When should I avoid using parallel agents?

Avoid parallel dispatch when tasks have shared state, sequential dependencies, or when fixing one issue is likely to resolve the others.

How do I prevent agents from interfering with each other?

Ensure each agent has a strictly defined scope, such as a specific file or subsystem, and clear constraints about which files they are allowed to modify.

What is the main benefit of dispatching parallel agents?

It saves significant time by allowing multiple independent investigations or fixes to happen simultaneously rather than waiting for one agent to finish before starting the next.

Do I need to manually review the work of parallel agents?

Yes, the pattern includes a critical integration step to verify that the independent fixes do not conflict and that the full test suite remains green after all changes are applied.

Parallel Agent Dispatcher

Name: Parallel Agent Dispatcher
Author: pur3v4d3r

bypur3v4d3r

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Productivity & Workflow

Accelerates development by orchestrating multiple AI agents to solve independent bugs, test failures, or system tasks concurrently.

About

This skill provides a structured framework for parallelizing complex debugging and maintenance tasks within Claude Code. By identifying independent problem domains—such as unrelated test failures or isolated subsystem bugs—it allows users to dispatch multiple specialized agents to work in parallel rather than sequentially. This approach significantly reduces investigation time, maintains a tight focus for each agent, and prevents context leakage between unrelated issues, making it ideal for large-scale codebases with diverse maintenance needs.

Key Features

1 GitHub stars
Structured prompt templates for focused agent tasks
Independent domain identification for parallel processing
Conflict-free integration patterns for multi-agent output
Decision logic for choosing between sequential and parallel dispatch
Concurrent execution of multiple debugging workstreams

Use Cases

Investigating independent bugs in separate subsystems at the same time
Fixing multiple unrelated test failures across different files simultaneously
Speeding up large-scale refactoring tasks that do not share state

About

Key Features

1 GitHub stars
Structured prompt templates for focused agent tasks
Independent domain identification for parallel processing
Conflict-free integration patterns for multi-agent output
Decision logic for choosing between sequential and parallel dispatch
Concurrent execution of multiple debugging workstreams

Use Cases

Investigating independent bugs in separate subsystems at the same time
Fixing multiple unrelated test failures across different files simultaneously
Speeding up large-scale refactoring tasks that do not share state