What is the main benefit of dispatching parallel agents?

The primary benefit is time efficiency; it allows you to investigate and fix multiple independent issues simultaneously instead of solving them one by one.

What is the recommended prompt structure for parallel agents?

Effective prompts should be focused on one domain, self-contained with all necessary context, and specific about the required output and constraints.

How do I prevent agents from conflicting with each other?

By ensuring each agent has a strictly defined, independent scope—such as different files or subsystems—and providing clear constraints on which files they are allowed to modify.

When should I avoid using parallel agents?

Avoid parallel dispatch when failures are related, share global state, or require a holistic view of the system where a fix in one area might resolve issues in another.

Parallel Agent Dispatcher

Name: Parallel Agent Dispatcher
Author: EricOo0

byEricOo0

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Productivity & Workflow

Optimizes development workflows by dispatching independent tasks to multiple AI agents for concurrent execution.

About

Parallel Agent Dispatcher is a specialized skill for Claude Code designed to accelerate troubleshooting and development cycles. It provides a structured framework for identifying independent problem domains—such as multiple unrelated test failures or isolated subsystem bugs—and delegating them to separate AI agents. By running these investigations in parallel rather than sequentially, it significantly reduces the time required to resolve complex issues while maintaining clear boundaries to prevent agent interference and code conflicts.

Key Features

Workflow patterns for concurrent test failure resolution
Domain decomposition logic for identifying parallelizable tasks
Conflict prevention guidelines for shared codebases
Structured agent prompt templates for focused task scope
Integration and verification strategies for multi-agent output
6 GitHub stars

Use Cases

Resolving multiple unrelated test failures across different files simultaneously
Implementing isolated features that do not share state or dependencies
Debugging independent bugs in separate subsystems concurrently

About

Key Features

Workflow patterns for concurrent test failure resolution
Domain decomposition logic for identifying parallelizable tasks
Conflict prevention guidelines for shared codebases
Structured agent prompt templates for focused task scope
Integration and verification strategies for multi-agent output
6 GitHub stars

Use Cases

Resolving multiple unrelated test failures across different files simultaneously
Implementing isolated features that do not share state or dependencies
Debugging independent bugs in separate subsystems concurrently