Replication Package
Assemble a submission-ready replication package to the AEA Data and Code Availability...
Install
npx skills add pedrohcgs/claude-code-my-workflow --skill replication-package -g -a claude-code -y- Repository
- pedrohcgs/claude-code-my-workflow1.7k
- Category
- Data and ML
- Updated
- 1mo ago
- License
- MIT
- Context cost
- Mediumabout 2,551 tokens
- Runs scripts
- No, instructions only
What it does
Assemble a submission-ready replication package to the AEA Data and Code Availability Standard (DCAS) / openICPSR / Social Science Reproduction Platform expectations, standard replication README, dataset manifest, computational-requirements capture, a Table/Figure → script:line map, and a confidential-data deposit plan. Use when user says "build the replication package", "prepare the openICPSR deposit", "make the AEA data and code package", "DCAS compliance", "assemble the deposit for the journal", or after a paper is accepted and the journal's data editor needs the package. NOT a numeric verifier, it calls /audit-reproducibility to confirm claims reproduce before packaging.
Replication Package
Produce the deposit an economist hands a journal at acceptance: a directory tree (data/, code/, output/, README) plus a DCAS compliance checklist, built to the AEA Data and Code Availability Standard, openICPSR deposit expectations, and the Social Science Reproduction Platform reproduction protocol. This skill moves the repo from auditing reproducibility to producing the deposit, /audit-reproducibility proves the numbers; this skill packages everything a third party needs to regenerate them from scratch.
Core principle: the package is reproducible by a stranger with the data and the README, no tacit knowledge, no "ask the author" steps. Every table and figure maps to the exact script and line that produces it.
When to use
- At acceptance. The journal's data editor (AEA, REStud, JPE, EJ, ...) requests a DCAS-compliant deposit before the paper is typeset.
- Before an openICPSR / Zenodo / Dataverse upload. Build the tree and README once, locally, before the web upload.
- Pre-submission dry run. Catch the "I never wrote down where Table 3 comes from" gap while it is cheap to fix.
- Confidential-data papers. Produce the access-restricted-data note and a runnable-on-restricted-data package even when the data itself cannot be deposited.
Inputs
$0, path to the manuscript (.tex,.qmd,.md,.pdf). Required (the source of the Table/Figure inventory).$1, outputs directory. Defaults tooutput/, where every language's pipeline writes. Recognised alternative:_targets/objects/. Ifoutput/does not exist but a pre-v2.6scripts/<lang>/_outputs/does, use that and say so.
