VeraSuperHub

Stat Research Pipeline — Testing skill for Claude Code

Testing community

Open-source AI skills for AI-assisted statistical research workflows: assumption checks, test selection, modeling, manuscript-section drafting, and review checkpoints.

How to install Stat Research Pipeline

This entry records only its repository, not the path inside it, so there is no exact command to give. Open VeraSuperHub/stat-research-pipeline and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Stat Research Pipeline does

Open-source AI skills for AI-assisted statistical research workflows: assumption checks, test selection, modeling, manuscript-section drafting, and review checkpoints.

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README

Statistical Research Pipeline

Open-source statistical research skills for Claude Code and Codex-compatible workflows.

This repository packages the Vera data/statistical research skill family for outcome detection, assumption checks, primary test selection, extended modeling, SEM workflows, manuscript-section drafting, LaTeX-ready artifact assembly, and review checkpoints.

Vera structures the execution layer. Researchers own study design, assumptions, interpretation, and submission decisions.

Skill Inventory

Reviewing Skills

Skill	Domain	Role
`vera-data-binary-reviewing`	Binary	Review inputs, assumptions, primary-test readiness, reporting constraints, and evidence quality.
`vera-data-cfa-reviewing`	CFA	Review inputs, assumptions, primary-test readiness, reporting constraints, and evidence quality.
`vera-data-continuous-reviewing`	Continuous	Review inputs, assumptions, primary-test readiness, reporting constraints, and evidence quality.
`vera-data-count-reviewing`	Count	Review inputs, assumptions, primary-test readiness, reporting constraints, and evidence quality.
`vera-data-doe-reviewing`	DOE	Review inputs, assumptions, primary-test readiness, reporting constraints, and evidence quality.
`vera-data-growth-reviewing`	Growth/change	Review inputs, assumptions, primary-test readiness, reporting constraints, and evidence quality.
`vera-data-meta-reviewing`	Meta-analysis	Review inputs, assumptions, primary-test readiness, reporting constraints, and evidence quality.
`vera-data-multivariate-reviewing`	Multivariate	Review inputs, assumptions, primary-test readiness, reporting constraints, and evidence quality.
`vera-data-nominal-reviewing`	Nominal	Review inputs, assumptions, primary-test readiness, reporting constraints, and evidence quality.
`vera-data-ordinal-reviewing`	Ordinal	Review inputs, assumptions, primary-test readiness, reporting constraints, and evi