Baton vs Collie

Baton and Collie are both cli coding agents tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Baton

Baton sits in your menu bar and polls the signals your machine already produces — no manual logging, no clipboard tricks — to show you which AI coding sessions are mid-run and which have handed the decision back to you. The core metaphor is the 🎽 icon: the baton is with the agent, or it's with you. Click the menu, see the queue, jump straight to the session that needs a response. This is a local Python app, MIT-licensed, installed via a shell script, and it runs entirely on your machine. It works with Claude Code and Codex threads on macOS — nothing else, and no roadmap to something else is documented.

Collie

Collie is a local, open-source coding agent that operates directly on your machine — your file system, your signed-in browser session, your real terminal. The core loop is: you describe the task in plain language, Collie does the actual work, then writes a verification step and runs it before declaring the job complete. That proof-first model is what separates it from a chat assistant. It installs as a desktop app on Windows and macOS, or via a single pip command on Linux. No telemetry, no cloud relay — your files and credentials stay local.

Attribute	Baton	Collie
Pricing	Free	Free
Free trial	No	No
Open source	Yes	Yes
Has API	No	No
Self-hosted option	Yes	Yes
Platforms	macOS	Windows, macOS, Linux
Pros	Reads session state from signals your machine already emits with no manual tagging required, so you skip the meta-work of tracking the tracker. Menu bar presence gives you persistent ambient visibility without opening a separate app, which means a stalled session doesn't stay hidden behind a terminal window you forgot about. Click-to-jump navigation takes you directly from the status view to the waiting session, so the time between 'agent is blocked' and 'you respond' shrinks to a single click rather than a tab hunt. MIT license and local-only architecture mean no data leaves your machine and no subscription gates the feature set — the thing you install on day one is the complete tool. Install script handles dependency setup, so the gap between 'found this on GitHub' and 'running in my menu bar' is a single shell command.	Runs against your real browser session and signed-in accounts, so tasks like pulling data from a portal or filling a form work without re-authentication or credential sharing with a third party. Writes and runs a verification step before calling a task complete, which means you get a passing test as proof of a bug fix rather than a diff you have to validate yourself. No telemetry and no cloud relay — your source code, files, and session credentials stay on your machine, so it fits workflows where data cannot leave the local environment. One-click desktop install on Windows and macOS with no admin rights required, so setup does not block a developer who lacks elevated permissions on a managed machine. MIT-licensed and self-hosted, so you can inspect the source, fork it, or audit what it does — which matters when you are handing an agent access to your file system and browser.
Cons	macOS is a hard requirement with no documented workaround — developers on Linux or Windows cannot run this at all, and teams with mixed environments need a different solution from day one. Support is scoped to Claude Code and Codex; the moment your workflow adds a third agent type — say, a custom LangChain runner or a Cursor session — Baton goes dark on that thread and you're back to manual tracking for part of your stack. There is no shared or team-facing view: status is visible only to the person running the local app, so any team that needs collective awareness of which agents are blocked across multiple developers has to maintain a separate coordination layer. Zero API surface means you cannot pipe Baton's session state into a dashboard, alert system, or ticketing tool — teams that want agent status wired into their existing ops tooling have to instrument that themselves from scratch or switch to a tool built for integration.	No API surface exists, so you cannot trigger Collie from a script, a CI job, or an external scheduler — any team that needs to embed AI task execution inside an automated pipeline will have to run it interactively or switch to an agent framework that exposes a callable interface. Linux installation requires Python 3.12 or later and a pip install from GitHub; teams on managed Linux environments where Python version is locked by policy will need to resolve that dependency before anything runs. The tool is scoped to single-session, single-machine operation with no documented multi-agent coordination — workflows that need parallel agents handing off between steps are outside what the current architecture supports, and teams building those patterns will move to a framework designed for it.

Bottom line

Baton runs on macOS; Collie on Windows, macOS, Linux. Pick the difference that actually blocks you.

Frequently asked questions

What is the difference between Baton and Collie?

Baton is Free and open source, while Collie is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Baton better than Collie?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.

Baton vs Collie: which should I pick?

Pick Baton if its pricing model, openness, or platform fit matches your constraints; pick Collie otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.