← ClaudeAtlas

orchestrating-parallel-worklisted

Orchestrates parallel execution of AI agents with dependency analysis and batch scheduling. Use when coordinating multiple concurrent tasks, optimizing task ordering, or when multiple independent agents would benefit the workflow.
dork-labs/dorkos · ★ 8 · AI & Automation · score 71
Install: claude install-skill dork-labs/dorkos
# Orchestrating Parallel Work ## Overview This skill provides patterns for coordinating parallel subagent execution in Claude Code workflows. Apply these patterns when tasks can run simultaneously without interdependencies — parallel fan-out saves wall-clock time and keeps large intermediate output out of the main context. ## When to Use - Launching multiple research or exploration agents - Implementing features with independent subtasks - Running diagnostics that check multiple layers - Processing batch operations with dependency graphs - Any workflow where "wait for A, then start B" isn't required ## Key Mechanics The **`Agent` tool** spawns a subagent with its own isolated context: - **Parallel launch**: to run agents concurrently, send multiple `Agent` calls in a **single message**. Each call takes `description`, `prompt`, and `subagent_type`. - **Results**: the agent's final message comes back as the tool result. It is not shown to the user — relay what matters. - **Background mode**: `run_in_background: true` returns immediately; the main conversation continues and completion arrives as an automatic task notification. No polling API exists — you are re-invoked when the agent finishes. - **Follow-ups**: `SendMessage` (addressed by the agent's ID or name) continues a previously spawned agent with its context intact. A fresh `Agent` call starts from zero. - **Isolation**: `isolation: "worktree"` gives an agent its own git worktree — required when parallel agents mut