dispatching-parallel-agents

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

Updated Dec 20, 2025
One-click install
npx skills add https://github.com/cristoslc/LLM-personal-agent-patterns --skill dispatching-parallel-agents-cristoslc
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dispatching-parallel-agents
Source: https://github.com/cristoslc/LLM-personal-agent-patterns/tree/main/L3-agents-core/.agents/skills/dispatching-parallel-agents
Command: npx skills add https://github.com/cristoslc/LLM-personal-agent-patterns --skill dispatching-parallel-agents-cristoslc

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 pattern for splitting work across parallel agents so several investigations run concurrently without interfering with each other. ## Core Features & Use Cases - Independence Assessment: Decision criteria for determining whether failures are independent enough to parallelize or require sequential investigation. - Focused Agent Prompts: A structure for writing self-contained agent tasks with specific scope, constraints, and expected output. - Integration Workflow: Steps for reviewing agent summaries, checking for conflicts, and running the full test suite after parallel fixes. - Use Case: After a refactoring leaves 6 test failures across 3 files (abort logic, batch completion, race conditions), dispatch one agent per test file so all three investigations complete concurrently, then integrate the non-conflicting fixes. ## Quick Start Ask the agent to dispatch one parallel agent per failing test file, giving each a focused scope, constraints, and a required summary of root cause and fixes.

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 covering scope, constraints, and expected output. After agents return, review summaries, check for conflicting edits, and run the full test suite.

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 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 parallel 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 root cause summary.

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

Yes, agents can conflict if they edit the same files or share state. Prevent this by assigning strictly independent domains, then verify after completion by reviewing each summary and running the full test suite to catch integration issues.

What are common mistakes when dispatching parallel agents?▼

Common mistakes include overly broad scopes like fixing all tests at once, missing context such as error messages, absent constraints that let agents refactor unrelated code, and vague output requirements that hide what actually changed.