team-swarm

<required_reading> @~/.maestro/workflows/run-mode-lite.md </required_reading> # Team Swarm Orchestrate ant-colony-style exploration over a user-defined task space. **Hybrid coordinator**: LLM handles task translation + worker spawning; Python script owns all numeric decisions (selection / pheromone update / convergence). Universal — task space and scoring rule come from `swarm-config.json`. ## Architecture ``` Skill(skill="team-swarm", args="task description") | SKILL.md (this file) = Router | +--------------+--------------+ | | no --role flag --role <name> | | Coordinator Worker roles/coordinator/role.md roles/<name>/role.md | +-- Phase 1: gen swarm-config +-- Phase 2: init --> Bash: scripts/aco.py init +-- Phase 3: iterate (K rounds, each = spawn-and-stop) | | | +-- Bash: aco.py select --iter k -> N assignments | +-- Spawn N x team-worker(ant) | +-- [callback when all ants done] | +-- (optional) Spawn team-worker(scorer) | +-- Bash: aco.py update --iter k | +-- Bash: aco.py converged | +-- branch: loop k+1 OR Phase 4 | +-- Phase 4: converge --> Bash: aco.py report -> Spawn team-worker(analyst) -> best-solution.md ``` ## Role Registry | Role | Path | Prefix | Inner Loop | |--...