What happens if two agents try to edit the same file?

The pattern encourages identifying independent domains first to avoid this. If shared state is detected, you should revert to sequential agents or a single-agent investigation.

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

Use parallel agents when you have three or more independent failures that do not share state, such as different test files failing for different, unrelated reasons.

Does this work for exploratory debugging?

No, this pattern is best suited for known failures with clear scopes. For exploratory work where the root cause is still unknown, a single-agent sequential approach is usually more effective.

Will the agents interfere with each other's work?

This skill is specifically designed for independent domains. By ensuring agents work on different files or subsystems, the risk of merge conflicts or shared state interference is minimized.

Parallel Agent Dispatcher

Name: Parallel Agent Dispatcher
Author: seanGSISG

byseanGSISG

Productivity & Workflow

Dispatches multiple concurrent AI agents to investigate and resolve independent software failures and bugs simultaneously.

About

The Parallel Agent Dispatcher skill optimizes the debugging process by parallelizing investigations into unrelated system failures. Instead of tackling bugs sequentially, it categorizes independent issues—such as failing test files or broken subsystems—into specific domains and assigns a dedicated Claude agent to each. This approach is particularly effective during large-scale refactors or complex testing phases, significantly reducing time-to-resolution by ensuring that multiple investigations occur in parallel without interfering with one another.

Key Features

Domain-specific constraint enforcement
Automated agent task partitioning and scoping
Structured review and integration of multi-agent fixes
Concurrent problem domain investigation
0 GitHub stars
Decision logic for sequential vs. parallel dispatch

Use Cases

Resolving multiple independent test failures after a major codebase refactor
Fixing unrelated bugs across disparate subsystems like Auth and Database
Simultaneous root-cause analysis for multiple race conditions in different modules

About

Key Features

Domain-specific constraint enforcement
Automated agent task partitioning and scoping
Structured review and integration of multi-agent fixes
Concurrent problem domain investigation
0 GitHub stars
Decision logic for sequential vs. parallel dispatch

Use Cases

Resolving multiple independent test failures after a major codebase refactor
Fixing unrelated bugs across disparate subsystems like Auth and Database
Simultaneous root-cause analysis for multiple race conditions in different modules