research-expert

Automate multi-source information gathering and produce structured findings.

218|14|Updated Apr 5, 2025
One-click install
npx skills add https://github.com/cin12211/orca-q --skill research-expert
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: research-expert
Source: https://github.com/cin12211/orca-q/tree/main/.agent/skills/research-expert
Command: npx skills add https://github.com/cin12211/orca-q --skill research-expert

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates targeted, multi-source information gathering to produce structured findings with minimal manual effort.

Core Features & Use Cases

  • Mode-based research: Quick Verification, Focused Investigation, and Deep Research with automated task scoping.
  • Multi-source aggregation: Coordinated use of WebSearch, WebFetch, Read, and Write to assemble verified information.
  • Use Case: A product manager needs market signals; run focused research to compile authoritative summaries and citations for a brief.

Quick Start

Use the research-expert to gather concise, sourced insights on a topic.

Frequently Asked Questions about research-expert

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

FAQPage Schema
How do I automate web search and information gathering for structured research reports?▼

Automated web search and information gathering aggregates data from multiple sources using WebSearch and WebFetch, producing structured findings with citations for focused professional investigations.

Can I run focused competitive analysis and gather evidence across multiple domains?▼

Focused competitive analysis and cross-domain evidence gathering are supported through mode-based research strategies, coordinating WebSearch and file operations to compile verified summaries.

What is the best way to scope a deep research task versus a quick verification query?▼

Scoping a deep research task versus a quick verification query is handled by a mode-based task parsing strategy, automatically adjusting the depth of multi-source aggregation.

Does this research automation approach require explicit metadata for structured output?▼

This research automation approach requires explicit frontmatter-driven metadata to enforce a structured output format, ensuring assembled information meets professional documentation standards.

What are the limitations of using automated multi-source aggregation for investigations?▼

Automated multi-source aggregation for investigations is limited by the availability and accessibility of online sources, relying on WebFetch and WebSearch to retrieve publicly available data.