Claim-Driven Experiment Planner
zjYao36/Auto-Research-Refine
Turns a refined research proposal into a claim-to-evidence-to-run-order roadmap instead of a sprawling benchmark wishlist.
Guides turning an observation into testable, falsifiable hypotheses with null and alternative statements, competing explanations and predictions tied to experimental design.
Install Hypothesis Formulation
$ npx skills add aiming-lab/AutoResearchClaw --skill hypothesis-formulation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aiming-lab/AutoResearchClaw hypothesis-formulation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/hypothesis-formulation .claude/skills/hypothesis-formulation && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "hypothesis-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/hypothesis-formulation into .claude/skills/hypothesis-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hypothesis-formulation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/hypothesis-formulationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aiming-lab/AutoResearchClaw --skill hypothesis-formulation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aiming-lab/AutoResearchClaw hypothesis-formulation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/hypothesis-formulation .agents/skills/hypothesis-formulation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "hypothesis-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/hypothesis-formulation into .agents/skills/hypothesis-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hypothesis-formulation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aiming-lab/AutoResearchClaw --skill hypothesis-formulation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aiming-lab/AutoResearchClaw hypothesis-formulation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/hypothesis-formulation .cursor/skills/hypothesis-formulation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "hypothesis-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/hypothesis-formulation into .cursor/skills/hypothesis-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hypothesis-formulation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aiming-lab/AutoResearchClaw.git --path .claude/skills/hypothesis-formulation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aiming-lab/AutoResearchClaw --skill hypothesis-formulation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aiming-lab/AutoResearchClaw hypothesis-formulation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/hypothesis-formulation .gemini/skills/hypothesis-formulation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "hypothesis-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/hypothesis-formulation into .gemini/skills/hypothesis-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hypothesis-formulation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aiming-lab/AutoResearchClaw hypothesis-formulationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aiming-lab/AutoResearchClaw --skill hypothesis-formulation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/hypothesis-formulation .github/skills/hypothesis-formulation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "hypothesis-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/hypothesis-formulation into .github/skills/hypothesis-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hypothesis-formulation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aiming-lab/AutoResearchClaw --skill hypothesis-formulation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aiming-lab/AutoResearchClaw hypothesis-formulation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/hypothesis-formulation .opencode/skills/hypothesis-formulation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "hypothesis-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/hypothesis-formulation into .opencode/skills/hypothesis-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hypothesis-formulation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
hypothesis-formulation- GitHub stars
- 15k
- Token cost
- ~628 tokens
- SKILL.md length
- 273 words
- Files
- 1
- Skills in repo
- 34
- Repo updated
- First seen
- Licence
- MIT
At a glance
Guides turning an observation into testable, falsifiable hypotheses with null and alternative statements, competing explanations and predictions tied to experimental design.
- Works in 5 steps: Start with a clear observation or… → Review existing literature for known… → Identify what is already established vs.… → …
- Turning a surprising observation into a testable hypothesis
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Writing null and alternative hypotheses before designing an experiment
What it does
A hypothesis is developed in steps: start from a clear observation, review the literature for known mechanisms, separate what is established from what is uncertain, and state a specific, testable claim with the outcome that would refute it defined in advance. The skill asks for a null hypothesis (H0, no effect) and an alternative (H1, a directional effect), with experiments designed to reject H0, and suggests an if, then, because pattern for mechanistic hypotheses.
It also covers competing explanations and predictions. The agent proposes two or three plausible hypotheses, finds the unique prediction of each, ranks them by parsimony, prior evidence and testability, and considers confounds. Predictions should be measurable, with an expected direction, a rough size and the conditions that would confirm or refute them. The last part links hypotheses to experimental design: sample size and power analysis, pre-registration where possible, confirmatory versus exploratory analyses, and a plan for positive and null results.
When your agent uses it
- Turning a surprising observation into a testable hypothesis
- Writing null and alternative hypotheses before designing an experiment
- Comparing competing explanations and deciding which experiment separates them
Example prompts
- “Our churn dropped after the redesign. Formulate competing hypotheses and the predictions that separate them.”
- “Write H0 and H1 for whether the new learning rate schedule improves validation accuracy.”
- “Check whether my hypothesis is falsifiable and say what result would refute it.”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Start with a clear observation or pattern that requires explanation
- Review existing literature for known mechanisms and prior explanations
- Identify what is already established vs. what remains uncertain
- Formulate the hypothesis as a specific, testable statement
- Ensure the hypothesis is falsifiable — define what outcome would refute it
What it can do on your machine
Read from SKILL.md and the folder at commit be4ba47. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Hypothesis Formulation loads about 628 tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 273 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from aiming-lab/AutoResearchClaw at commit be4ba47, republished under its MIT licence (© aiming-lab). 273 words, ~628 tokens.
Download SKILL.mdSave it as
.claude/skills/hypothesis-formulation/SKILL.md (or your agent's skills folder).- name
- hypothesis-formulation
- description
- Structured scientific hypothesis generation from observations. Use when formulating testable hypotheses, competing explanations, or experimental predictions.
- metadata.category
- experiment
- metadata.trigger-keywords
- hypothesis,prediction,mechanism,falsifiable,null,alternative,testable
- metadata.applicable-stages
- 7,8,9
- metadata.priority
- 3
- metadata.version
- 1.0
- metadata.author
- researchclaw
- metadata.references
- adapted from K-Dense-AI/claude-scientific-skills
Hypothesis Formulation Best Practice
Structured Hypothesis Development
- Start with a clear observation or pattern that requires explanation
- Review existing literature for known mechanisms and prior explanations
- Identify what is already established vs. what remains uncertain
- Formulate the hypothesis as a specific, testable statement
- Ensure the hypothesis is falsifiable — define what outcome would refute it
Hypothesis Format
- Null hypothesis (H0): There is no effect or no difference
- Alternative hypothesis (H1): There is a specific, directional effect
- State both explicitly; design experiments to reject H0
- Use "If... then... because..." structure for mechanistic hypotheses:
- If [independent variable is manipulated], then [predicted outcome], because [proposed mechanism]
Generating Competing Hypotheses
- Propose at least 2-3 plausible explanations for the same observation
- For each, identify unique predictions that distinguish it from alternatives
- Rank hypotheses by parsimony, consistency with prior evidence, and testability
- Design experiments that can discriminate between competing hypotheses
- Consider confounding variables that could produce the same observation
Testable Predictions
- Derive specific, measurable predictions from each hypothesis
- Define expected effect direction AND approximate magnitude
- Specify what experimental conditions would confirm vs. refute the prediction
- Identify potential confounds and plan controls to address them
- Ensure predictions are achievable with available methods and resources
Aligning with Experimental Design
- Map each hypothesis to a concrete experimental condition or comparison
- Ensure sample size is adequate to detect the predicted effect (power analysis)
- Pre-register hypotheses and analysis plans when possible
- Distinguish confirmatory (hypothesis-testing) from exploratory analyses
- Plan for both positive and null results — what will you conclude in each case?
© aiming-lab, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .claude/skills/hypothesis-formulation of aiming-lab/AutoResearchClaw.
Open the folder on GitHubat commit be4ba47
Compare with similar skills
Hypothesis Formulation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Hypothesis Formulation this skillaiming-lab/AutoResearchClaw | 15k | — | ~628 | Automated safety check: Pass | MIT | |
| Claim-Driven Experiment PlannerzjYao36/Auto-Research-Refine | 128 | 7 repos | ~2.3k | Automated safety check: Notes | None | |
| Research RefinezjYao36/Auto-Research-Refine | 128 | 7 repos | ~6.9k | Automated safety check: Notes | None | |
| Scientific BrainstormingOleafly/Oleafly | 205 | 2 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Academic GrillExekiel179/psyclaw | 103 | — | ~2k | Automated safety check: Pass | MIT | |
| Denariodavila7/claude-code-templates | 32k | 9 repos | ~1.5k | Automated safety check: Notes | MIT |
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Related
Categories
Questions about Hypothesis Formulation
What does Hypothesis Formulation do?
Guides turning an observation into testable, falsifiable hypotheses with null and alternative statements, competing explanations and predictions tied to experimental design. A hypothesis is developed in steps: start from a clear observation, review the literature for known mechanisms, separate what is established from what is uncertain, and state a specific, testable claim with the outcome that would refute it defined in advance. The skill asks for a null hypothesis (H0, no effect) and an alternative (H1, a directional effect), with experiments designed to reject H0, and suggests an if, then, because pattern for mechanistic hypotheses.
When should I use Hypothesis Formulation?
Hypothesis Formulation fits situations like: turning a surprising observation into a testable hypothesis; writing null and alternative hypotheses before designing an experiment; comparing competing explanations and deciding which experiment separates them.
How do I install Hypothesis Formulation in Claude Code?
Run `npx skills add aiming-lab/AutoResearchClaw --skill hypothesis-formulation -a claude-code`. Or copy the skill folder (.claude/skills/hypothesis-formulation in aiming-lab/AutoResearchClaw) into .claude/skills/hypothesis-formulation in your project. Claude Code loads it when a task matches its description.
How do I install Hypothesis Formulation in Codex?
Run `npx skills add aiming-lab/AutoResearchClaw --skill hypothesis-formulation -a codex`. Or copy the skill folder (.claude/skills/hypothesis-formulation in aiming-lab/AutoResearchClaw) into .agents/skills/hypothesis-formulation in your project. Codex loads it when a task matches its description.
Can I use Hypothesis Formulation in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aiming-lab/AutoResearchClaw --skill hypothesis-formulation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hypothesis-formulation, .gemini/skills/hypothesis-formulation, .github/skills/hypothesis-formulation and .opencode/skills/hypothesis-formulation in your project.
What does Hypothesis Formulation need to run?
SKILL.md names no scripts, command-line tools or credentials: Hypothesis Formulation is instructions for the agent only.
Does Hypothesis Formulation access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Hypothesis Formulation safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Hypothesis Formulation use?
Hypothesis Formulation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Hypothesis Formulation use?
About 628 tokens (SKILL.md is roughly 2.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Hypothesis Formulation?
Skills that share tags, products or a category with Hypothesis Formulation: Claim-Driven Experiment Planner (zjYao36/Auto-Research-Refine, 128 stars), Research Refine (zjYao36/Auto-Research-Refine, 128 stars), Scientific Brainstorming (Oleafly/Oleafly, 205 stars) and Academic Grill (Exekiel179/psyclaw, 103 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Hypothesis Formulation?
aiming-lab (a GitHub organization) maintains it in aiming-lab/AutoResearchClaw, which has 14,587 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on August 19, 2026.
Source: aiming-lab/AutoResearchClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.