agent-launcher, Domain Orchestrator

Every session starts with a goal, one sentence for one CMA. This orchestrator reads that goal, routes to the right phase, and compiles the goal into a loop or a workflow. Heavy intake stays in the forked context; the parent gets a digest.

Inspired by Anthropic's launch-your-agent reference skill (Apache-2.0). This is an independent re-implementation; CMA semantics come from ../../references/cma-primitives.md.

The through-line: the session goal

State lives at ./my-agent/goal.json (the user's folder). Manage it with goal_state.py (init / set / status / advance), it also backs the /cs-goal command and the opt-in SessionStart hook. The goal's phase selects the lane; the phase + recurrence selects the loop shape.

Routing (deterministic)

Run the router, then act on its exit code:

python3 scripts/goal_router.py --out-dir ./my-agent
# exit 0 ROUTE  -> fork to the named phase sub-skill
# exit 3 ASK    -> ask the one printed forcing question, then re-route
# exit 4 REFUSE -> goal too vague; get one sentence, then re-route

Lane (phase)	Sub-skill	Loop/workflow
interview	interview	single-pass workflow
stage-launch	stage-launch	single-pass workflow
grade-iterate	grade-iterate	bounded grade→iterate loop
run-without-you	run-without-you	recurring cron deployment loop
wrap-up	wrap-up	,

Compile the loop

python3 scripts/loop_compiler.py \
  --out-dir ./my-agent --max-iterations 5 --cron "0 9 * * *" --timezone Europe/Berlin --nest-outcome

loop_compiler.py emits plan.v1: single-pass, grade-iterate (always with a max_iterations cap 1..20), or cron-loop (optionally nesting a self-grading outcome per firing). See ../../references/loops-and-workflows.md.

Pre-flight gates (hard refusals)