swarmlisted

# /swarm — Ad-hoc parallel task executor ## Host dispatch contract - Codex: `$skill`, Codex collaboration roles, and GPT-5.6 tiers. - Claude: `/skill`, Agent/Skill tools, and Claude aliases. - A bare `/skill` in this shared source denotes the Claude form; Codex dispatches the same named skill as `$skill`. One command. Pass task descriptions, get model classification, parallel execution, and a structured result. No spec pipeline, no `.planning/` prerequisite. ## When to invoke - "swarm these tasks", "run these in parallel", "do all of these" - Multi-task batch execution without the full spec pipeline - Quick automation: lint + test + docs + cleanup at once For anything that IS a feature (multi-phase, TDD, ship tail): use `/feature-implement` — the gsd loop owns that shape. ## Invocation ``` /swarm "task1" "task2" "task3" # classify + execute /swarm --tasks-file PATH # md checklist or one-per-line /swarm ... --dry-run # print annotated plan, don't execute /swarm ... --sequential # serial execution /swarm ... --model-request '{"kind":"tier","name":"judgment"}' ``` ## Workflow ### Step 1: Classify Per task, assign a typed workload request: volume for mechanical/search, execution for default development, judgment for architecture/security/review. Resolve through the active host and mark `[P]` when tasks share no files and no ordering dependency. ### Step 2: Execute - `[P]` groups → concurrent host-native subagent calls in one wav