Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Use when targeting Earth System Science Data (ESSD) or deciding whether an earth-system dataset fits this venue. Encodes the journal's data-paper fit, the open-deposition-with-DOI requirement, quality and reuse-documentation bar, Copernicus house style, official-submission re-check, and desk-reject heuristics.
Use when targeting Earth's Future (Earth's Future) or deciding whether an Anthropocene, Earth-system-futures, or sustainability manuscript fits this AGU open-access venue. Encodes the journal's fit, framing, method-and-evidence bar, house style, official-submission re-check, and desk-reject heuristics.
Use when planning the reproducibility/artifact story for an ECAI paper — noting that ECAI/FAIA has NO ACM/IEEE-style artifact-badging committee, so credibility is carried by the paper and its supplement and judged by the same reviewers, and adapting an ML-style reproducibility package (or a complete proof appendix for theory work) to that reality.
Use when reasoning about how an ECAI submission is evaluated — double-blind review, the summary-reject first phase, area chairs / senior PC, the single author-response (rebuttal) window, an accept/reject decision (no journal-style major-revision round), and how ECAI's process and its joint IJCAI-ECAI 2026 form differ from AAAI, IJCAI standalone, and AAMAS.
Use when hardening the reproducibility story of an ECCV paper — training recipes and schedules readers can re-run, dataset versioning and split provenance, pinned foundation-model dependencies, compute disclosure, and seed/variance honesty for benchmark deltas, sized for the 14-page LNCS body plus supplement.
Use when deciding whether a computer-vision project should target ECCV — weighing the two-year even-year cadence against CVPR, ICCV, WACV, BMVC, ACCV, NeurIPS, and journal routes, testing whether the work matches ECCV's breadth from geometry to vision-language, and reading the Koenderink Prize lineage as a durability signal.
Use when the empirical identification strategy is the bottleneck for a The Economic Journal (EJ) manuscript — quasi-experimental designs (DID, IV, RDD, event study) or structural estimation. Stress-tests the design and its economic interpretation before drafting tables; it does not write the model from scratch (see ecj-theory-model).
Use when the main result of a The Economic Journal (EJ) manuscript rests on a single specification and you need to pre-empt the alternative-explanation and fragility objections a demanding referee will raise. Builds the robustness battery and the falsification logic; it does not establish the primary identification (see ecj-identification).
Use when scoping or framing a research question for a The Economic Journal (EJ) manuscript and you need to test whether it is "EJ-shaped" — a substantial contribution of broad interest to economists at large, full-length or short-paper. Diagnoses fit and frames the contribution; it does not design the empirics.
Use when the identification argument is the bottleneck for an Economic Policy (EP) manuscript — causal identification of a policy effect, or parameter identification in a quantitative policy model. Stress-tests it to the EP bar (credible to an academic discussant, legible to a policy discussant) before exhibits are finalized.