ar-scoping

Refine a topic seed into a research question with scope boundaries and feasibility assessment.

Updated Mar 22, 2026
One-click install
npx skills add https://github.com/ShinyGua/AutoArtsResearch --skill ar-scoping
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ar-scoping
Source: https://github.com/ShinyGua/AutoArtsResearch/tree/main/.claude/skills/ar-scoping
Command: npx skills add https://github.com/ShinyGua/AutoArtsResearch --skill ar-scoping

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Refine a user's topic seed into a well-defined research problem by outlining a clear research question, scope boundaries, and a feasibility assessment.

Core Features & Use Cases

  • Web landscape scouting: perform web searches to map existing scholarship, debates, and methodological precedents.
  • Question refinement: generate 3 candidate research questions with feasibility rankings and rationales.
  • Scope delineation: define included and excluded topics, regions, time frames, and source types.
  • Sub-question planning: identify 2-4 sub-questions to structure evidence gathering.
  • Deliverables: output a scoping_report.json and a scoping_summary.md and update status for gate progression.

Quick Start

Command your AI assistant to scope a topic seed by providing the workspace path and topic seed.

Frequently Asked Questions about ar-scoping

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

FAQPage Schema
How do I refine a research topic seed into a defined research question?

To scope a research topic, you map existing scholarship and methodological precedents to generate candidate research questions with feasibility rankings. This process yields a defined research question, scope boundaries, and a feasibility assessment for early-stage research planning.

What is the best way to set scope boundaries for a literature review?

Scoping boundaries for a literature review requires defining included and excluded topics, regions, time frames, and source types. This delineation structures evidence gathering and ensures the research question remains feasible within project constraints.

Can I use automated scoping for comparative case studies in social sciences?

Yes, automated scoping applies to early-stage research planning in arts and social sciences, including comparative case studies and policy analysis. It refines topic seeds by synthesizing web searches to map debates and methodological precedents, yielding a structured scoping report.

How do I generate sub-questions to structure evidence gathering?

Generating sub-questions to structure evidence gathering requires refining the primary research question and delineating scope boundaries. The process then identifies 2-4 sub-questions, which are outputted alongside scope boundaries to a scoping summary file.

What inputs are required to assess research feasibility and generate a scoping report?

Assessing research feasibility requires a topic seed, workspace status, and configuration inputs. The process synthesizes web searches to map scholarship, then outputs a scoping report and markdown summary to workspace paths, updating the status to scoping in progress.