research

Coordinate parallel scientist agents to decompose research goals and generate reports.

Updated Feb 1, 2026
One-click install
npx skills add https://github.com/suhwan/claude-registry --skill research-suhwan
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: research
Source: https://github.com/suhwan/claude-registry/tree/main/skills/project/research
Command: npx skills add https://github.com/suhwan/claude-registry --skill research-suhwan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coordinating multiple domain experts to tackle large research goals is time-consuming and error-prone. This skill autobundles decomposition, parallel execution, verification, and synthesis into a repeatable workflow, increasing speed and consistency.

Core Features & Use Cases

  • Decomposition of goals into independent stages for parallel investigation.
  • Parallel invocation of specialized agents (researchers, data-collectors, synthesizers) with AUTO mode support.
  • Structured session management and final report generation for auditability.

Quick Start

Run the research workflow in AUTO mode to decompose a goal and generate a report.

Frequently Asked Questions about research

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

FAQPage Schema
How do I automate parallel research tasks across multiple documents?

Automate parallel research tasks by decomposing goals into independent stages for parallel investigation. Specialized agents execute concurrently, followed by verification and synthesis to generate a final structured report.

What is parallel agent orchestration for multi-stage investigations?

Parallel agent orchestration coordinates specialized researchers, data-collectors, and synthesizers to execute multi-stage investigations concurrently. It handles decomposition, parallel execution, verification, and synthesis automatically.

Can I use AUTO mode to generate research reports without manual intervention?

Yes, AUTO mode supports decomposing a research goal, invoking parallel agents, and generating a final report automatically. Structured session management ensures the entire workflow remains auditable.

Does parallel execution work for analyzing codebases and APIs?

Parallel execution applies to research, analysis, and synthesis tasks across codebases, APIs, and documents. It decomposes comprehensive goals into independent stages for concurrent investigation by specialized agents.

What's the best way to coordinate domain experts for large research goals?

Coordinate domain experts by bundling decomposition, parallel execution, verification, and synthesis into a repeatable workflow. This structured session management increases speed and consistency while reducing manual coordination errors.

Why use a structured research workflow instead of sequential analysis?

A structured research workflow replaces sequential analysis with parallel execution to increase speed and consistency. It decomposes goals into independent stages, verifies results, and synthesizes findings into an auditable report.