Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Use when targeting JAMA Surgery or deciding whether a surgical-outcomes or surgical-trial study fits this venue. Encodes the journal's fit, the surgical-trial and perioperative evidence bar, surgical-reporting challenges, reporting-guideline and trial-registration requirements, JAMA Network house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.
Use when running and reporting the analysis for a Journal of the Academy of Marketing Science (JAMS) manuscript — selecting the estimator that matches the design (SEM/PLS, HLM, regression/econometrics, experiments, meta-analysis), reporting effect sizes and uncertainty, and translating estimates into managerial magnitudes. Executes and reports; jams-methods designs the study and jams-contribution-framing states the payoff.
Use when matching the research design to the claim for a Journal of the Academy of Marketing Science (JAMS) manuscript — construct validity and measurement, survey/SEM design, secondary-data identification, experiments, or meta-analysis. Designs the study and stress-tests validity; jams-data-analysis executes and reports the estimates.
Use when understanding how Journal of the Academy of Marketing Science (JAMS) review and decisions work — the Springer Editorial Manager flow, the double-anonymized developmental review, the area-editor structure, the dual theory-and-managerial evaluation bar, and how to read a decision letter. Explains the process and reads the letter; it does not draft the response (jams-rebuttal).
Use when running estimation and inference for a Journal of Applied Econometrics (JAE) manuscript so the analysis is reproducible and archive-ready — every table/figure regeneratable from plain-text data and programs you will deposit in the JAE Data Archive. Covers robust inference, master-script discipline, Monte Carlo evidence, and the archive's plain-ASCII/CSV format rule.
Use when designing or defending the empirical identification of a Journal of Applied Econometrics (JAE) manuscript — a credible strategy applied to real data, with assumptions stated, tested, and reproducible. Covers time-series, panel, IV, and quasi-experimental designs typical of applied econometrics, tying every claim to depositable evidence.
Use when running and reporting the empirical-archival analysis for a Journal of Accounting Research (JAR) manuscript — standard-error clustering, endogeneity execution, construct measurement, and the robustness battery referees expect, plus the reproducible data-and-code package JAR requires. Executes and reports; it does not choose the identification strategy (jar-methods) or frame the contribution (jar-contribution-framing).
Use when the research design and identification strategy are the bottleneck for a Journal of Accounting Research (JAR) manuscript — choosing the setting, source of identifying variation, and sample to support a causal accounting claim. Designs the study; it does not run the estimation, clustering, or robustness (jar-data-analysis).
Use when setting expectations for how Journal of Accounting Research (JAR) review and decisions work, or when reading a JAR decision letter — the Senior-Editor-panel structure, double-anonymized review, the desk-screen and tiered-fee gate, and the distinctive Ray Ball Conference and Registered Reports tracks. Explains the process; it does not draft the R&R response (jar-rebuttal).
Use when building the economic mechanism and deriving signed, falsifiable predictions for a Journal of Accounting Research (JAR) manuscript — grounding hypotheses in information economics, contracting, and disclosure theory rather than psychology-style construct chains. Builds the mechanism; it does not design the empirical test (jar-methods) or run it (jar-data-analysis).