What problem does it solve? Working a repo's issue queue one task at a time in a single long thread is slow and error-prone: parallel workers clobber each other's files, uncapped jobs can OOM-kill every session on the machine, and progress reporting scatters across messages. This Skill turns the agent into a dispatcher that splits the queue into safe parallel lanes, spawns one subagent per task, and keeps a live Running / Planned / Done panel pinned to the terminal. ## Core Features & Use Cases - Queue triage and lane splitting: Reads the GitHub Projects board in one GraphQL call, skips Blocked/Review/backlog items, and groups surviving tasks by the file paths they touch so disjoint work runs in parallel and shared paths run serially. - Memory-budgeted workers: Every heavy job runs under systemd-run with MemoryMax and MemorySwapMax=0 cgroup caps sized from measured peaks, so an overrun kills only that job instead of the whole session tree. - Live status panel and report footer: The orchestrate-status tool renders a pinned Running / Planned / Done table with per-worker token counts, countdown ETAs, and clickable transcript links, then prints the same table as the final report footer. - Use Case: Given five open issues on the yajna repo, run a pass that works three of them simultaneously in separate subagents — each with its own path ownership, model, and memory cap — verifies and commits their results by path, and closes with a priced backlog and a full timing report. ## Quick Start Invoke /orchestrate to work this repo's issue queue as a dispatcher with parallel subagents and a pinned status panel.