Analysis updated 2026-05-18
Turn a vague research interest into a structured, testable question
Stress-test an early idea before investing more time in it
Prepare a research proposal with anticipated objections already addressed
Diagnose why a stalled project's core question needs sharpening
| rimagination/good-question | ensigncocoonenergy/undown-tool | disintegr8te/teams-policy-export | |
|---|---|---|---|
| Stars | 94 | 92 | 114 |
| Language | PowerShell | PowerShell | PowerShell |
| Setup difficulty | easy | easy | moderate |
| Complexity | 1/5 | 3/5 | 3/5 |
| Audience | researcher | developer | ops devops |
Figures from each repo's GitHub metadata at analysis time.
Good Question is a portable skill for AI agent tools, specifically Codex and Claude Code, designed to help researchers sharpen a research question before investing time in it. The idea is that having a good question is itself a skill, and this tool tries to make that process more structured and repeatable. You use it by describing where you are: a vague interest, a gap you noticed in published literature, an early idea you want to stress-test, a proposal you are preparing, or a project that has stalled. The skill then works through a sequence of checks. It looks at whether the question matters to theory or practice, whether it is specific enough to be tested, whether there are competing explanations, whether there is a result that could disprove it, and whether a small pilot study could be started within two weeks. The output is a structured card with fields for the research question, why it matters, what assumptions it challenges, what competing hypotheses exist, what evidence would settle the question, what would falsify it, the strongest expected objection from a reviewer, and a suggested next step. The README is written in both Chinese and English. The Chinese version is longer and contains additional detail about how the tool handles domain-specific contexts for fields like ecology, social science, and biomedicine. The repository includes a folder of reference method cards that can be loaded on demand, as well as field playbooks, contribution guidelines, and a release checklist. The skill is built around seven criteria for what makes a question worth pursuing: it changes something if answered, it is specific and reachable by evidence, it has more than one possible explanation, it can be disproved, it can be started under real constraints, it teaches something even if the main hypothesis fails, and any claim about recent trends is traceable to a public source rather than stated as assumed fact. Installation is a single git clone command into the skills directory of either Codex or Claude Code. The license is MIT.
A portable AI-agent skill that helps researchers stress-test and sharpen a research question before committing time to it.
Mainly PowerShell. The stack also includes Markdown, Claude Code, Codex.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.