A conductor agent decomposes a plan, spawns implementers in isolated worktrees, and runs reviewers and critics over the result.
$cast install orchestration
Orchestration runs a whole plan across many agents at once. A conductor decomposes the goal into granular tasks with dependencies, spawns an implementer per ready task — each in its own isolated git worktree — then runs reviewers over completed work and critics over the integrated result. Humans watch waves of parallel work land instead of babysitting one session.
Two entry points share this machinery: the cast plan autopilot commands, and the /orchestrate skill the orchestration snippet installs.
What the snippet installs
Unlike the other snippets, orchestration installs more than a markdown section. Via the snippet system, cast install orchestration writes:
an /orchestrate skill into ~/.claude/skills/ — the conductor's playbook,
three agent definitions into ~/.claude/agents/ — implementer (does the work), reviewer (checks each task before merge), critic (sweeps the integrated result for issues),
two lifecycle hooks in ~/.claude/settings.json that fire only during orchestration runs.
Nothing activates on its own. Saying "orchestrate this plan" to an agent with the skill installed turns that agent into the conductor.
The execution model
Waves. The conductor resolves the task dependency graph topologically. Every task whose dependencies are satisfied forms the current wave; the wave runs in parallel, one agent per task; completions unlock the next wave.
Worktree isolation. Each implementer works in its own git worktree on its own branch. Parallel agents never trample each other's files; completed branches merge back to main as their tasks pass review.
Review before merge. A reviewer agent checks each completed task against its acceptance criteria and returns a verdict — pass, needs changes, or reject. Failures route back to implementation with the review attached.
Drive rounds. After the graph completes, a critic reviews the integrated codebase. Issues it finds become fix tasks, which run as a new wave. Repeat until quality converges.
Driving from the CLI
cast plan create "Build user dashboard" --goal "Activity feed, metrics, settings"
cast plan decompose pl-xxxx --depth deep # Claude breaks the goal into 20–50 tasks
cast plan show pl-xxxx # review the task list before running
cast plan autopilot pl-xxxx # the main loop: waves until done
Autopilot options bound the blast radius: --dry-run shows what would spawn, --max-agents 4 caps concurrency, --max-waves 3 stops early, --verify typechecks before merging. While it runs:
cast plan agents pl-xxxx # active agent sessions
cast plan wave pl-xxxx # current and next wave
cast plan progress pl-xxxx # ETA and breakdown by status
Failed tasks retry with escalation logging; a task that keeps failing is marked blocked and the run continues around it.
Watching it
Every agent is a real session in the inbox, so the whole apparatus is observable with the ordinary tools: the dashboard groups workers under their plan, cast sessions --label watches a fleet live, and messaging lets you — or the conductor — nudge any worker directly. Decisions made along the way land on the plan's timeline (tasks and plans), so the record of why survives the run.
Choose orchestration when the structure of the work is not known up front and a conductor should discover it. When the steps are known and must run the same way every time, write a workflow instead.