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Use when assembling the data and code replication package for an American Economic Journal: Applied Economics (AEJ: Applied) manuscript to pass the AEA Data and Code Availability Policy and the AEA Data Editor's pre-publication reproducibility check. Builds the openICPSR deposit and README; it does not run the analysis or write the paper.
Passed 20 of 22 test cases with the skill, and 14 of 22 without it.
and 5 more in the full report
7 fixed13 passed either way1 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am preparing our replication package for openICPSR after receiving a conditional acceptance at AEJ: Applied. Could you audit our repository and output a report with bracketed field tags evaluating master script capability, data file packaging or restricted extract status, README exhibit-to-code mapping, Data Availability Statement completeness, reproducibility parameters like seeds and paths, early exemption declaration timing, and the appropriate next step?
| Checked | Without skill | With skill |
|---|---|---|
| Evaluates whether a single master script executes the complete code pipeline. | Passed | Passed |
| Checks that deposited data files are uncompressed rather than provided as zip archives. | Missed | Passed |
The instructions your model reads when the skill loads.
The single most distinctive AEJ: Applied differentiator is the AEA Data and Code Availability Policy, administered by the AEA Data Editor (Lars Vilhuber). Papers offered a revise-and-resubmit are asked to submit a data replication package at resubmission, and accepted papers must clear the Data Editor's compliance and reproducibility checks before publication. The default home is the AEA Data and Code Repository on openICPSR; other trusted repositories require appropriate Data Editor access. Build this package as you analyze; do not treat it as an acceptance-day formality.
| Component | Requirement |
|---|---|
| Data files | All data used, unzipped, in open/documented formats; or, for restricted data, a precise access path |
| Analysis + transformation code | Every script from raw data → cleaned data → each table/figure |
| Master script | One run_all that regenerates every exhibit from raw inputs |
| README | AEA README template: data sources, access, computational requirements, run instructions, exhibit-to-code mapping |
| Data Availability Statement (DAS) | States provenance and access terms for each dataset; required in the paper |
| Instruments | Survey instruments / experiment instructions for own-data studies |
version + recorded ssc/net package versions; requirements.txt/conda env (Python); renv.lock (R).code/05_main.do, Figure 2 → code/06_event_study.R, etc.Adapt the vendored skeleton in
../../resources/code/(master script → clean → descriptive → DID/IV/RD/DML → mechanism → robustness → tables) as the package backbone.
test cases passed, vs 14 / 22 without
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