Ralph Loop
Open-source AI agent loop that iterates a task list in Docker Sandboxes and commits the results.
If you already live in a terminal and want an agent that keeps working after you close the laptop, Ralph Loop delivers deterministic Docker Sandboxes, mid-flight steering via .agent/STEERING.md, and commits by morning across six agentic CLIs. The catch is the setup: Docker, CLI comfort, and task-list discipline are assumed, and the first iteration alone takes about five minutes just to prepare the sandbox. Skip it if you want a GUI or real-time pair-programming, because those are different products entirely.
Verified 7d ago · liveness 70/100 · cite: rightaichoice.com/tools/ralph-loop
- Developers who want unattended overnight coding sessions that produce commits by morning
- Teams automating large PRD-to-code pipelines with hundreds of tasks
- Power users who prefer CLI and Docker over GUI agent tools
- Hackers who want to modify ralph.sh and extend loop behavior
- Non-technical users unfamiliar with CLI and Docker
- Anyone wanting a no-setup GUI agent tool with drag-and-drop interfaces
- Beginners who need hand-holding and immediate error explanations
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Skip Ralph Loop if you want a GUI, real-time pair-programming, or a tool that works without Docker and a terminal.
The loop is free, but each underlying agent CLI (Claude Code, Codex CLI, Cursor CLI, Copilot CLI, Gemini CLI) can carry its own usage or subscription costs.
Ralph Loop is a free, MIT-licensed open-source shell script with no paid tier of its own. Your real spend comes from the agentic CLI you drive — Claude Code, Codex CLI, Cursor CLI, GitHub Copilot CLI, Gemini CLI, or opencode — each of which prices separately. Compared with paid GUI agent editors that bundle a UI and subscription, Ralph costs nothing but assumes you already pay for an agent CLI and have Docker.
In short
Ralph Loop — Open-source AI agent loop that iterates a task list in Docker Sandboxes and commits the results. Best for Developers who want unattended overnight coding sessions that produce commits by morning, Teams automating large PRD-to-code pipelines with hundreds of tasks, Power users who prefer CLI and Docker over GUI agent tools. Free to use.
What's new in Ralph Loop
Checked 7 days agoAcross the latest 5 updates: 5 changelog entries.
How to Run a Ralph Loop With the Cursor CLI
A full end-to-end setup for running the Ralph loop with the Cursor CLI, including install, task list, sandbox login, and commit review.
The Ralph Loop Shell Script: How ralph.sh Works and How to Run It
Deep dive into the open-source ralph.sh script, covering installation, flags, iteration behavior, and extensibility.
How to Run a Ralph Loop With Claude Code
Walkthrough for running the Ralph loop with Claude Code, including install, sandbox login, and commit review.
How to Run a Ralph Loop With the Codex CLI
Guide for using the Codex CLI with Ralph, covering non-interactive exec, model selection, and commit review.
How to Run a Ralph Loop With the Gemini CLI
Setup guide for Gemini CLI integration, including install, sandbox login, and model choice.
What people actually say about Ralph Loop — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
72 mentions across 4 sources (Hacker News, YouTube, GitHub, Lemmy) · researched Aug 31, 2026.
Average across the 4 sources that answered — each source counts once, not each post.
- +Deterministic Docker sandboxes per agent run, reusable and isolated.
- +Full observability: step detection, stream preview, screenshot capture, logs.
- +Mid-flight steering via STEERING.md is genuinely useful and works.
- +Multi-agent support: Claude Code, Codex CLI, Cursor, GitHub Copilot, Gemini, opencode.
- +PRD and task lookup table give durable source of truth, not fragile prompt.
- −Token costs can explode — user reported $200 overnight on 91 Codex reviews.
- −Major bug: silent no-op iterations on Windows/Git Bash due to TTY issue.
- −Shell script uses set -e but has arithmetic bugs that kill runs after first iteration.
- −PRD creator sometimes writes full code into task details, polluting the task list.
- −Fresh context per iteration means re-learning project state, costing tokens on long runs.
- • API costs for each agent call (Claude, Codex, etc.) can accumulate rapidly
- • Docker overhead and compute time
- • Potential for unexpected token burn without careful monitoring
Viability Score
How well maintained and how widely used is Ralph Loop? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Open-source long-running AI agent loop (MIT-licensed)
- PRD-driven loop generation from raw requirements
- Task lookup table with detailed per-task specs, scales to hundreds of tasks
- Deterministic Docker Sandboxes named ralph-<agent>-<dir>-<hash8>
- Multi-agent support: Claude Code, Codex CLI, Cursor CLI, GitHub Copilot CLI, Gemini CLI, opencode
- Live step detection and stream preview during runs
- Screenshot capture of agent runs
- Full history logs with per-iteration timing
- Mid-flight steering via .agent/STEERING.md read each iteration
- Automatic commit on loop completion
- CLI interface via npx @pageai/ralph-loop
- Hackable open-source shell script (ralph.sh)
- Agent login inside the sandbox via ./ralph.sh --login (default Claude, or --agent)
- Print exact sandbox name without running via ./ralph.sh --print-name
- Publish dev server port to host via ./ralph.sh --ports
About Ralph Loop
Ralph Loop is an open-source, long-running AI agent loop for developers who hand off a task list and come back to working code. You point it at a task list, walk away, and it iterates your chosen agentic CLI inside Docker Sandboxes until the job is done — even if that takes days. Instead of one fragile prompt, Ralph starts from raw requirements: it generates a PRD and a task lookup table, so every iteration has a durable source of truth and scales to hundreds of tasks without losing context. Each agent run gets a deterministic Docker Sandbox named ralph-<agent>-<dir>-<hash8>, isolated, reusable, and stopped cleanly on exit. Multi-agent support covers Claude Code (the default), Codex CLI, Cursor CLI, GitHub Copilot CLI, Gemini CLI, and opencode, all driven through the same ralph.sh script with agent flags. While it runs you get live observability — step detection, stream preview, screenshot capture, full history logs, and per-iteration timing — and you can steer mid-flight by editing .agent/STEERING.md, which Ralph reads each iteration to reprioritize critical work. Results are committed automatically on loop completion. Install is a single npx @pageai/ralph-loop command; the whole thing stays hackable through the MIT-licensed ralph.sh shell script. It is CLI and Docker only, so it competes more with running a raw agent CLI overnight than with GUI agent editors.
Behind the Verdict
Ralph Loop solves a specific problem well: letting an agent work for hours or days without you babysitting it. The design choices all serve that goal. The PRD-and-task-lookup-table step gives each iteration a durable source of truth instead of one prompt you keep re-pasting. The deterministic sandbox naming convention — ralph-<agent>-<dir>-<hash8>, e.g. ralph-claude-my-app-a1b2c3d4 — means the same project always lands in the same isolated environment, and it's stopped cleanly on exit rather than left dangling. Running your agent inside a sandbox and answering "Yes" to Bypass Permissions mode is the whole point: the isolation is what makes unattended execution tolerable. Where it stands out is control. You can read live step detection, stream preview, screenshots, history logs, and per-iteration timing while it runs, and you can change priorities mid-flight by editing .agent/STEERING.md — no restart. It supports Claude Code, Codex CLI, Cursor CLI, GitHub Copilot CLI, Gemini CLI, and opencode through the same ralph.sh script, so you are not locked to one vendor's CLI. It is MIT-licensed and hackable; the loop is a shell script you can read and modify. Its weaknesses are structural, not bugs. It is CLI and Docker only — no web UI, monitoring through terminal logs, and no hand-holding when an agent fails. Loop duration depends on your machine and Docker sandbox limits. The tool itself is free, but the underlying agent CLIs may carry their own costs, and model selection depends on which CLI you drive. It is also fundamentally batch work: point it at a task list and leave. If you want interactive pair-programming or a drag-and-drop GUI, this is the wrong shape of product. For developers who already let agents code overnight, few open-source options give you this much control over the loop itself.
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Real-world workflow fit
Concrete scenarios for the personas Ralph Loop actually fits — and what changes day-one when you adopt it.
Install with npx @pageai/ralph-loop, generate a PRD and task list using the prd-creator skill in plan mode, log in to Claude inside the sandbox via ./ralph.sh --login, then run ./ralph.sh -n 50 overnight.
Outcome: You wake up to a stack of automatic commits from 50 iterations, plus history logs and screenshots to review what changed.
Break a multi-hundred-task PRD into a task lookup table, run the loop against a deterministic sandbox named ralph-<agent>-<dir>-<hash8>, and edit .agent/STEERING.md mid-run to reprioritize critical tasks.
Outcome: The pipeline keeps moving without a human restart, and results are committed for review each time the loop completes.
Run ./ralph.sh --print-name to get the exact sandbox name, inspect the ralph-<agent>-<dir>-<hash8> environment, and use ./ralph.sh --ports to expose the dev server to the host.
Outcome: You can see the failing state inside the isolated sandbox and confirm the app's behavior without leaving your terminal.
Use Cases
- Automate overnight code generation by pointing Ralph at a PRD and walking away.
- Run multi-step refactoring tasks with deterministic sandbox isolation per step.
- Steer an agent mid-flight by editing .agent/STEERING.md without restarting the loop.
- Debug sandboxed agent failures by inspecting the ralph-<agent>-<dir>-<hash8> sandbox.
- Run a Ralph loop end-to-end with Claude Code, Cursor CLI, Codex CLI, or Gemini CLI using the published setup guides.
- Generate a PRD and task list from raw requirements, then loop through individual tasks.
- Publish a dev server port to the host with ./ralph.sh --ports to inspect a running app.
- Commit results automatically when the loop completes for morning review.
Models Under the Hood
as of 2026-10-03
Limitations
- Ralph Loop is a CLI-based tool that requires Docker and terminal proficiency; monitoring happens via terminal logs.
- It runs your chosen agentic CLI in Docker Sandboxes, so underlying agent CLIs may incur their own costs and model selection varies by the agent CLI you drive.
- Loop duration depends on system resources and Docker sandbox limits.
as of 2026-10-02
Verification history
We have re-verified Ralph Loop 7 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 7 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Ralph Loop tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Open Source
$0
Ideal for
Developers and teams who already pay for an agentic CLI and have Docker, and want the loop itself at no cost.
What this tier adds
Starting tier — the MIT-licensed ralph.sh script is free, with costs coming from the agent CLI you drive.
Where the pricing makes sense
The company stage and team size where Ralph Loop's pricing actually pencils out — and where peers do it cheaper.
Ralph Loop is a free, MIT-licensed open-source shell script with no paid tier of its own. Your real spend comes from the agentic CLI you drive — Claude Code, Codex CLI, Cursor CLI, GitHub Copilot CLI, Gemini CLI, or opencode — each of which prices separately. Compared with paid GUI agent editors that bundle a UI and subscription, Ralph costs nothing but assumes you already pay for an agent CLI and have Docker.
Setup time & first value
How long it actually takes to get something useful out of Ralph Loop — broken out by persona, not the marketing-page minute.
Solo developers comfortable with Docker and a terminal can reach first value in roughly 30-60 minutes: install Ralph, generate a PRD and task list with the prd-creator skill, log in to your agent inside the sandbox, then launch the loop. Budget about 5 minutes for the first iteration alone, which is spent preparing the named sandbox environment. Teams running large PRDs should add time for
Switching to or from Ralph Loop
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From manual agent prompting: replace re-pasted prompts with a generated PRD and task lookup table so each iteration has a durable source of truth.
- →From running a raw agent CLI overnight: install Ralph, authenticate inside Docker Sandboxes with ./ralph.sh --login, and let ralph.sh drive the same CLI in a loop.
- →From Cursor CLI alone: run the Ralph loop with the Cursor CLI by logging in inside the sandbox and looping on your task list.
- →From Codex CLI alone: drive Codex CLI under Ralph using non-interactive exec and commit review.
- →From Gemini CLI alone: point Ralph at Gemini CLI after logging in inside the sandbox and choosing your model.
- ↗To a raw agent CLI: take the task list Ralph generated and run the CLI manually per task, losing sandbox isolation and auto-commits.
- ↗To a GUI agent editor: move to a drag-and-drop interface, giving up deterministic sandboxes and .agent/STEERING.md mid-flight control.
- ↗To a managed pipeline: hand the same PRD to a hosted multi-step agent service, trading script hackability for managed infrastructure.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Ralph Loop”, and we withheld 4: 4 did not mention Ralph Loop. Showing the 2 we can prove are about Ralph Loop.
Official links
Tools that pair well with Ralph Loop
Common stack mates teams adopt alongside Ralph Loop, with the specific reason each pairing earns its keep.
MetaGPT
Open-source multi-agent framework that assigns PM, architect, engineer and QA roles to LLMs for structured software tasks
Refact.ai
Open-source autonomous AI coding agent that plans, executes, and deploys tasks inside VS Code and JetBrains IDEs.
OpenHands
Open-source platform for autonomous coding agents that fix bugs, review PRs, and automate engineering workflows.
Featured Head-to-Head Comparisons
Ralph Loop vs Locus Robotics
Ralph Loop and Locus Robotics serve completely different domains – code generation vs. warehouse automation. For developers needing unsupervised, multi-agent coding in sandboxed environments, Ralph Loop is a free, open-source powerhouse with recent CLI expansions. For logistics operations seeking to boost picking productivity 2-3x with flexible AMRs, Locus Robotics (RaaS model) is the proven choice, especially with the new Locus Array Physical AI. Choose based on your problem: digital code loops vs. physical robots.
Ralph Loop vs Presto Voice
These tools solve completely different problems — Ralph Loop is for developers automating code generation using AI agents, while Presto Voice is for QSR chains automating drive-thru ordering. Your choice depends purely on whether you need unattended code loops (Ralph Loop, free) or restaurant voice AI (Presto Voice, contact pricing).
Ralph Loop vs Truleo
These tools serve completely different domains. Ralph Loop is for developers who want to set up unattended, multi-agent coding sessions that work through a spec overnight. Truleo is an enterprise law enforcement intelligence platform for connecting data from RMS, CAD, jail calls, and BWC. Choose based on your role: builder vs law enforcement analyst.
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Frequently Asked Questions
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