BMAD-METHOD/samples/sample-custom-modules/cc-agents-commands/commands/parallelize.md

description	prerequisites	argument-hint	allowed-tools
Parallelizes tasks across sub-agents	—	<task_description> [--workers=N] [--strategy=auto|file|feature|layer|test|analysis]	Task TodoWrite Glob Grep Read LS

Parallelize the following task across independent agents: $ARGUMENTS

Task Analysis

Parse the arguments and understand the parallelization requirements:

• Extract any --workers=N option to guide agent count
• Extract any --strategy=TYPE option (or auto-detect from task content)
• Identify the core work to be parallelized

Strategy Detection

Analyze the task to determine the best parallelization approach:

• File-based: Task mentions file patterns (.js, .py, .md) or specific file/directory paths
• Feature-based: Task involves distinct components, modules, or features
• Layer-based: Task spans frontend/backend/database/API architectural layers
• Test-based: Task involves running or fixing tests across multiple suites
• Analysis-based: Task requires research or analysis from multiple perspectives

Work Package Creation

Divide the task into independent work packages based on the strategy:

For file-based tasks:

• Use Glob to identify relevant files
• Group related files together (avoid splitting dependencies)
• Ensure agents don't modify shared files

For feature-based tasks:

• Identify distinct features or components
• Create clear boundaries between feature scopes
• Assign one feature per agent

For layer-based tasks:

• Separate by architectural layers (frontend, backend, database)
• Define clear interface boundaries
• Ensure layers can be worked on independently

For test-based tasks:

• Group test suites by independence
• Separate unit tests from integration tests when beneficial
• Distribute test execution across agents

For analysis-based tasks:

• Break analysis into distinct aspects or questions
• Assign different research approaches or sources to each agent
• Consider multiple perspectives on the problem

Agent Execution

Launch multiple Task agents in parallel (all in a single message) using subagent_type="parallel-executor".

Best practices:

• Send all Task tool calls in one batch for true parallelization
• Give each agent clear scope boundaries to avoid conflicts
• Include specific instructions for each agent's work package
• Define what each agent should NOT modify to prevent overlaps

Typical agent count:

• Simple tasks (1-2 components): 2-3 agents
• Medium tasks (3-5 components): 3-4 agents
• Complex tasks (6+ components): 4-6 agents

Each agent prompt should include:

• The specific work package it's responsible for
• Context about the overall parallelization task
• Clear scope (which files/components to work on)
• Constraints (what NOT to modify)
• Expected output format

Result Synthesis

After agents complete:

• Collect and validate each agent's results
• Check for any conflicts or overlaps between agents
• Merge findings into a coherent summary
• Report on overall execution and any issues encountered