agent-research

Coordinate multi-agent research with dynamic expert selection and phase-based workflows.

68|29|Updated Jan 26, 2026
One-click install
npx skills add https://github.com/revfactory/skills --skill agent-research-revfactory
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-research
Source: https://github.com/revfactory/skills/tree/main/agent-research
Command: npx skills add https://github.com/revfactory/skills --skill agent-research-revfactory

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill assembles dynamic expert teams to conduct comprehensive research by selecting the most suitable specialists from a predefined pool, ensuring depth and quality of insights.

Core Features & Use Cases

  • Dynamic selection of 11 specialists to form a multi-perspective research team.
  • Phase-based workflow: target analysis, parallel investigation, cross-validation, gap analysis, and final reporting.
  • Robust collaboration protocol with inter-agent sharing, task management, and audit trails.
  • Output artifacts include team design rationale, phase logs, cross-validation notes, and a final report.

Quick Start

Provide a project target and keywords to trigger team design and initiate the multi-agent research workflow.

Frequently Asked Questions about agent-research

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

FAQPage Schema
How do I automate comprehensive research report generation for complex topics?▼

Automate research report generation by dynamically selecting specialists from a predefined pool to form a multi-perspective team. This enforces cross-agent collaboration and evidence-based validation throughout a structured phase workflow to produce a final report.

What is the best way to structure multi-agent research for investigating companies or regulatory issues?▼

Structure multi-agent research using a phase-based workflow: target analysis, parallel investigation, cross-validation, gap analysis, and final reporting. This ensures robust collaboration protocols with inter-agent sharing and audit trails for investigating companies or regulatory issues.

How does cross-verification work in an agent-team based research workflow?▼

Cross-verification works by enforcing inter-agent sharing and evidence-based validation during the cross-validation phase. Agents investigate targets in parallel, then share findings to identify gaps and validate insights before generating the final dynamic report.

Can I control the depth of investigation when researching AI tech and individuals?▼

Yes, you can control the depth of investigation using options like quick, standard, and deep. These depth settings dictate the intensity of the parallel investigation and cross-validation phases conducted by the dynamically selected expert team.

Do I need to manually select specialists for target analysis?▼

No, you do not need to manually select specialists. The system dynamically selects the most suitable experts from a predefined pool of 11 specialists based on your provided project target and keywords to form the research team.

What outputs should I expect from a dynamic expert team research workflow?▼

Outputs from a dynamic expert team research workflow include team design rationale, phase logs, cross-validation notes, and a final report. These artifacts document the end-to-end process from target analysis to dynamic report generation.