Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when deciding which aeri-* sub-skill to invoke next, or when sequencing work on a short-format manuscript from topic selection through the conditional-accept response for an American Economic Review: Insights (AER: Insights) submission. Routes — it does not replace — the specialized skills.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
This is the router. It tells you which aeri- skill to use at the current stage* of a manuscript aimed at American Economic Review: Insights (AER: Insights) — the AEA's short-format, general-interest journal (founded 2019) for papers built around ONE clear, important, well-executed idea, empirical, theoretical, or methodological. The bar is AER-level importance compressed into a short paper. AER: Insights is the short sibling of the American Economic Review (long, multi-result, flagship) and is general-interest, unlike the field-oriented full papers of the AEJ family.
Default assumption: unless the user says otherwise, treat the target as AER: Insights. The two operational tells that you are at AER: Insights and not AER or an AEJ: (1) a hard length cap — main text ≤7,000 words with no exhibits, minus 200 words per exhibit, maximum five exhibits, abstract ≤100 words — papers over the cap are returned unreviewed; (2) a single insight must carry the whole paper, with everything secondary pushed to the online Supplemental Appendix. Process tells: AEA single-blind review that is fast and decisive — no traditional revise-and-resubmit; first decisions are conditional accept or reject, and conditional accepts (usually an 8-week window) are normally not sent back to referees. Editor as of 2026: Matthew Gentzkow (lead editor beginning January 2024; founding editor Amy Finkelstein). Live-check volatile specifics on the official AEA pages.
| Current symptom | Next skill |
|---|---|
| Paper has several results / no single crisp insight; fit to short format unclear | aeri-topic-selection |
| Contribution vs. the closest published work is fuzzy or oversold | aeri-literature-positioning |
| The causal or parameter identification is shaky | aeri-identification |
| A model is present but bloated, or unclear what it must minimally show | aeri-theory-model |
| Robustness is sprawling; unclear what stays in-text vs. appendix | aeri-robustness |
| Over the five-exhibit budget; exhibits are dense or carry significance asterisks | aeri-tables-figures |
| Prose buries the result; abstract/intro do not lead with it; over word cap | aeri-writing-style |
| Data/code deposit, README, or AEA Data Editor prep | aeri-replication-package |
| Want to understand the fast review / conditional-accept-vs-reject odds | aeri-referee-strategy |
| Ready to submit via the AEA portal; need a preflight | aeri-submission |
| Received a conditional accept; need a short, decisive response | aeri-rebuttal |
aeri-topic-selection — confirm ONE crisp, important, well-identified insight that stands aloneaeri-literature-positioning — stake the contribution in one or two paragraphsaeri-identification — make the design or parameter identification clean and self-containedaeri-theory-model — keep only the model the single insight requiresaeri-robustness — the few in-text checks that matter; rest to the appendixaeri-tables-figures — at most five exhibits, no significance asterisksaeri-writing-style — lead with the result; enforce the word budget (abstract + intro last)aeri-replication-package — assemble the AEA-compliant data/code packageaeri-referee-strategy — calibrate expectations for the fast, decisive processaeri-submission — AEA portal preflight (word count + exhibit count)aeri-rebuttal — after the conditional accept
aeri-writing-styleis a late-stage polish, but the word cap is a constraint from day one — track it throughout, not at the end.
aeri-tables-figures polish a sixth exhibit that should not existaeri-replication-package until acceptance — the AEA Data Editor checks before publicationThe single insight differs by archetype; enter the chain at the right link.
| Archetype | Likely first bottleneck | Enter at |
|---|---|---|
| one clean causal estimate (DiD / RDD / IV / experiment) | is the design credible AND is it a single headline number? | aeri-topic-selection → aeri-identification |
| a sharp theoretical result / impossibility | is the model minimal and the result surprising? | aeri-theory-model |
| a methodological point with one application | does the method change a substantive answer in few pages? | aeri-identification → aeri-robustness |
| a striking new fact / measurement | is the fact important enough to stand alone, and robust? | aeri-topic-selection → aeri-robustness |
A user says: "My field experiment has a clean main effect, but I also estimated three heterogeneity splits and a structural extension, and the draft is 9,500 words." That is the canonical AER: Insights problem — one good insight buried under a multi-result, over-cap paper. Route first to aeri-topic-selection to confirm the single headline effect is the paper, then aeri-robustness and aeri-tables-figures to move the heterogeneity and the structural extension to the Supplemental Appendix, then aeri-writing-style to land the draft under the 7,000-word (minus exhibits) cap.
if decision_letter_arrived: -> aeri-rebuttal
elif ready_to_submit: -> aeri-submission
elif over_cap_or_too_many_exhibits: -> aeri-tables-figures / aeri-writing-style
elif robustness_sprawling: -> aeri-robustness
elif model_bloated: -> aeri-theory-model
elif identification_shaky: -> aeri-identification
elif contribution_fuzzy: -> aeri-literature-positioning
else: -> aeri-topic-selection
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Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.