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Hypothesis Formulation

OrganizationPopular
aiming-lab
hypothesis-formulation

Structured scientific hypothesis generation from observations. Use when formulating testable hypotheses, competing explanations, or experimental predictions.

Overview

Publisheraiming-lab
RepositoryAutoResearchClaw
Skill namehypothesis-formulation
Stars
14.4K
Forks
1.7K
Bundled files
Instructions only
LicenseMIT
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 aiming-lab on GitHub. Read the source before you install it.

Installation

Install the Hypothesis Formulation 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.
  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/aiming-lab/AutoResearchClaw.git /tmp/AutoResearchClaw
mkdir -p .claude/skills
cp -r /tmp/AutoResearchClaw/researchclaw/skills/builtin/experiment/hypothesis-formulation .claude/skills/hypothesis-formulation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hypothesis Formulation 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 Hypothesis Formulation 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 Hypothesis Formulation 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.

Hypothesis Formulation Best Practice

Structured Hypothesis Development

  1. Start with a clear observation or pattern that requires explanation
  2. Review existing literature for known mechanisms and prior explanations
  3. Identify what is already established vs. what remains uncertain
  4. Formulate the hypothesis as a specific, testable statement
  5. Ensure the hypothesis is falsifiable — define what outcome would refute it

Hypothesis Format

  1. Null hypothesis (H0): There is no effect or no difference
  2. Alternative hypothesis (H1): There is a specific, directional effect
  3. State both explicitly; design experiments to reject H0
  4. Use "If... then... because..." structure for mechanistic hypotheses:
    • If [independent variable is manipulated], then [predicted outcome], because [proposed mechanism]

Generating Competing Hypotheses

  1. Propose at least 2-3 plausible explanations for the same observation
  2. For each, identify unique predictions that distinguish it from alternatives
  3. Rank hypotheses by parsimony, consistency with prior evidence, and testability
  4. Design experiments that can discriminate between competing hypotheses
  5. Consider confounding variables that could produce the same observation

Testable Predictions

  1. Derive specific, measurable predictions from each hypothesis
  2. Define expected effect direction AND approximate magnitude
  3. Specify what experimental conditions would confirm vs. refute the prediction
  4. Identify potential confounds and plan controls to address them
  5. Ensure predictions are achievable with available methods and resources

Aligning with Experimental Design

  1. Map each hypothesis to a concrete experimental condition or comparison
  2. Ensure sample size is adequate to detect the predicted effect (power analysis)
  3. Pre-register hypotheses and analysis plans when possible
  4. Distinguish confirmatory (hypothesis-testing) from exploratory analyses
  5. Plan for both positive and null results — what will you conclude in each case?

Frequently asked questions

What does the Hypothesis Formulation AI skill do?

Structured scientific hypothesis generation from observations. Use when formulating testable hypotheses, competing explanations, or experimental predictions.

Why use Hypothesis Formulation on TypingMind?

Because you install it once and use it with any model. Hypothesis Formulation 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 Hypothesis Formulation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/experiment/hypothesis-formulation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hypothesis Formulation?

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 Hypothesis Formulation?

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

Is the Hypothesis Formulation AI skill free?

Yes. It is published on GitHub by aiming-lab under the MIT license. 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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