Skills vs Unspaghettit

Skills 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.

Skills

Orbit is a CLI harness that wraps any JSON-speaking coding agent — Claude, Codex, Cursor, or your own — in a bounded loop: one task selected from a dependency-ordered backlog, executed by the agent, then checked against tests, lint, and type validation before the orbit closes. If the agent cannot prove the work, the run does not advance. Every orbit writes structured JSON artifacts and a human-readable progress log, so you are reviewing evidence rather than re-reading diffs and guessing. The harness runs entirely locally, requires no API key for the replay demo, and is MIT licensed. Where it breaks: teams whose validation needs go beyond tests and lint — custom scoring rubrics, multi-step human approval workflows, or large parallel backlogs — will find the intentionally small surface area a ceiling rather than a feature.

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	Skills	Unspaghettit
Pricing	Free	Free
Free trial	No	No
Open source	Yes	Yes
Has API	No	No
Self-hosted option	Yes	Yes
Platforms	Cross-platform (Python 3.6+)	Linux, macOS, Windows (Python-based)
Pros	Validation gates block an orbit from closing unless tests, lint, and type checks pass, so you stop merging agent output that ran without error but failed to do what the task required. Four structured artifacts per run — result, evaluation, review recommendation, and a progress log — give you an auditable evidence trail, so post-mortem debugging is reading JSON rather than reconstructing what the agent did from git history. Agent-neutral CLI contract means you can run Claude and Codex against the same task and backlog, comparing scored artifacts directly instead of running separate experiments with incomparable outputs. Dependency-ordered backlog selection keeps each orbit focused on one task at a time, so the agent cannot silently absorb scope from adjacent work and produce diffs that are hard to attribute. MIT licensed with a no-API-key replay demo, so you can evaluate the full validation loop against a real artifact chain without committing credentials or incurring cost.	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	Validation is limited to tests, lint, and type checks as described on the vendor page — teams whose definition of 'done' includes semantic correctness, security scanning, or domain-specific rules have to build that checking outside the harness and wire it in manually, adding a second system to maintain. The harness executes one orbit at a time; teams running large backlogs where tasks are independent and could parallelize will hit a throughput ceiling and move to a more capable orchestration layer or build parallelism themselves. There is no built-in multi-step human approval workflow beyond the accept/iterate/stop recommendation in `review.json` — teams that need a formal sign-off gate before code advances to staging will need to script that around the harness or switch to a tool that treats human review as a first-class execution step.	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

Skills 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 Skills and Unspaghettit?

Skills 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 Skills 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.