How do I prevent parallel agents from interfering with each other?

Assign each agent a specific, isolated scope (like a single file) and set clear constraints to ensure they don't modify production code outside their assigned domain.

When should I use parallel agents instead of a single agent?

Use parallel agents when you have two or more independent tasks that don't share state or sequential dependencies, such as failures in different test files or unrelated subsystems.

How do I merge the work of multiple agents?

Once agents return, review their individual summaries, verify there are no file-level conflicts, and run the full project test suite to ensure all fixes work together correctly.

What are the main benefits of parallel dispatching?

The primary benefits are speed and focus. Investigations happen simultaneously rather than sequentially, and each agent operates within a narrower context window, which improves problem-solving accuracy.

Parallel Agent Dispatcher

Name: Parallel Agent Dispatcher
Author: Krosebrook

byKrosebrook

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生产力与工作流

Accelerates development by orchestrating multiple AI agents to handle independent tasks and bug fixes simultaneously.

关于

The Parallel Agent Dispatcher skill optimizes development workflows by identifying independent problem domains and dispatching specialized agents to handle them concurrently. Instead of investigating failures or implementing features sequentially, this pattern allows for the rapid resolution of multiple test failures, subsystem issues, or non-dependent bugs. By dividing complex workloads into isolated tasks, it significantly reduces total debugging time and ensures each agent remains focused on a narrow, well-defined scope for higher accuracy and speed.

主要功能

Conflict detection and integration workflow for parallel outputs
Logic-driven decision framework for parallelization suitability
Concurrent execution of multiple specialized AI sub-agents
Domain-based task grouping for independent problem solving
Standardized prompt templates for focused agent tasking
1 GitHub stars

使用场景

Resolving multiple independent test failures across different files simultaneously
Handling multi-component refactoring where subsystems have no shared state
Implementing several minor, unrelated feature requests in a single session

关于

主要功能

Conflict detection and integration workflow for parallel outputs
Logic-driven decision framework for parallelization suitability
Concurrent execution of multiple specialized AI sub-agents
Domain-based task grouping for independent problem solving
Standardized prompt templates for focused agent tasking
1 GitHub stars

使用场景

Resolving multiple independent test failures across different files simultaneously
Handling multi-component refactoring where subsystems have no shared state
Implementing several minor, unrelated feature requests in a single session