How does parallel dispatching save time in Claude Code?

By running multiple investigations or fixes simultaneously instead of waiting for one agent to finish before starting the next, cutting total resolution time by the number of concurrent tasks.

How do I prevent agents from interfering with each other?

Assign each agent a strictly defined scope, such as a specific file or directory, and ensure they are working on independent problem domains with no shared dependencies.

When should I avoid using parallel agents?

Avoid parallel dispatching when tasks are interdependent, share the same state, or if fixing one issue is likely to resolve the others, as this can lead to merge conflicts or redundant work.

What subagent types can I use with this skill?

You can utilize general-purpose agents, Bash execution agents, Explore agents for codebase analysis, and Plan agents for design tasks.

Can I run these parallel tasks in the background?

Yes, the skill supports the run_in_background parameter, allowing you to continue working while subagents perform long-running analyses or fixes.

Parallel Agent Dispatcher

Name: Parallel Agent Dispatcher
Author: lgbarn

bylgbarn

Productivity & Workflow

Optimizes development speed by orchestrating multiple Claude subagents to resolve independent tasks concurrently.

About

The Parallel Agent Dispatcher provides a structured framework for managing complex debugging and development scenarios by splitting workload across multiple concurrent subagents. By identifying independent problem domains—such as isolated test failures or unrelated subsystem bugs—it allows Claude to dispatch focused tasks in a single message, drastically reducing total execution time. This pattern prevents context bloat in any single agent and ensures that independent issues are investigated and resolved without sequential bottlenecks or shared state interference.

Key Features

Domain-specific scoping to keep agent investigations focused and small
Concurrent task execution via single-message subagent dispatching
Structured integration workflow for reviewing and merging parallel fixes
Model-specific optimization for cost and speed (e.g., Haiku for simple tasks)
Support for multiple subagent types including Explore, Bash, and Plan
0 GitHub stars

Use Cases

Resolving multiple independent test failures across different subsystems simultaneously
Conducting wide-scale codebase exploration or audits across disparate modules
Performing concurrent infrastructure updates and security reviews in DevOps workflows

About

Key Features

Domain-specific scoping to keep agent investigations focused and small
Concurrent task execution via single-message subagent dispatching
Structured integration workflow for reviewing and merging parallel fixes
Model-specific optimization for cost and speed (e.g., Haiku for simple tasks)
Support for multiple subagent types including Explore, Bash, and Plan
0 GitHub stars

Use Cases

Resolving multiple independent test failures across different subsystems simultaneously
Conducting wide-scale codebase exploration or audits across disparate modules
Performing concurrent infrastructure updates and security reviews in DevOps workflows