compose:parallel

Dispatch concurrent subagents to fix independent failures across separate problem domains.

Updated Jun 27, 2026
One-click install
npx skills add https://github.com/HKUST-QUANT-SOCIETY/quantcode --skill compose-parallel-hkust-quant-society
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: compose:parallel
Source: https://github.com/HKUST-QUANT-SOCIETY/quantcode/tree/main/.opencode/meta-skills/parallel
Command: npx skills add https://github.com/HKUST-QUANT-SOCIETY/quantcode --skill compose-parallel-hkust-quant-society

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? When multiple unrelated failures appear across different test files or subsystems, investigating them sequentially wastes time and bloats your working context. This Skill coordinates parallel subagents so each independent problem is investigated and fixed concurrently with isolated context. ## Core Features & Use Cases - Independent Domain Detection: Decision rules to determine whether failures are truly independent and safe to parallelize, or related and better handled by a single agent. - Focused Agent Prompts: A prompt structure ensuring each subagent gets a specific scope, clear goal, constraints, and expected output format. - Integration & Verification Workflow: Steps to review agent summaries, detect conflicting edits, and run the full test suite after parallel fixes. - Use Case: After a major refactoring leaves 6 failing tests across 3 files (abort logic, batch completion, race conditions), dispatch three agents in parallel, then integrate their independent fixes with zero conflicts. ## Quick Start Ask the agent to dispatch parallel subagents to investigate and fix the failing tests in each of these independent test files, then review and integrate their results.

Frequently Asked Questions about compose:parallel

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 subagent per domain in the same turn with a focused prompt covering scope, goal, 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 with different root causes, and no shared state exists between investigations. Avoid parallelism when failures are related, when full system context is needed, or when agents would edit the same files.

What makes a good subagent prompt for parallel debugging?

A good 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 fixes.

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 independent domains, and after completion verify no overlapping edits occurred before integrating changes and running the full suite.

What are the limitations of dispatching parallel subagents?

Parallel dispatch does not help with related failures where fixing one may fix others, exploratory debugging where the problem is unknown, or tasks requiring full system context. In those cases a single sequential investigation is more effective.