dispatching-parallel-agents

Dispatch focused sub-agents in parallel to fix independent test failures concurrently.

Updated Jun 11, 2026
One-click install
npx skills add https://github.com/marcocpt/trae_skills --skill dispatching-parallel-agents-marcocpt
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dispatching-parallel-agents
Source: https://github.com/marcocpt/trae_skills/tree/main/dispatching-parallel-agents
Command: npx skills add https://github.com/marcocpt/trae_skills --skill dispatching-parallel-agents-marcocpt

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? When multiple unrelated failures appear across different test files or subsystems, investigating them one by one wastes time and bloats your working context. This Skill lets you delegate each independent problem domain to an isolated sub-agent so investigations run concurrently. ## Core Features & Use Cases - Independence Decision Framework: A decision flowchart and criteria help you determine whether failures are independent enough to parallelize or share state requiring sequential handling. - Agent Prompt Structure: Provides a proven template for writing focused, self-contained agent prompts with clear scope, constraints, and expected output summaries. - Review and Integration Workflow: Guides you through reviewing agent summaries, checking for conflicting edits, and running the full test suite after agents return. - Use Case: After a large refactor leaves 6 failing tests across 3 files (abort logic, batch completion, race conditions), dispatch 3 agents in parallel—one per file—and integrate their independent fixes with zero conflicts. ## Quick Start Ask the AI to dispatch one parallel sub-agent per failing test file, each with a focused prompt to diagnose and fix its failures, then review and integrate the results.

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 sub-agent per domain with a focused prompt covering scope, goal, constraints, and expected output. Each agent works in an isolated context concurrently, and you integrate their fixes afterward.

When should I use parallel agents instead of debugging sequentially?

Use parallel agents when failures are independent—different root causes, different files, no shared state. If fixing one failure might fix others, or understanding requires full system context, investigate sequentially with a single agent instead.

What should a good sub-agent prompt include?

A good agent prompt is focused on one problem domain, self-contained with all needed context like error messages and test names, explicit about constraints such as not modifying unrelated code, and clear about the expected output summary.

Can parallel agents conflict with each other when editing code?

Yes, if agents share state or edit the same files they can interfere. Prevent this by assigning strictly disjoint scopes, and after agents return, review summaries, check for overlapping edits, and run the full test suite to verify integration.

What are the limitations of dispatching parallel debugging agents?

It does not fit related failures where one fix cascades, exploratory debugging where the problem is unknown, or tasks needing complete system context. Agents also lack your conversation history, so prompts must supply everything they need.