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Agent skill

Ecj Replication Package

by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills

A skill your agent uses when assembling the data and code replication package for a The Economic Journal (EJ) manuscript to the RES / EJ Data Editor standard (DCAS-endorsed, Zenodo deposit…

MITAuto-check passedResearch & Science

Install Ecj Replication Package

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ecj-replication-package -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ecj-replication-package --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/The-Economic-Journal-Skills/skills/ecj-replication-package .claude/skills/ecj-replication-package && rm -rf skills-src

Use ~/.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/

Facts

Skill name
ecj-replication-package
GitHub stars
1.2k
Token cost
~1.5k tokens
SKILL.md length
731 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when assembling the data and code replication package for a The Economic Journal (EJ) manuscript to the RES / EJ Data Editor standard (DCAS-endorsed, Zenodo deposit…

  • Works in 4 steps: README (the centerpiece) following the… → Data: raw inputs (when license permits)… → Code: a master script that reproduces… → …
  • Reproducibility check before final acceptance)
  • SKILL.md covers When to trigger, What a passing package contains, Reproducibility discipline and Restricted / proprietary data…, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ecj Replication Package is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when assembling the data and code replication package for a The Economic Journal (EJ) manuscript to the RES / EJ Data Editor standard (DCAS-endorsed, Zenodo deposit, reproducibility check before final acceptance). Builds the package and README; it does not run the analysis itself.

Its SKILL.md is about 1.5k 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, covering Econometrics and empirical research and Reproducible research. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.

When your agent uses it

  • Reproducibility check before final acceptance)
  • Tasks that involve Econometrics and empirical research
  • Tasks that involve Reproducible research

Example prompts

  • “/ecj-replication-package”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. README (the centerpiece) following the DCAS / Social Science Data Editors README template
  2. Data: raw inputs (when license permits) and the code that builds analysis files from them. Provide complete documentation of all…
  3. Code: a master script that reproduces every number, table, and figure from raw inputs, with relative paths and fixed seeds.
  4. Output: log files and generated exhibits, so the editor can diff against the paper.

What it can do on your machine

Read from SKILL.md and the folder at commit 932eb23. 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

Ecj Replication Package loads about 1.5k tokens when it runs. Until then it costs about 77 tokens; SKILL.md has 731 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~77
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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 brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 731 words, ~1,528 tokens.

Download SKILL.mdSave it as .claude/skills/ecj-replication-package/SKILL.md (or your agent's skills folder).
name
ecj-replication-package
description
Use when assembling the data and code replication package for a The Economic Journal (EJ) manuscript to the RES / EJ Data Editor standard (DCAS-endorsed, Zenodo deposit, reproducibility check before final acceptance). Builds the package and README; it does not run the analysis itself.

Replication Package (ecj-replication-package)

When to trigger

  • The paper is heading toward acceptance and the EJ Data Editor needs a reproducible deposit
  • You want the package to pass the EJ Data Editor's reproducibility check on the first pass
  • Some data are proprietary or restricted and you must request an exemption and document access
  • You are setting up the project early so reproducibility is not a last-minute scramble

Verify the current policy on the EJ Data Editor site (ejdataeditor.github.io) and the OUP Instructions before depositing. EJ runs pre-acceptance reproducibility checks: the paper is accepted for final publication only after results have been checked for reproducibility. The package is posted to the journal's Zenodo repository or another trusted repository and linked from the paper. It is essential to request a data exemption at the point of first submission if you face any access restrictions.

What a passing package contains

  1. README (the centerpiece) following the DCAS / Social Science Data Editors README template:
    • Overview of what the code does and the mapping from code → every exhibit and in-text number.
    • Data availability statement: source, terms, whether each dataset is public / restricted / proprietary, and exact access steps (registrations, memberships, monetary and time costs). State clearly if data cannot be shared and why, referencing the exemption requested at first submission.
    • Computational requirements: software + versions, packages + versions, OS, memory, and approximate run time.
    • Instructions to run: a single master script ordering everything end to end.
    • List of every table/figure/in-text number with the script and line that produces it.
  2. Data: raw inputs (when license permits) and the code that builds analysis files from them. Provide complete documentation of all variables; if data are in a proprietary format (e.g., Stata .dta), also provide an ASCII/plain-text copy such as .csv. If raw data are restricted, include construction code plus a synthetic/simulated dataset that lets the pipeline run.
  3. Code: a master script that reproduces every number, table, and figure from raw inputs, with relative paths and fixed seeds.
  4. Output: log files and generated exhibits, so the editor can diff against the paper.

Reproducibility discipline

  • One master script; no manual steps, no hard-coded absolute paths, no "run cell 4 then cell 2."
  • Set and record random seeds for any simulation, bootstrap, or ML step.
  • Pin software and package versions; record them in the README and, where possible, in a lockfile/environment file.
  • Every exhibit and in-text number in the paper is regenerated by the code — no hand-edited tables.
  • Directory layout is clean: data/ (raw, derived), code/ (build, analysis), output/ (tables, figures, logs).
Show full SKILL.md (310 more words)Show less

Restricted / proprietary data (the EJ exemption route)

  • Request the exemption at first submission, not at acceptance — the EJ Data Editor stresses this timing.
  • You may not need to deposit the data, but you must deposit the code and a precise access path so a third party with the same license can reproduce results.
  • Provide a Data Availability Statement and, where feasible, a small simulated dataset matching the schema so the pipeline is executable.
  • Confidential-data results may require a verification arrangement with the EJ Data Editor; document it.

Checklist

  • README follows the DCAS template (overview, data availability, requirements, run instructions, exhibit map)
  • Deposit goes to the journal's Zenodo repository (or another trusted repository) with a license allowing replication
  • Package layout matches EJ guidance: 1-paper, 2-appendices, README.pdf, 3-replication-package.zip, and optional 4-confidential-data-not-for-publication.zip
  • Single master script reproduces every table, figure, and in-text number from inputs
  • Software and package versions pinned and recorded
  • Random seeds set and documented
  • Relative paths only; runs on a clean machine in a fresh directory
  • All variables documented; proprietary-format data also provided as ASCII/plain text
  • Data availability statement covers each dataset (public / restricted / proprietary) with access steps and costs
  • Restricted data: exemption requested at first submission
  • Package re-run from scratch and output diffed against the paper, ready for the EJ Data Editor
  • Current EJ/RES data policy (DCAS, Zenodo, EJ Data Editor) verified on the official pages

Anti-patterns

  • A zip of scripts with no README and no code → exhibit mapping
  • Absolute paths (/Users/me/...) that break on any other machine
  • Unset seeds so bootstrap/simulation numbers do not reproduce
  • "Data available on request" with no construction code and no access detail
  • Requesting a restricted-data exemption only at acceptance instead of at first submission
  • Proprietary-only data with no ASCII/plain-text companion and no variable documentation
  • Hand-edited tables that the code does not actually generate
  • Submitting without re-running the package on a clean environment

Output format

【Policy verified】EJ/RES data policy (DCAS, Zenodo, EJ Data Editor) checked on official pages [y/n]
【README】DCAS template sections present? [y/n each]
【Deposit】Zenodo (or trusted repo) + replication license attached? [y/n]
【Master script】reproduces all exhibits + in-text numbers from raw? [y/n]
【Versions + seeds】pinned/documented? [y/n]
【Data status】public / restricted (exemption at first submission) + access path; ASCII companion? [y/n]
【Clean-machine test】passed, ready for EJ Data Editor? [y/n]
【Next】ecj-submission

© brycewang-stanford, 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 The-Economic-Journal-Skills/skills/ecj-replication-package of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Ecj Replication Package 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.

Ecj Replication Package compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ecj Replication Package this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~1.5kAutomated safety check: PassMIT
Replication Packagepedrohcgs/claude-code-my-workflow1.6k—~2.8kAutomated safety check: NotesMIT
Audit Reproducibilitypedrohcgs/claude-code-my-workflow1.6k—~6.4kAutomated safety check: NotesMIT
Reproducible Pipelinesbrycewang-stanford/Auto-Empirical-Research-Skills4.5k—~3.3kAutomated safety check: PassCustom licence
Audit Replicationbrycewang-stanford/Auto-Empirical-Research-Skills4.5k—~984Automated safety check: NotesCustom licence
Scholar Openjoshzyj/open-scholar-skill168—~14kAutomated safety check: PassCustom licence

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Categories

Questions about Ecj Replication Package

What does Ecj Replication Package do?

A skill your agent uses when assembling the data and code replication package for a The Economic Journal (EJ) manuscript to the RES / EJ Data Editor standard (DCAS-endorsed, Zenodo deposit…. Ecj Replication Package is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when assembling the data and code replication package for a The Economic Journal (EJ) manuscript to the RES / EJ Data Editor standard (DCAS-endorsed, Zenodo deposit, reproducibility check before final acceptance).

When should I use Ecj Replication Package?

Ecj Replication Package fits situations like: reproducibility check before final acceptance); tasks that involve Econometrics and empirical research; tasks that involve Reproducible research.

How do I install Ecj Replication Package in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ecj-replication-package -a claude-code`. Or copy the skill folder (The-Economic-Journal-Skills/skills/ecj-replication-package in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/ecj-replication-package in your project. Claude Code loads it when a task matches its description.

How do I install Ecj Replication Package in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ecj-replication-package -a codex`. Or copy the skill folder (The-Economic-Journal-Skills/skills/ecj-replication-package in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/ecj-replication-package in your project. Codex loads it when a task matches its description.

Can I use Ecj Replication Package 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 brycewang-stanford/Awesome-Journal-Skills --skill ecj-replication-package -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ecj-replication-package, .gemini/skills/ecj-replication-package, .github/skills/ecj-replication-package and .opencode/skills/ecj-replication-package in your project.

What does Ecj Replication Package need to run?

SKILL.md names no scripts, command-line tools or credentials: Ecj Replication Package is instructions for the agent only.

Does Ecj Replication Package 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 Ecj Replication Package 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 Ecj Replication Package use?

Ecj Replication Package 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 Ecj Replication Package use?

About 1.5k tokens (SKILL.md is roughly 6.1k 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 Ecj Replication Package?

Skills that share tags, products or a category with Ecj Replication Package: Replication Package (pedrohcgs/claude-code-my-workflow, 1.6k stars), Audit Reproducibility (pedrohcgs/claude-code-my-workflow, 1.6k stars), Reproducible Pipelines (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars) and Audit Replication (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ecj Replication Package?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,219 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.

Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.