research

Generate structured research documents from inquiry topics with mode-driven templates.

2|Updated Apr 3, 2026
One-click install
npx skills add https://github.com/jscott3201/ai-agent-skills --skill research-jscott3201
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: research
Source: https://github.com/jscott3201/ai-agent-skills/tree/main/skills/research
Command: npx skills add https://github.com/jscott3201/ai-agent-skills --skill research-jscott3201

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Structured research producing actionable findings documents. Supports technical deep-dives, multi-perspective analysis, competitive landscape, and documentation lookup. Use when investigating before building.

Core Features & Use Cases

  • Generates structured, verifiable findings with cross-references and severity rankings.
  • Supports mode-driven templates (deep-dive, multi-perspective, landscape) and recall via graph memory.
  • Provides actionable outputs for design, build, and strategy decisions.

Quick Start

Provide a topic or question to initiate a structured research session.

Frequently Asked Questions about research

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

FAQPage Schema
How do I generate structured research documents from technical deep-dives?

Generate structured research documents by providing an inquiry topic to the session, which applies mode-driven templates to produce verifiable findings with cross-references and severity rankings for design and strategy decisions.

What is the best way to conduct a competitive landscape assessment before building?

The best way to conduct a competitive landscape assessment is to apply the landscape mode template, which structures multi-perspective analyses into actionable findings documents to inform your build and strategy decisions.

Can I use graph memory to recall prior research findings during an investigation?

Yes, you can recall prior findings during an investigation by optionally integrating graph memory via SeleneDB. This allows you to recall past structured findings to support technical deep-dives and multi-perspective analyses.

Does this research tool support multi-perspective analysis templates?

Yes, this research tool supports multi-perspective analysis templates alongside deep-dive and landscape modes. These frontmatter-driven templates ensure consistent outputs for actionable findings documents across different investigation types.

When do I need frontmatter-driven templates for documentation lookups?

You need frontmatter-driven templates for documentation lookups when you require consistent, structured, and verifiable findings documents. The templates ensure your research outputs include cross-references and severity rankings for actionable decision-making.