Orchestra runs AI agent pipelines on your GitHub repos. Plan, implement, review, and merge, each stage gated by verifiers.
Start a run from a GitHub issue. The Orchestrator writes a briefing for each stage, dispatches a specialist agent, and only advances when the stage's verifier passes.
An engineer agent reads the issue and opens a pull request carrying the implementation plan.
The agent pushes the change onto the plan's PR, behind the repo's build and test gates.
A reviewer on a different provider files findings. Rejected work loops straight back to implement.
The Orchestrator merges the pull request once every gate has passed, and keeps the evidence.
Review findings loop the run back to implement until the reviewer approves. Every briefing, dispatch, and verdict lands in an append-only decision log.
Each stage is dispatched to a role-specific agent with its own briefing, skills, and model, running on Claude Code, Codex, or OpenCode.
Standard Change, Quick, Advanced Feature, and Investigation ship built in. Clone one, then edit stages, roles, and gates per project.
A stage is complete when its verifier says so, not when the agent does.
Install skills, agents, hooks, MCP servers, and rules per project. They materialize into the agent's worktree at launch.
Every session runs Claude Code, Codex, or OpenCode inside its own Docker container. Watch, stop, or restart the whole fleet.
An append-only decision log, live session activity, and per-run cost, kept for every run your team starts.
Connect a repo, pick a pipeline, and start your first run.