Hypothesis Generation
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
Formulate statistical research problems with formal notation, target parameters, assumptions, hypotheses, evaluation criteria, and theory targets.
Install Statistical Problem Formulation
$ npx skills add aiming-lab/AutoResearchClaw --skill statistical-problem-formulation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aiming-lab/AutoResearchClaw statistical-problem-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/external/agents/stat_research_agent/skills/statistical-problem-formulation .claude/skills/statistical-problem-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 "statistical-problem-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/external/agents/stat_research_agent/skills/statistical-problem-formulation into .claude/skills/statistical-problem-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-problem-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/external/agents/stat_research_agent/skills/statistical-problem-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 statistical-problem-formulation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aiming-lab/AutoResearchClaw statistical-problem-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/external/agents/stat_research_agent/skills/statistical-problem-formulation .agents/skills/statistical-problem-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 "statistical-problem-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/external/agents/stat_research_agent/skills/statistical-problem-formulation into .agents/skills/statistical-problem-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-problem-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 statistical-problem-formulation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aiming-lab/AutoResearchClaw statistical-problem-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/external/agents/stat_research_agent/skills/statistical-problem-formulation .cursor/skills/statistical-problem-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 "statistical-problem-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/external/agents/stat_research_agent/skills/statistical-problem-formulation into .cursor/skills/statistical-problem-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-problem-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 external/agents/stat_research_agent/skills/statistical-problem-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 statistical-problem-formulation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aiming-lab/AutoResearchClaw statistical-problem-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/external/agents/stat_research_agent/skills/statistical-problem-formulation .gemini/skills/statistical-problem-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 "statistical-problem-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/external/agents/stat_research_agent/skills/statistical-problem-formulation into .gemini/skills/statistical-problem-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-problem-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 statistical-problem-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 statistical-problem-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/external/agents/stat_research_agent/skills/statistical-problem-formulation .github/skills/statistical-problem-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 "statistical-problem-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/external/agents/stat_research_agent/skills/statistical-problem-formulation into .github/skills/statistical-problem-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-problem-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 statistical-problem-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 statistical-problem-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/external/agents/stat_research_agent/skills/statistical-problem-formulation .opencode/skills/statistical-problem-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 "statistical-problem-formulation" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/external/agents/stat_research_agent/skills/statistical-problem-formulation into .opencode/skills/statistical-problem-formulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-problem-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
statistical-problem-formulation- GitHub stars
- 15k
- Token cost
- ~671 tokens
- SKILL.md length
- 162 words
- Files
- 1
- Skills in repo
- 34
- Repo updated
- First seen
- Licence
- MIT
At a glance
Formulate statistical research problems with formal notation, target parameters, assumptions, hypotheses, evaluation criteria, and theory targets.
- Research & Science work in your project
- SKILL.md covers Overview, Required Formulation Elements, Handoff Schema and Template, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Statistical Problem Formulation is an agent skill from aiming-lab/AutoResearchClaw. Formulate statistical research problems with formal notation, target parameters, assumptions, hypotheses, evaluation criteria, and theory targets.
Its SKILL.md is about 670 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science. The repository describes itself as: Fully autonomous & self-evolving research from idea to paper. Chat an Idea. Get a Paper. 🦞. The licence is MIT.
When your agent uses it
- Research & Science work in your project
Example prompts
- “/statistical-problem-formulation”
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 (its code samples are yaml and markdown).
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
Statistical Problem Formulation loads about 671 tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 162 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). 162 words, ~671 tokens.
Download SKILL.mdSave it as
.claude/skills/statistical-problem-formulation/SKILL.md (or your agent's skills folder).- name
- statistical-problem-formulation
- description
- Formulate statistical research problems with formal notation, target parameters, assumptions, hypotheses, evaluation criteria, and theory targets.
- metadata.category
- domain
- metadata.trigger-keywords
- problem formulation,statistical formulation,estimand,assumptions,data model,hypothesis,theory target
- metadata.applicable-stages
- 1,2,3,4,5
- metadata.priority
- 1
Statistical Problem Formulation
Overview
Use this skill before any method design, theory, experiment, or report writing. The goal is to transform a broad topic into a precise statistical problem.
Required Formulation Elements
| Element | Questions |
|---|---|
| Observed data | What is observed? What is the sample size? Are samples iid, dependent, clustered, censored, or selected? |
| Data model | What family of distributions or data-generating processes is considered? |
| Target | What parameter, decision, prediction, or risk is the object of study? |
| Assumptions | What must hold for the target to be identifiable or the method to work? |
| Hypotheses | What claims should be supported, refuted, or made inconclusive? |
| Criteria | What metrics define success or failure? |
| Theory target | What property should be derived: bias, variance, consistency, rate, coverage, error bound, robustness, or impossibility? |
Handoff Schema
The problem formulation should be precise enough to support this structured handoff:
topic_id: TXX
title: ""
research_question: ""
observed_data:
notation: ""
sampling: iid | dependent | clustered | time_series | selected | unknown
data_model:
notation: ""
family: ""
target:
name: ""
notation: ""
type: estimand | decision | prediction | risk | descriptive_quantity
truth_source: analytic | simulation | oracle | empirical_reference | not_applicable
assumptions:
structural: []
sampling: []
regularity: []
identifiability: []
claims:
- id: C1
statement: ""
formal_statement: ""
evaluation_criteria:
- name: ""
direction: ""
theory_targets:
- identifiability
- bias
- consistency
blocking_ambiguities: []Template
# Problem Formulation
## Research Question
...
## Observed Data
Let ...
## Data-Generating Model
Assume ...
## Target / Estimand
Define ...
## Candidate Procedure Class
We consider procedures ...
## Assumptions
1. ...
## Claims / Hypotheses
- ...
## Evaluation Criteria
- ...
## Theoretical Questions
- ...
## Experimental Questions
- ...Quality Bar
A formulation passes only if another researcher could implement or analyze the problem without guessing the target, assumptions, or success criteria.
© 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 external/agents/stat_research_agent/skills/statistical-problem-formulation of aiming-lab/AutoResearchClaw.
Open the folder on GitHubat commit be4ba47
Compare with similar skills
Statistical Problem 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 |
|---|---|---|---|---|---|---|
| Statistical Problem Formulation this skillaiming-lab/AutoResearchClaw | 15k | — | ~671 | Automated safety check: Pass | MIT | |
| Hypothesis Generationspacering-net/codeg | 3.8k | 15 repos | ~3.6k | Automated safety check: Notes | MIT | |
| GitHub Deep Researchbytedance/deer-flow | 83k | 5 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Nature Paper CardYuan1z0825/nature-skills | 46k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Read arXiv Paperkarpathy/nanochat | 58k | 2 repos | ~494 | Automated safety check: Pass | MIT | |
| Content Research Writerweapp-tailwindcss/weapp-tailwindcss | 1.9k | 25 repos | ~3.5k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Statistical Problem Formulation
What does Statistical Problem Formulation do?
Formulate statistical research problems with formal notation, target parameters, assumptions, hypotheses, evaluation criteria, and theory targets. Statistical Problem Formulation is an agent skill from aiming-lab/AutoResearchClaw. Formulate statistical research problems with formal notation, target parameters, assumptions, hypotheses, evaluation criteria, and theory targets.
When should I use Statistical Problem Formulation?
Statistical Problem Formulation fits situations like: research & Science work in your project.
How do I install Statistical Problem Formulation in Claude Code?
Run `npx skills add aiming-lab/AutoResearchClaw --skill statistical-problem-formulation -a claude-code`. Or copy the skill folder (external/agents/stat_research_agent/skills/statistical-problem-formulation in aiming-lab/AutoResearchClaw) into .claude/skills/statistical-problem-formulation in your project. Claude Code loads it when a task matches its description.
How do I install Statistical Problem Formulation in Codex?
Run `npx skills add aiming-lab/AutoResearchClaw --skill statistical-problem-formulation -a codex`. Or copy the skill folder (external/agents/stat_research_agent/skills/statistical-problem-formulation in aiming-lab/AutoResearchClaw) into .agents/skills/statistical-problem-formulation in your project. Codex loads it when a task matches its description.
Can I use Statistical Problem 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 statistical-problem-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/statistical-problem-formulation, .gemini/skills/statistical-problem-formulation, .github/skills/statistical-problem-formulation and .opencode/skills/statistical-problem-formulation in your project.
What does Statistical Problem Formulation need to run?
SKILL.md names no scripts, command-line tools or credentials: Statistical Problem Formulation is instructions for the agent only.
Does Statistical Problem 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 Statistical Problem 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 Statistical Problem Formulation use?
Statistical Problem 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 Statistical Problem Formulation use?
About 671 tokens (SKILL.md is roughly 2.7k 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 Statistical Problem Formulation?
Skills that share tags, products or a category with Statistical Problem Formulation: Hypothesis Generation (spacering-net/codeg, 3.8k stars), GitHub Deep Research (bytedance/deer-flow, 83k stars), Nature Paper Card (Yuan1z0825/nature-skills, 46k stars) and Read arXiv Paper (karpathy/nanochat, 58k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Statistical Problem 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.