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Research Grill

Community
scdenney
research-grill

Interviews a researcher in rounds until an idea, design, or draft has no unexamined decision — numbered questions, each with why it matters and a recommended answer, facts looked up rather than asked, and settled decisions written to a file. Stages are idea (topic or hunch to a falsifiable question and contribution claim), design (estimand, identification, sample and power, measurement, analysis plan, pre-registration, venue), and defend (reviewer objections to a finished design or draft). Use when the user says "grill me", asks to stress-test or poke holes in an idea, design, or plan, asks what they are assuming, or brings an idea that is not yet a design. --plan grills software or process plans.

Overview

Publisherscdenney
Repositoryopen-science-skills
Skill nameresearch-grill
Stars
69
Forks
3
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by scdenney on GitHub. Read the source before you install it.

Installation

Install the Research Grill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/scdenney/open-science-skills/tree/main/plugin/skills/research-grill
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/scdenney/open-science-skills.git /tmp/open-science-skills
mkdir -p .claude/skills
cp -r /tmp/open-science-skills/plugin/skills/research-grill .claude/skills/research-grill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Research Grill in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Research Grill on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Research Grill is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Research Grill

An interview, not an evaluation. You ask; the researcher decides. The session ends when nothing about the project is left silently assumed and every decision is written down.

Related skills. research-wayfinder carries the same interview across many sessions as a ticket map; use it when a project has more open decisions than one conversation can hold, and use this skill for one sitting. diverge puts several distinct options on the table when a question needs them before it can be answered. hypothesis-building, survey-design, conjoint-design, list-experiment, cross-national-design, and pre-registration-writing are where a settled decision goes to be worked out in full; name the relevant one in your recommended answer so the researcher can go deeper.

Stage

Infer the stage from what the researcher brings; an argument forces it.

StageResearcher bringsDone when
ideaa topic, a hunch, a puzzle, "I want to study X"one falsifiable research question, the population it covers, the contribution claim in one sentence, and the reason an experiment or survey is the right instrument rather than existing data
designa research questionthe design tree below is fully visited: estimand, identification, sample and power, measurement, analysis plan, ethics and pre-registration venue, output venue
defenda finished design, a pre-analysis plan, or a draftevery objection a careful reviewer would raise has been put to the researcher and either answered, accepted as a limitation, or turned into a design change

--plan runs the generic version for software, process, or teaching plans: the same rounds mechanic over the plan's own decision tree, without the research design tree.

The design tree

Every decision branches into the decisions that hang off it. The tree for research, in the order prerequisites usually settle:

  1. Question and estimand. What quantity, for whom, under what counterfactual. A question without an estimand is a topic.
  2. Theory and hypotheses. The mechanism that yields a falsifiable if-then, the direction it predicts, and the smallest effect size that would matter (SESOI). hypothesis-building.
  3. Design and identification. Random assignment or the identification strategy; what would break it; whether the treatment is the one the theory names. conjoint-design, list-experiment where they apply.
  4. Population, sample, and power. Who the claim covers, how they are recruited, N for the SESOI, and what is lost if the sample is a convenience sample. cross-national-design when multi-country.
  5. Measurement. Instruments, scales, manipulation checks, attention checks, social-desirability exposure. survey-design.
  6. Analysis plan. Estimator matched to the design, covariates, multiple-comparison policy, what counts as a null.
  7. Ethics, pre-registration, and logistics. IRB or ethics review, consent, registry, timeline, budget. pre-registration-writing.
  8. Output. Thesis, working paper, journal, grant report; what the venue expects; who the reader is.

For a student thesis the "done" criteria are the programme's assessment rubric, which the thesis:* skills carry (BAIS, BAKS, MAAS, MAIR at Leiden). Ask which programme once, then read that rubric and treat its criteria as branches of node 8.

Rounds

Work the tree in rounds. The frontier is every decision whose prerequisites are settled, so every question you can ask now without guessing at an answer you have not heard. Ask the whole frontier in one round, then wait.

Each question takes this form:

❓ Q1 — <short title>
<the question, in plain language; if it has a technical name, give it and gloss it once>
Why this matters: <one sentence on what goes wrong downstream if this is left open>
➡️ Recommended: <your answer, and the skill or source that backs it>

Rules for a round:

  • Number every question. The researcher answers by number.
  • Recommend every time. A question with no recommended answer is homework, not an interview. The recommendation cites the method skill or the source it rests on.
  • Plain language first. A student must be able to answer without looking anything up. Give the technical term after the plain version, glossed once, and use it consistently afterward.
  • One round, one frontier. A question whose answer depends on another question still open in this round belongs to the next round.
  • Facts are yours to find. When a question needs a fact from the world (has this been done, what does the literature say the effect size is, does a dataset exist, what does the registry require), fetch it: literature-review or WebSearch for prior work and current tools, Explore or Grep for repository state, WebFetch for a registry or a journal's requirements. Dispatch the lookup and keep asking the rest of the frontier while it runs; only the questions downstream of that fact wait. Ask the researcher only for what they alone know, and look up any name, tool, or dataset you do not confidently recognize rather than answering from memory.
  • Decisions are theirs. Put every decision to the researcher and wait for the answer, including the ones whose answer seems obvious. The skill sharpens the researcher's claim; it never supplies the research question or the claim itself.
  • Recompute after every round. Settled decisions push the frontier outward and unblock what depended on them. A decision the researcher reverses later reopens its subtree.

Writing it down

Decisions that exist only in the chat are lost at the end of the session, so write them to a file.

  • If the project has a research-wayfinder map (planning/map.md), write each settled decision into the matching ticket and add new tickets for what the interview surfaced.
  • Otherwise write and maintain decisions.md in the project root (or the path the researcher names): one entry per settled decision, with the decision, the rationale in the researcher's words, what would change it, and the round it was settled in. Update the file after every round, not at the end.
  • Facts you fetched go in the same file under a Looked up heading with the source, so the next session does not fetch them again.

Exit

The session is done when the frontier is empty for the chosen stage and the file is written. Then, in one line each, name what comes next and stop: hypothesis-building after idea; pre-registration-writing or research-wayfinder after design; narrative-building, paper-review-lite, or the relevant thesis:* skill after defend. Do not start the next skill unless asked.

Notes

  • The tree and its rigour are the same for a student and a professor; only the gloss changes.
  • A researcher who cannot answer a frontier question has found the open decision the interview exists to find. Offer the recommended answer, mark it as provisional in the file, and move on; do not stall the round on it.
  • Heritage: the frontier-rounds mechanic is Matt Pocock's grill-me (MIT, mattpocock/skills); see RECOMMENDED.md. This skill adds the research design tree, the plain-language and recommended-answer rules, the fetch-not-ask routing through the library's method skills, the thesis rubric as done criteria, and the written decision record.

Frequently asked questions

What does the Research Grill AI skill do?

Interviews a researcher in rounds until an idea, design, or draft has no unexamined decision — numbered questions, each with why it matters and a recommended answer, facts looked up rather than asked, and settled decisions written to a file. Stages are idea (topic or hunch to a falsifiable question and contribution claim), design (estimand, identification, sample and power, measurement, analysis plan, pre-registration, venue), and defend (reviewer objections to a finished design or draft). Use when the user says "grill me", asks to stress-test or poke holes in an idea, design, or plan, asks...

Why use Research Grill on TypingMind?

Because you install it once and use it with any model. Research Grill is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Research Grill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/scdenney/open-science-skills/tree/main/plugin/skills/research-grill. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Research Grill?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Research Grill?

As many as you like. As long as a model supports skills, you can use Research Grill with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Research Grill AI skill free?

It is published on GitHub by scdenney. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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