← 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 · ★ 4 · AI & Automation · score 74
Install: claude install-skill dork-labs/dorkos
# Orchestrating Parallel Work ## Overview This skill provides patterns for coordinating parallel agent execution in Claude Code workflows. Apply these patterns when tasks can run simultaneously without interdependencies, achieving 3-6x speedup and 80-90% context savings. ## 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 Concepts ### Background Agents Agents launched with `run_in_background: true` execute in isolated context. The main conversation continues while they work. ``` task = Task( description: "Describe what agent does", prompt: "Detailed instructions", subagent_type: "agent-type", run_in_background: true ) # Returns immediately with task.id ``` ### Collecting Results Use `TaskOutput` to wait for completion: ``` result = TaskOutput(task_id: task.id, block: true) # Wait for completion status = TaskOutput(task_id: task.id, block: false) # Check without waiting ``` ### Task Dependencies Use `TaskUpdate` to set up dependencies between tasks: ``` TaskUpdate({ taskId: childTask.id, addBlockedBy: [parentTask.id] }) ``` ## Decision Logic ### Should I Parallelize? Ask these questions: 1. **Are tasks independent?** → If no, use sequential 2. **Will each task take >30 seconds?** → If no, sequential might be fas