases and source archives are also available via GitHub and the SourceForge mirror.)
First Run Ensure necessary agent binaries and API credentials are configured in your shell environment, then launch the interface: bash npm start
Example Session Launch Ralph TUI to initialize your task queue: bash ralph-tui From the TUI dashboard, populate your task queue (e.g., Task 1: Add user auth endpoint, Task 2: Write integration tests), assign skills for implementation, and trigger the execution pipeline to run through the queued tasks.
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