AutoMaxFix vs Unspaghettit

AutoMaxFix and Unspaghettit 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.

AutoMaxFix

AutoMaxFix runs a detect-reproduce-repair loop: it watches for test failures or runtime drift, surfaces one ticket at a time, lets an AI agent propose a patch, and stops cold until a human approves it. That deliberate stop is the point. The vendor describes it explicitly as 'the boring opposite of an autonomous agent' — one ticket, one patch attempt, one approval, one report. Every fix is logged with provenance so you can trace what changed and why. The ceiling arrives fast: the tool handles one ticket per execution, so teams running parallel failure streams will need external orchestration to manage the queue.

Unspaghettit

Orbit wraps each coding-agent invocation in a bounded loop: it selects a dependency-ordered task from a backlog, runs the agent, then gates advancement on passing tests, lint, and type checks — not on the agent's self-report. Every run writes structured JSON artifacts and a human-readable progress log, so you can inspect what changed and why a task closed or stalled. The deterministic replay demo runs without an API key, which means you can verify the harness behavior before committing any agent credits. The ceiling appears when your workflow needs anything beyond CLI-compatible agents — there is no API and no visual interface.

Attribute	AutoMaxFix	Unspaghettit
Pricing	Free	Free
Free trial	No	No
Open source	Yes	Yes
Has API	No	No
Self-hosted option	Yes	Yes
Platforms	Linux, macOS, Windows (Python 3.11+)	Linux, macOS, Windows (Python-based)
Pros	Human approval gate is structural, not configurable — patches cannot merge without explicit sign-off, so teams using AI coding agents have a documented decision point for every change rather than discovering autonomous commits after the fact. Fix provenance logging means every patch carries a record of what triggered it, what the agent proposed, and who approved it, so a post-incident audit does not require reconstructing context from git blame and Slack history. Single-ticket, single-patch execution model keeps the blast radius of any one repair attempt contained — a bad patch attempt does not cascade into a queue of subsequent changes built on a broken base. MIT-licensed and self-hosted, so the tool runs inside your existing infrastructure without routing code or failure telemetry through a third-party cloud, which matters when the codebase contains proprietary logic. Test failure and runtime drift detection in one loop means the tool catches failures that show up after deployment — not just the ones CI catches before it — so drift that accumulates quietly in production is surfaced before it compounds.	Proof-gated task closure — tests, lint, and type checks must pass before an orbit advances — which means you stop shipping agent output that looked correct in the diff but broke downstream. Structured JSON artifacts on every run (agent-result.json, evaluation.json, review.json, progress.md), so debugging a failed orbit means reading a file rather than reconstructing what the agent did from memory. Agent-neutral adapter contract, so you can run Claude and Codex against the same task backlog and compare evaluation scores instead of arguing from anecdotes. Deterministic replay demo requires no API key, which means the harness itself is verifiable in CI before any live agent is connected — reducing the risk of paying for agent credits on a broken setup. Dependency-aware backlog selection keeps each agent invocation scoped to one task, which means you avoid the compounding errors that come from letting an agent chain across unverified intermediate states.
Cons	Single-ticket-per-execution is a hard architectural limit: when multiple tests fail simultaneously or a deploy surfaces a cascade of issues, there is no built-in queue. Teams with parallel failure streams have to wrap the CLI in their own orchestration layer, which means they are now maintaining that glue code. No hosted option, no webhook integration, and no multi-user approval UI means the approval gate is a local CLI prompt — functional for a solo developer or a small team running in the same terminal session, but not viable for a distributed team that needs asynchronous review. Teams that need a browser-based approval workflow or Slack-integrated sign-off will need to build that integration themselves or move to a different toolchain. At 16 commits with pull requests still open, the documented integration surface is thin. Teams cannot assume the examples directory covers their CI/CD setup — expect to read source code to understand behavior at the edges, and expect the API surface to shift before it stabilizes.	Orbit requires agents that speak JSON over CLI. Agents with proprietary APIs, browser-based interfaces, or non-CLI outputs cannot be connected without writing a custom adapter — a task the docs acknowledge but leave entirely to the contributor. There is no hosted option, no REST API, and no web interface. Teams that need to hand off agent monitoring to non-engineering stakeholders, integrate Orbit into an existing SaaS workflow, or run it without local infrastructure have no path forward within the current scope. The harness assumes a test suite exists and is the source of truth for correctness. Repositories without meaningful test coverage get validation gates that pass trivially, which defeats the proof model entirely — at that point teams are back to trusting agent self-reports. Teams that need agents running in parallel across multiple tasks, conditional branching based on intermediate outputs, or cross-agent handoffs will hit the single-orbit-at-a-time design ceiling quickly. When that happens, the documented response is to build on top of Orbit or move to a more full-featured orchestration layer — at which point Orbit becomes a sub-component rather than the primary harness.

Bottom line

AutoMaxFix and Unspaghettit are closely matched on pricing model, openness, and API availability — pick by feature set and platform support in the table above.

Frequently asked questions

What is the difference between AutoMaxFix and Unspaghettit?

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

Is AutoMaxFix better than Unspaghettit?

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.