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

Use parallel agents when you face two or more independent tasks that do not share state or sequential dependencies, such as fixing different test files or unrelated bugs in separate subsystems.

Can multiple agents interfere with each other's work?

Yes, if they edit the same files or shared resources. This skill teaches you to identify 'Independent Domains' to ensure agents are isolated before dispatching.

What is the primary benefit of the Parallel Agent Dispatcher?

The primary benefit is speed; it allows you to solve multiple problems in the time it would typically take to solve one by utilizing concurrent processing.

How do I integrate changes after parallel agents finish?

Review each agent's summary, verify that no conflicting code changes were made, and run the full test suite to ensure the integrated solution is stable.

Parallel Agent Task Dispatcher

Name: Parallel Agent Task Dispatcher
Author: lastdays03

bylastdays03

生産性とワークフロー

Accelerates development by orchestrating multiple independent AI agents to solve concurrent tasks and debugging issues simultaneously.

概要

The Parallel Agent Task Dispatcher skill provides a strategic framework for managing complex development workflows by identifying independent problem domains and dispatching specialized agents to handle them concurrently. By moving away from sequential task execution, this skill allows for the simultaneous resolution of unrelated test failures, subsystem bugs, and feature implementations. It includes specific patterns for prompt structuring and integration workflows to ensure that parallel agents operate efficiently without interfering with one another, significantly reducing the total time required for system-wide maintenance.

主な機能

0 GitHub stars
Concurrent execution framework for multi-agent workflows
Standardized prompt structures for focused agent tasks
Domain isolation logic to identify parallelization opportunities
Systematic integration and conflict review patterns
Visual decision trees for choosing between sequential and parallel dispatch

ユースケース

Parallelized code audits and documentation updates for disparate modules
Resolving multiple independent test failures across different files or subsystems
Simultaneous implementation of unrelated features without shared state

概要

主な機能

0 GitHub stars
Concurrent execution framework for multi-agent workflows
Standardized prompt structures for focused agent tasks
Domain isolation logic to identify parallelization opportunities
Systematic integration and conflict review patterns
Visual decision trees for choosing between sequential and parallel dispatch

ユースケース

Parallelized code audits and documentation updates for disparate modules
Resolving multiple independent test failures across different files or subsystems
Simultaneous implementation of unrelated features without shared state