What should be included in an agent prompt for this skill?

Prompts should be focused on one domain, provide all necessary context (like error logs), and specify exactly what the agent should return as a summary.

Can I use this for exploratory debugging?

No, it is best used when failures are already isolated. Exploratory debugging where the root cause is unknown usually requires a single agent to see the full system state.

When should I use parallel agent dispatching?

Use it when you have three or more independent failures, such as different test files or subsystems, that can be investigated without shared state or dependencies.

What is the main benefit over sequential fixing?

The primary benefit is speed; by parallelizing investigations, you can solve multiple independent problems in the time it would normally take to solve one.

How does it prevent agents from conflicting with each other?

The skill focuses on identifying independent domains and setting strict constraints in prompts, ensuring agents only modify code within their assigned scope.

Parallel Agent Dispatcher

Name: Parallel Agent Dispatcher
Author: yusoofsh

byyusoofsh

Productividad y Flujo de Trabajo

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

Acerca de

The Parallel Agent Dispatcher skill optimizes the debugging workflow by identifying unrelated failures across different subsystems or test suites and assigning them to specialized agents simultaneously. Instead of tackling bugs sequentially, it groups failures by domain and generates focused tasks for independent resolution. This pattern is particularly effective when facing three or more isolated issues, allowing developers to leverage parallel processing to significantly reduce the time required for system-wide fixes and post-refactoring cleanup.

Características Principales

Structured agent prompt generation with focused scope and constraints
Automated failure domain grouping for independent issues
Time-optimized debugging for large-scale test regressions
0 GitHub stars
Conflict-aware integration workflow for merging multi-agent fixes
Concurrent task dispatching for 3+ unrelated bugs

Casos de Uso

Simultaneously fixing flaky tests in different files without shared dependencies
Resolving multiple unrelated test failures following a major codebase refactor
Investigating independent bugs across different subsystems like API, UI, and Database

Acerca de

Características Principales

Structured agent prompt generation with focused scope and constraints
Automated failure domain grouping for independent issues
Time-optimized debugging for large-scale test regressions
0 GitHub stars
Conflict-aware integration workflow for merging multi-agent fixes
Concurrent task dispatching for 3+ unrelated bugs

Casos de Uso

Simultaneously fixing flaky tests in different files without shared dependencies
Resolving multiple unrelated test failures following a major codebase refactor
Investigating independent bugs across different subsystems like API, UI, and Database