dispatching-parallel-agents

Dispatches concurrent agents to investigate independent test failures across separate problem domains.

Updated Dec 23, 2025
One-click install
npx skills add https://github.com/macintorsten/aurapod --skill dispatching-parallel-agents-macintorsten
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dispatching-parallel-agents
Source: https://github.com/macintorsten/aurapod/tree/main/.github/skills/dispatching-parallel-agents
Command: npx skills add https://github.com/macintorsten/aurapod --skill dispatching-parallel-agents-macintorsten

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Investigating multiple unrelated failures sequentially wastes time when each problem domain is independent. This Skill provides a structured pattern for dispatching one agent per independent failure domain so investigations run concurrently without interference. ## Core Features & Use Cases - Independence Assessment: A decision flowchart and criteria to determine whether failures are independent enough for parallel dispatch or require sequential investigation. - Agent Prompt Structure: A template for writing focused, self-contained agent tasks with specific scope, constraints, and expected output summaries. - Integration Workflow: Steps for reviewing agent summaries, checking for conflicts, and running the full test suite after parallel fixes. - Use Case: After a major refactoring leaves 6 test failures across 3 files (abort logic, batch completion, race conditions), dispatch three agents in parallel, each fixing one test file, then integrate all fixes with zero conflicts. ## Quick Start Ask the AI to dispatch one parallel agent per failing test file, giving each agent the specific test names, error messages, and a constraint to not modify unrelated code.

Frequently Asked Questions about dispatching-parallel-agents

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fix multiple failing tests in parallel with AI agents?▼

Group failures by independent problem domain, then dispatch one agent per domain with a focused prompt containing the test names, error messages, and constraints. Review each agent's summary and run the full test suite to verify the fixes integrate without conflicts.

When should I use parallel agents instead of sequential debugging?▼

Use parallel agents when failures are independent, such as different test files or subsystems with different root causes and no shared state. Avoid parallel dispatch when failures are related, when full system context is needed, or when agents would edit the same files.

What makes a good prompt for a debugging agent?▼

A good agent prompt is focused on one problem domain, self-contained with pasted error messages and test names, explicit about constraints like not changing production code, and specific about the expected output such as a summary of root cause and changes.

Can parallel agents conflict with each other when fixing code?▼

Yes, conflicts occur when agents share state or edit the same files. Prevent this by assigning each agent a distinct scope such as one test file, adding explicit constraints, and reviewing all summaries for overlapping changes before integration.

What are common mistakes when dispatching parallel agents?▼

Common mistakes include overly broad scopes like fixing all tests, missing context such as error messages, absent constraints that let agents refactor unrelated code, and vague output requirements. Each agent needs a narrow scope, full context, and a defined deliverable.