Agent Skillsbrycewang-stanford/Awesome-Journal-Skills › expecon-replication-package

expecon-replication-package

GitHub

用于汇编实验经济学论文的数据、代码及说明,以满足ESA可重复性标准。构建包含指令、软件、原始数据和分析脚本的归档包,确保他人能复现结果或重运行实验,但不执行分析或撰写正文。

Experimental-Economics-Skills/skills/expecon-replication-package/SKILL.md brycewang-stanford/Awesome-Journal-Skills

Trigger Scenarios

准备提交论文并需附上参与者说明和数据/代码附录时 尚未组装符合ESA政策的信任存储库归档包时 审稿人或编辑询问能否复现数字并重运行实验时

Install

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill expecon-replication-package -g -y
More Options

Non-standard path

npx skills add https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Experimental-Economics-Skills/skills/expecon-replication-package -g -y

Use without installing

npx skills use brycewang-stanford/Awesome-Journal-Skills@expecon-replication-package

指定 Agent (Claude Code)

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill expecon-replication-package -a claude-code -g -y

安装 repo 全部 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --all -g -y

预览 repo 内 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --list

SKILL.md

Frontmatter
{
    "name": "expecon-replication-package",
    "description": "Use when assembling the data, code, instructions, and experiment software for an Experimental Economics (ExpEcon) manuscript to meet the ESA reproducibility standard. Builds the deposit; it does not run the analysis or draft prose."
}

Replication Package (expecon-replication-package)

When to trigger

  • You are preparing to submit and must attach participant instructions (required at submission) and a data/code appendix
  • The ESA Data and Replication Policy deposit (trusted repository) is not yet assembled
  • z-Tree / oTree code, raw session data, and analysis scripts are scattered and not runnable end-to-end
  • A referee or editor asks whether someone could reproduce your numbers and re-run your experiment

What ExpEcon reproducibility actually requires

Experimental Economics is an ESA journal, and since 2021 the ESA Data and Replication Policy requires authors to deposit, in a trusted online repository, the materials needed to reproduce or replicate the study (检索于 2026-06;以官网为准). Reproducibility here is stronger than at most economics journals because it has two layers:

  • Reproduce the analysis — raw data + cleaning + analysis code regenerate every table and figure.
  • Replicate the experiment — instructions + experiment software let another lab re-run the study.

Treat the package as a deliverable engineered for both.

The deposit, component by component

  1. Instructions — the exact instructions subjects received, per treatment, in the original language (translation if relevant). These are required at submission, not just at acceptance; reviewers read them to check for deception and comprehension.
  2. Experiment software — the z-Tree .ztt treatment files or the oTree app (full project, settings.py, requirements pinned). Include screenshots or the comprehension quiz as run. This is what makes re-running possible.
  3. Raw data — session-level exports as collected (z-Tree .xls/.sbj, oTree CSV), with a codebook for every variable and the session/treatment/matching-group identifiers.
  4. Analysis code — scripts (Stata/R/Python) that run from raw to results with a single master file; set and record the random seed for any simulation/permutation test.
  5. README — repository map, software versions, run order, expected runtime, and a table mapping each exhibit in the paper to the script that produces it.
  6. Pre-registration / PAP link — the registry entry and timestamp; for a Registered Report, the in-principle-acceptance Stage-1 protocol.
  7. Ethics / consent — IRB approval reference and the consent procedure (and the explicit no-deception statement).

Repository and hygiene

  • Deposit in a trusted, persistent repository (OSF, Harvard Dataverse, Zenodo, or OpenICPSR are commonly used by ESA authors) and cite the DOI in the paper.
  • Anonymize subject identifiers; never include payment records with identifying info.
  • Pin every dependency and software version; a package that does not run on a clean machine fails the policy.
  • Match repository contents to the paper exactly — no stale scripts, no figures the code cannot produce.

A workable directory layout

/instructions    treatment_A.pdf, treatment_B.pdf (+ translations)
/software         ztree/  *.ztt    OR   otree/  (full app, requirements.txt)
/data/raw         session exports as collected (.xls/.sbj or .csv)
/data/clean       analysis-ready files built by /code
/code             00_master.* , 01_clean.* , 02_analysis.* , 03_figures.*
/output           tables + figures regenerated by /code
README.md         map, versions, run order, exhibit→script table
ETHICS.md         IRB ref, consent text, no-deception statement

The single rule the policy enforces in spirit: a stranger with a clean machine runs 00_master and gets your paper's exact numbers, and another lab opens /software and /instructions and re-runs your experiment.

The two-layer self-test

  1. Reproduce: delete /data/clean and /output, run the master script, confirm every table/figure regenerates byte-for-byte (or value-for-value for stochastic steps with a fixed seed).
  2. Replicate: hand /software + /instructions to a colleague who was not on the project and confirm they can launch a session and understand what subjects faced.

Checklist

  • Participant instructions (all treatments, original language) included at submission
  • z-Tree .ztt / oTree app deposited so the experiment can be re-run
  • Raw session data + codebook + session/group/treatment IDs present
  • Master analysis script runs raw→results; seeds set for simulation/permutation
  • README maps every table/figure to the script that generates it; versions pinned
  • Pre-registration / PAP (or Stage-1 RR protocol) linked with timestamp
  • Trusted-repository DOI cited; data anonymized; IRB + no-deception statement included

Anti-patterns

  • Promising the package "on request" or only at acceptance — ESA expects a real deposit, and instructions are due at submission
  • Depositing data but not the z-Tree/oTree code, so the experiment cannot be replicated
  • A "replication package" whose scripts do not reproduce the paper's exact numbers
  • Unpinned software versions / no seed, so permutation tests and figures are not reproducible
  • Identifiable subject data or payment records left in the repository

Output format

【Journal】Experimental Economics (ESA method flagship)
【Skill】expecon-replication-package
【Verdict】deposit-ready / incomplete
【Instructions】all treatments, at submission? [Y/N]
【Software】z-Tree .ztt / oTree app deposited (re-runnable)? [Y/N]
【Data + code】raw + codebook + master script (seeded) reproduce all exhibits? [Y/N]
【Repository】trusted-repo DOI; versions pinned; anonymized? [Y/N]
【Pre-reg / ethics】PAP/RR link + IRB + no-deception statement
【Next skill】expecon-referee-strategy

Version History

  • 1839142 Current 2026-07-05 13:13

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