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Use when drafting or revising the prose of an AEJ: Economic Policy manuscript — especially the abstract and introduction — to translate causal estimates into a clear policy takeaway without overclaiming. Shapes the policy-first narrative and house style; it does not design identification or build the welfare model.
Passed 16 of 22 test cases with the skill, and 16 of 22 without it.
and 2 more in the full report
4 fixed12 passed either way2 still failing4 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
I have finished framing my empirical introduction, headline estimates, policy takeaways, and scope calibration for my manuscript on wage subsidies. What should I focus on next in my publication preparation? Provide your feedback in the standard bracketed output layout.
| Checked | Without skill | With skill |
|---|---|---|
| Recommends preparing the empirical replication package containing data processing and analysis scripts | Passed | Passed |
| Advises auditing code and data documentation to meet journal data editor requirements | Missed | Passed |
The instructions your model reads when the skill loads.
Late-stage polish: do not rewrite the intro until identification (
aejpol-identification), the welfare bridge (aejpol-theory-model), and robustness (aejpol-robustness) have settled.
Policy question → why credible identification is hard → the design that delivers it → headline causal estimate (with SE/CI) → welfare / cost-benefit / distributional reading → concrete, calibrated policy lesson → brief roadmap.
The distinctive moves vs. a general applied-micro intro:
aejpol-tables-figures); active voice; abstract that states question, design, headline estimate, and policy lesson. Online appendix carries the long material; the main text stays self-contained and readable. Review is single-blind, so the front matter names the authors — no need to anonymize the prose.test cases passed, vs 16 / 22 without
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