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.