Legioni vs WinkTerm

Legioni and WinkTerm 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.

Legioni

The orchestrator receives a plain-language task in opencode, breaks it down, and hands it to a chain of specialist agents — architect, implementer, reviewer, test-strategist — in sequence. Each step feeds the next; the loop closes only when tests pass. The 'lesson promotion' mechanism lets teams encode what they learn into persistent agent behavior, so the same mistake doesn't resurface two projects later. The hard boundary: Legioni runs inside opencode, full stop. If your team is not already on opencode or cannot adopt it, the architecture is irrelevant — there is no standalone path and no API to route through a different runtime.

WinkTerm

Orbit wraps each coding-agent run in a bounded loop: one task selected from a dependency-ordered backlog, executed by whatever CLI agent you hand it, then validated through tests, lint, and type checks before the orbit closes. Every run writes structured JSON artifacts — what the agent returned, how the diff scored, whether the reviewer should accept or iterate. This is not an agent itself; it is the scaffold that keeps agents accountable. The ceiling appears when your workflow needs dynamic replanning or multi-agent coordination across parallel tasks — Orbit's contract is deliberately single-focus, and teams that outgrow that boundary are maintaining a layer above the harness.

Attribute	Legioni	WinkTerm
Pricing	Free	Free
Free trial	No	No
Open source	Yes	Yes
Has API	No	No
Self-hosted option	Yes	Yes
Platforms	npm, Node.js	Linux, macOS, Windows (via Python)
Pros	Test-driven agent loop closes only when tests pass, so you are not manually checking whether the implementer's output actually works before shipping it to review. Specialist agents handle discrete roles — architecture, implementation, review, test strategy — which means a single task does not collapse into one undifferentiated prompt that loses track of constraints halfway through. Lesson promotion persists learned behaviors across sessions and projects, so teams stop re-encoding the same project rules every time they open a new task. Zero-install path via npx means you can run `legioni init` in a new repo without touching your global Node environment, keeping adoption friction low for the first experiment. MIT license and self-hosted operation mean the agents run entirely within your environment — no usage data leaves to a vendor API beyond whatever opencode itself sends.	Validation gates (tests, lint, type checks) block an orbit from closing until the agent proves the work passed, so you stop shipping diffs that look correct but break the suite. Four structured artifact files per run — agent result, evaluation, reviewer recommendation, progress log — so you have a durable, inspectable record of what the agent did and how it scored, instead of a conversation history you cannot query. Agent-neutral JSON contract means you can run the same task through Claude, Codex, or Cursor and compare scored evaluation artifacts side by side, so agent selection becomes evidence-based rather than demo-based. Dependency-aware backlog selection keeps each orbit focused on one task at a time, so the agent cannot drift scope mid-run and the validation result is unambiguous. Fully self-hosted with no external API dependency for the core harness, so teams with data-residency requirements or air-gapped environments can run validated agent workflows without routing artifacts through a third-party service.
Cons	Legioni is a hard dependency on opencode: every agent, every loop, every lesson runs inside opencode's runtime. Teams on Cursor, Cline, or any other AI coding environment cannot use this tool — the only path forward is adopting opencode first, which is a separate adoption decision with its own trade-offs. The project's public repository shows five commits and a small star count, which means edge cases in the agent loop, lesson promotion conflicts, and stack detection failures are under-documented and under-reported. Teams hitting unexpected behavior have no community issue history to search and no support channel beyond filing a GitHub issue themselves. Lesson promotion is a manual, explicit action — the agents do not automatically surface or apply learned behaviors without team intervention. Projects where nobody curates the promoted lessons see no compounding benefit across sessions, which makes the core differentiating feature opt-in rather than default.	Orbit's contract is single-task and bounded by design — the moment a coding task cannot be expressed as one verifiable unit with a clear pass/fail validation suite, the orbit structure breaks down and teams are left writing wrapper logic that effectively duplicates Orbit's job at a higher level. There is no built-in parallel execution or multi-agent coordination: teams that need agents working on interdependent tasks simultaneously hit the single-orbit model's ceiling and move to a purpose-built orchestration layer, at which point Orbit either becomes a sub-component or gets replaced entirely. The adapter ecosystem depends on community contributions — the docs explicitly frame adapter development as a contributor responsibility, not a vendor roadmap item. Teams that need a production-grade adapter for a specific agent and cannot write it themselves are blocked until someone else builds and maintains it.

Bottom line

Legioni and WinkTerm 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 Legioni and WinkTerm?

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

Is Legioni better than WinkTerm?

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.