Patterns for parallel subagent execution using Task tool with run_in_background. Use when coordinating multiple independent tasks, spawning dynamic subagents, or implementing features that can be parallelized.
npxskills add cloudai-x/claude-workflow-v2--skill parallel-executionLoading…
Parallel execution spawns multiple subagents simultaneously using the Task tool with run_in_background: true. This enables N tasks to run concurrently, dramatically reducing total execution time.
Critical Rule: ALL Task calls MUST be in a SINGLE assistant message for true parallelism. If Task calls are in separate messages, they run sequentially.
Before spawning, verify tasks are independent:
Each subagent receives a custom prompt defining its role:
You are a [ROLE] specialist for this specific task.
Task: [CLEAR DESCRIPTION]
Context:
[RELEVANT CONTEXT ABOUT THE CODEBASE/PROJECT]
Files to work with:
[SPECIFIC FILES OR PATTERNS]
Output format:
[EXPECTED OUTPUT STRUCTURE]
Focus areas:
- [PRIORITY 1]
- [PRIORITY 2]
CRITICAL: Make ALL Task calls in the SAME assistant message:
I'm launching N parallel subagents:
[Task 1]
description: "Subagent A - [brief purpose]"
prompt: "[detailed instructions for subagent A]"
run_in_background: true
[Task 2]
description: "Subagent B - [brief purpose]"
prompt: "[detailed instructions for subagent B]"
run_in_background: true
[Task 3]
description: "Subagent C - [brief purpose]"
prompt: "[detailed instructions for subagent C]"
run_in_background: true
After launching, retrieve each result:
[Wait for completion, then retrieve]
TaskOutput: task_1_id
TaskOutput: task_2_id
TaskOutput: task_3_id
Combine all subagent outputs into unified result:
When you have N tasks to implement, spawn N subagents:
Plan:
1. Implement auth module
2. Create API endpoints
3. Add database schema
4. Write unit tests
5. Update documentation
Spawn 5 subagents (one per task):
- Subagent 1: Implements auth module
- Subagent 2: Creates API endpoints
- Subagent 3: Adds database schema
- Subagent 4: Writes unit tests
- Subagent 5: Updates documentation
Analyze multiple directories simultaneously:
Directories: src/auth, src/api, src/db
Spawn 3 subagents:
- Subagent 1: Analyzes src/auth
- Subagent 2: Analyzes src/api
- Subagent 3: Analyzes src/db
Review from multiple angles simultaneously:
Perspectives: Security, Performance, Testing, Architecture
Spawn 4 subagents:
- Subagent 1: Security review
- Subagent 2: Performance analysis
- Subagent 3: Test coverage review
- Subagent 4: Architecture assessment
When using parallel execution, TodoWrite behavior differs:
Sequential execution: Only ONE task in_progress at a time
Parallel execution: MULTIPLE tasks can be in_progress simultaneously
# Before launching parallel tasks
todos = [
{ content: "Task A", status: "in_progress" },
{ content: "Task B", status: "in_progress" },
{ content: "Task C", status: "in_progress" },
{ content: "Synthesize results", status: "pending" }
]
# After each TaskOutput retrieval, mark as completed
todos = [
{ content: "Task A", status: "completed" },
{ content: "Task B", status: "completed" },
{ content: "Task C", status: "completed" },
{ content: "Synthesize results", status: "in_progress" }
]
Good candidates:
Avoid parallelization when:
| Approach | 5 Tasks @ 30s each | Total Time |
|---|---|---|
| Sequential | 30s + 30s + 30s + 30s + 30s | ~150s |
| Parallel | All 5 run simultaneously | ~30s |
Parallel execution is approximately Nx faster where N is the number of independent tasks.
User request: "Implement user authentication with login, registration, and password reset"
Orchestrator creates plan:
Parallel execution:
Launching 5 subagents in parallel:
[Task 1] Login endpoint implementation
[Task 2] Registration endpoint implementation
[Task 3] Password reset endpoint implementation
[Task 4] Auth middleware implementation
[Task 5] Integration test writing
All tasks run simultaneously...
[Collect results via TaskOutput]
[Synthesize into cohesive implementation]
Tasks running sequentially?
run_in_background: true is set for eachResults not available?
Conflicts in output?
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