Collie vs Hanesu

Collie and Hanesu 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.

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.

Hanesu

The project borrows from Harness Engineering principles: work is broken into phases with task files, role handoffs, quality gates, and progress artifacts written to disk. Agents using runtimes like OpenCode, Codex, or Claude Code run through that structure rather than a monolithic prompt. The vendor explicitly flags this is not for small, obvious edits — a direct prompt is faster there. Where it earns its place is multi-step refactors, security-sensitive changes, or bugfix workflows where you need the agent to stop, surface what it found, and wait for your sign-off before proceeding.

Attribute	Collie	Hanesu
Pricing	Free	Free
Free trial	No	No
Open source	Yes	Yes
Has API	No	No
Self-hosted option	Yes	Yes
Platforms	Windows, macOS, Linux	npm, GitHub
Pros	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.	Phase-gated workflow structure means the agent stops and surfaces findings before writing code, so risky refactors don't reach your codebase without a checkpoint you signed off on. Artifact writing is built into each phase, so decision records and discovery outputs are committed alongside the code change — teams doing security audits or post-incident reviews have a documented trail rather than a reconstructed chat log. MIT license and local repo installation means no external service dependency and no data leaving your environment, which removes the approval friction that blocks adoption in regulated or air-gapped codebases. Works alongside existing agent runtimes rather than replacing them, so teams already invested in OpenCode, Codex, or Claude Code don't have to abandon their toolchain to add structured workflow control.
Cons	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.	For tasks that are small or well-defined, the phase and artifact overhead slows the agent down relative to a single direct prompt — the tool's own docs acknowledge this, but teams will still burn time learning where that line sits in their specific codebase. The project carries 2 stars and 4 commits at the time of curation; there is no issue tracker activity and no documented community — teams hitting an undocumented edge case in the gate logic have no support channel beyond reading the source code themselves. Hanesu has no API and no integration surface beyond local repo files, so any team that needs to tie agent workflow state into CI pipelines, ticketing systems, or deployment gates will have to build that plumbing from scratch — at which point they are maintaining the workflow layer Hanesu provides plus the integration layer it doesn't, and a more mature agent orchestration platform becomes the faster path.

Bottom line

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

Frequently asked questions

What is the difference between Collie and Hanesu?

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

Is Collie better than Hanesu?

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.

Collie vs Hanesu: which should I pick?

Pick Collie if its pricing model, openness, or platform fit matches your constraints; pick Hanesu 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.