Comparison
Shelbi vs OpenHands
Shelbi orchestrates the agent CLIs you already trust across every machine you own; OpenHands ships its own sandboxed agent and a cloud automation platform. Here's how to choose.
Shelbi and OpenHands solve the same problem from opposite ends of the stack
Both let you ship real changes with AI coding agents, not just autocomplete. But OpenHands gives you the agent and the sandbox it runs in, while Shelbi gives you the control room for running the agents you already trust — many of them, in parallel, across your own machines.
At a glance
| Shelbi | OpenHands | |
|---|---|---|
| What it is | Agent orchestrator for the terminal | Autonomous coding agent + cloud/enterprise platform |
| The agent | None of its own — drives your CLI (Claude Code, Codex, aider) | Ships the CodeAct agent, which writes and runs Python + bash to act |
| Where work runs | Many workers in parallel across laptop + remote machines over SSH | One agent per conversation inside a sandboxed runtime |
| Isolation unit | A git worktree on its own branch, per task | A Docker / Apptainer / remote container, per conversation |
| Runtime deps | ssh, tmux, git, your agent CLI — no daemons, no servers | Docker (often Docker-in-Docker), agent/automation servers, optional Kubernetes |
| State | Plain markdown + YAML files on disk | An event-sourced action/observation stream inside the platform |
| Interface | Two-pane terminal TUI | Web GUI (Agent Canvas), CLI, headless, IDE plugins, SDK |
| Models | Whatever your agent CLI already uses | Model-agnostic via LiteLLM (Claude, OpenAI, Gemini, local, …) |
| License & cost | MIT; a single self-installed binary | MIT core + paid hosted cloud + custom-priced Enterprise |
Where Shelbi excels
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It orchestrates the agents you already trust — it doesn't replace them. OpenHands is built around its own CodeAct agent. Shelbi ships no agent of its own; you point it at whatever CLI you run —
claude,codex,aider, anything you can drive interactively. Runners are declared per project, so you can hand backend tasks to one runner and front-end tasks to another without changing tools or relearning a workflow. -
Many workers in parallel, across every machine you own. OpenHands runs one agent per conversation inside a sandbox. Shelbi runs a pool of named workers concurrently — on your laptop and on remote boxes reached over SSH — each in its own git worktree on its own branch. A Mac mini in the closet plus a Linux workstation become a worker pool; the orchestrator picks the highest-priority unblocked task and dispatches it the moment a worker frees up.
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No daemons, no servers, no Docker-in-Docker. OpenHands centers on a container runtime — Docker (frequently Docker-in-Docker), agent and automation servers, optional Kubernetes at the enterprise tier — and its docs note the setup "takes real effort." Shelbi needs only
ssh,tmux,git, and your agent CLI on each machine. Adding a remote worker is a few lines in a YAML file and ashelbi reload. -
State is plain text you can grep, diff, and edit. OpenHands keeps conversation state as an event-sourced stream inside the platform. Shelbi keeps every task, log, and worker status as markdown or YAML under
~/.shelbi/— no database. A task is just a markdown file with frontmatter (column,branch,depends_on, …); move it between Kanban columns from the TUI or by editing the file in your editor. -
Review and merge without leaving the terminal. When a worker finishes, its card lands in a
Ready for Reviewqueue. Activating it checks the branch out on the machine that ran the task and spawns a fresh agent pane there to interrogate the diff; approve to merge into the default branch, or push and open a PR with--pr. The whole loop — dispatch, watch, review, merge — stays in one two-pane TUI.
Where OpenHands excels
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It brings its own agent — and a strong one. If you don't already have an agent CLI you trust, OpenHands hands you the CodeAct agent out of the box. It's among the strongest open agents on SWE-bench Verified — independent reviews cite roughly 72% with Claude Sonnet 4.5, with higher figures on newer models and pass@k. Shelbi deliberately ships nothing here; it assumes you bring your own.
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A real sandboxed execution environment. OpenHands runs the agent inside an isolated runtime (Docker, Apptainer, or remote) complete with an in-sandbox VS Code IDE, a VNC desktop, and a persistent Chromium browser, plus an optional action-confirmation gate and security analysis before risky commands run. Shelbi delegates isolation to git worktrees and to your agent CLI's own safeguards; it does not sandbox execution itself.
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Org-wide automation and a GUI for non-terminal users. OpenHands Cloud and the Agent Canvas add scheduled and event-triggered automation wired into Slack, GitHub, Jira, Linear, Notion, and HubSpot, a browser GUI, and an enterprise tier with SSO and VPC self-hosting. Shelbi is a terminal tool with no hosted SaaS, no GUI, and no per-seat tier.
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Deterministic replay and self-verification. Because every action and observation is an immutable event, OpenHands can replay and recover runs deterministically, and its 2026 Verification Stack layers critic models so the agent catches its own mistakes before producing output. Shelbi has no equivalent agent-level verification layer — that responsibility lives with the agent you plug in.
Choose Shelbi if…
You live in the terminal, already run an agent CLI you trust, and want to run many of them at once across the machines you already own — each task isolated on its own branch, all state in plain files you can read, with no servers to stand up and no per-seat bill.
Choose OpenHands if…
You want a capable autonomous agent and the sandbox to run it in without assembling your own; you need org-wide automation triggered from Slack or Jira, or a browser GUI for teammates who don't live in a terminal; or you want enterprise SSO and VPC self-hosting with a support SLA, deterministic replay, and built-in verification.