Clixad
Freemium
Developers who prefer terminal workflows
Most multi-agent coding setups dissolve between sessions — context evaporates, lessons learned get re-learned, and you start the next sprint from scratch. Legioni is an open-source agent team built on top of opencode that holds that context, coordinates specialist agents, and loops until the tests actually pass.
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.
Bottom line: Pick Legioni if your team already runs opencode and needs a structured, session-persistent agent loop for test-driven coding tasks; skip it if your stack is built around any other AI coding runtime, because there is no migration path.
Find your fit
More options in CLI Coding Agents. Compare pricing, platforms, and features side by side.
Freemium
Developers who prefer terminal workflows
Freemium
Developers preferring fully local agent execution
Legioni installs as an npm package and attaches to opencode as a team of coordinated coding agents. After running `legioni init` in a project directory — which detects the stack and compiles the agents — you address the orchestrator directly in opencode with a plain-language task. The orchestrator plans the work, routes subtasks to specialist agents (architect, implementer, reviewer, test-strategist), and loops until the tests pass. You watch the handoffs happen; you do not manually wire the pipeline.
The differentiating mechanism is lesson promotion. As agents complete tasks, the system allows teams to promote learned behaviors — patterns, constraints, project-specific rules — into persistent agent configuration. This means the agents on your third project carry the institutional knowledge from your first two, rather than starting from a blank context every time. For teams iterating on the same codebase across multiple sessions, this is the feature that separates Legioni from a one-shot code-generation prompt.
Legioni fits cleanly on a single-developer or small-team project where opencode is already the chosen coding environment and the goal is structured, test-verified iteration. It breaks down when the team needs to operate outside opencode — the docs describe no API surface, no webhook integration, and no adapter layer for other runtimes. The project’s GitHub page shows five commits and a star count in the single digits, which is accurate signal for where it sits on the maturity curve: functional, early, and not yet battle-tested at team scale.
Installation requires Node.js and a global npm install for the full feature set (promote, install, upgrade-team commands); `npx legioni init` works for one-off initialization without a global install. The agent workflow is defined as: orchestrator → architect → plan.md → implementer → code + tests → reviewer → passes or fails → test-strategist → edge cases + full suite → done.
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