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Rimagination / good-question

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A portable agent skill for sharpening research questions.

agent-skill ai-agents research-ideation research-questions scientific-method
10
0
69% credibility
Found Jun 01, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

Good Question is a small tool that helps researchers turn vague ideas into sharp, testable scientific questions. It works as an add-on for AI assistants, guiding you through a conversation to clarify exactly what you want to study and why it matters. The project provides a simple configuration file that defines how the AI should help you refine your research thinking.

How It Works

1
πŸ’‘ You have a research idea

You've been thinking about a topic you want to study, but it feels fuzzy and hard to pin down.

2
πŸ”§ You sharpen your idea

You use Good Question to transform your rough concept into a clear, focused question you can actually test.

3
πŸ€– Your AI assistant helps out

The tool works with your AI assistant, asking you smart questions to dig deeper into what you really want to know.

4
✨ Your question becomes clear

What started as a vague notion now reads like a proper research question with clear focus and direction.

🎯 You're ready to move forward

You now have a strong, testable question that you can use to design your study or write your proposal.

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AI-Generated Review

What is good-question?

good-question is a portable agent skill designed to transform rough research ideas into sharp, testable scientific questions. Built as a YAML-based configuration, it integrates with AI agent systems to provide a structured prompting framework. The skill accepts a loose research concept and outputs a refined, actionable question through a simple command syntax.

Why is it gaining traction?

Researchers and developers are increasingly building AI-assisted workflows, and having modular skills like this one makes agent customization more accessible. The portable design means it can slot into different agent platforms without heavy modification. For teams doing literature reviews or early-stage research, having a tool that forces ideas into testable form addresses a real pain point in the research process.

Who should use this?

Academic researchers writing proposals or designing experiments will find this most useful. Developers building custom AI agents with research capabilities can use this as a ready-made skill module. Product managers or analysts conducting exploratory research may also benefit when they need to move from vague hypotheses to concrete questions. Anyone frustrated with停在"interesting idea" without a clear next step will appreciate the structure it provides.

Verdict

This is a niche tool with minimal traction (10 stars) and limited documentation to evaluate thoroughly. The credibility score sits at 0.699%, reflecting its early-stage status and sparse community feedback. If you're building an AI agent framework and need a question-sharpening skill, it's worth a quick test. For standalone use, wait until the project accumulates more examples and documentation. The concept is sound, but maturity matters when you're betting on tooling.

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