execute-fleet

# execute-fleet Atlas Fleet is the premium parallel sibling of `execute-task`. It keeps the same proof discipline, but the orchestrator owns the scoreboard while workers only build inside isolated worktrees. ## Hard Gates Before the first wave, all gates must pass. If any gate fails, report the gap and stop; do not fall back to solo execution from inside this skill. 1. `mcp__plugin_prd_go__detect_capabilities()` reports `tier: "premium"` and atlas-launcher MCP registration/aliveness. 2. `mcp__atlas-launcher__inbox_read` is callable for this session. 3. `.taskmaster/tasks/tasks.json` exists. 4. `.taskmaster/reports/task-complexity-report.json` exists. 5. `git status --short` is empty. Fleet starts only from a committed base. 6. The integration branch policy is clear: use `fleet-integration`; main is never auto-touched. **SOLE-WRITER RULE:** only this orchestrator writes `.taskmaster/tasks/tasks.json` and `.atlas-ai/state/pipeline.json`. Workers must never edit those files. The orchestrator may update task state only through TaskMaster or the plugin pipeline MCP, and only after verification. ## Wave Loop Repeat until no runnable tasks remain: 1. Call `mcp__plugin_prd_go__compute_fleet_waves(concurrency=<N>, tag=<tag>)`. Use the returned frontier as the only dispatch source. If it reports a deadlock, render status, mark the blocked set, and stop dispatching those tasks. 2. For each chunk in the current wave, spawn exactly one worker: `mcp__atlas-launcher__...