Guides researchers through the full AEJ: Macro submission workflow—from topic selection and literature positioning to empirical identification, model discipline, robustness testing, and AEA-compliant replication packages. Includes rebuttal planning and pre-submission checks.
Use when the empirical identification of a macro shock or dynamic causal effect is the bottleneck for an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript — SVAR, local projections, narrative, high-frequency/proxy-VAR, or micro-data macro designs. Stress-tests the identification to the AEJ: Macro broad-interest quantitative bar; for model-parameter identification see aejmac-theory-model.
Use when the contribution of an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript relative to the macro frontier is fuzzy, contested, or undersold. Frames the marginal contribution against quantitative-theory and identified-empirical literatures; it does not fix the identification or the model itself.
Use when an American Economic Journal: Macroeconomics (AEJ: Macro) decision letter has arrived (R&R or reject-with-comments) and you need a response-letter strategy and revision plan. Plans the rebuttal and revision; it does not run new identification, model, or robustness work itself (route to those skills).
Use when anticipating the objections referees and coeditors will raise on an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript, and calibrating desk-reject and revision odds, before submission. Pre-empts pushback and plans the review; it does not draft the post-decision response letter (use aejmac-rebuttal).
Use when assembling the data, code, and documentation package for an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript to pass the AEA Data and Code Availability Policy and the AEA Data Editor's pre-publication reproducibility check. Covers macro specifics (simulation/calibration code, restricted-access data); it does not write the analysis itself.
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横跨经管社科 · 人文社科 · 自然科学 · 临床医学 · AI 计算机等多个主流学科,为每一本期刊 / 每一个会议单独编码它的投稿工作流。
🧭 布局指南 · 📚 Skill Pack 一览 · ⚡ 如何使用 · 🗺 路线图 · 🌐 English
先看期刊,再进 Pack。点击任意封面即可进入对应的期刊 Skill 包。
🆕 四个最新学科广度合集 —— 工程技术 40 · 农业环境 30 · 临床医学 30 · 英文人文 36;点击封面进入合集页。
其他合集 · 中文体育学 · 12 本 CSSCI 体育学来源刊
AI-first computer-science conference skill stack: 155 conference fit-and-submission profiles plus a CS/AI router. Covers top AI/ML, data mining, vision, NLP, robotics, HCI, systems, security, software engineering, programming languages, databases, and theory venues, with current-cycle CFP and author-kit re-check discipline.
Agent skill stack for submitting to 《经济研究》 (Economic Research Journal), the top economics journal in China. Eighteen skills across the manuscript lifecycle: China-context topic selection, introduction, bilingual literature review, theory & hypotheses, data & sample, modern causal identification (DID / IV / RDD / DML with heterogeneity-robust estimators), mechanism analysis (post-江艇 2022 paradigm), heterogeneity, robustness, three-line tables, policy implications, abstract, house style, reviewer-lens self-audit, reproducibility, submission preflight, and R&R rebuttals. Ships a runnable Stata + Python code library. Bilingual zh-CN / en docs.
Agent skill stack for articles and proposals targeted at the Journal of Economic Perspectives (JEP) — the open-access, non-technical synthesis journal of the American Economic Association, founded 1987, sister to the Journal of Economic Literature (technical surveys of record) and the AER/AEJ research journals. JEP is largely invited and organized in symposia, and rewards accessible writing readable by 90 percent of AEA members, not new identification or replication. Twelve role skills cover the JEP lifecycle: workflow routing, topic selection for a broad audience, the 2–5 page proposal and symposium pitch ([email protected]), narrative arc for a general economist reader, plain-language translation of technical results, presenting evidence with minimal equations, exhibits a non-specialist can read, the JEP voice, balance and objectivity over advocacy, working with the managing-editor-led editorial team, the pre-submission preflight, and revising for accessibility and balance. Bilingual en / zh-CN docs.
Agent skill stack for submitting to 《会计研究》 (Accounting Research) — the flagship journal of the Accounting Society of China and the only accounting title among CSSCI sources (monthly, founded 1980, ISSN 1003-2886, CN 11-1078/F). Built around the journal's defining bar: archival capital-market empirics with accurate institutional / standard-setting detail and an information mechanism, distinguished from generic corporate finance. Covers fit positioning, topic selection, literature review, institutional/standards background, accounting measurement (discretionary accruals, conservatism, disclosure indices), quasi-experimental identification, information mechanism, robustness, tables/figures, standard-setter/regulator implications, submission preflight, and R&R rebuttals.
Agent skill stack for manuscripts targeted at the Journal of Financial and Quantitative Analysis (JFQA) — empirical and quantitative financial economics (corporate finance, investments, capital and security markets, financial institutions, and finance-relevant quantitative methods), published by Cambridge University Press for the Michael G. Foster School of Business at the University of Washington. Built around the JFQA realities: submission via Editorial Manager with a text-searchable PDF, a $350 fee (only $275 refunded if not sent to a reviewer), double-anonymous review, a strict one-paragraph / 100-word abstract cap, prescriptive 8.5x11 / 1-inch / 12-pt Times New Roman double-spaced formatting, a one-year resubmission ban for undisclosed prior rejections, and the JFQA Code Sharing Policy with a dedicated JFQA Dataverse at the Harvard Dataverse. Covers topic fit, literature positioning, causal/identification design for finance, robustness, tables and figures, house style, the code/data archive, referee strategy, submission preflight, and R&R rebuttals. Bilingual en / zh-CN docs; Stata / R / Python conventions.
npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin aej-macroeconomics-skillsAgent skill stack for manuscripts targeted at the Journal of Monetary Economics (JME) — Elsevier's leading outlet for monetary economics and macroeconomics broadly defined (monetary theory and policy, central banking, business cycles, growth, financial intermediation, fiscal interactions, expectations). Submission is via Elsevier Editorial Manager (editorialmanager.com/monec/) with a US$350 fee (US$200 for full-time PhD students) charged up front, single anonymized (single-blind) review, a distinctive 'up or out' first-revision rule, a ~50% publication-likelihood threshold for an R&R, a strict 40-page / 10-tables-and-figures cap on accepted papers, a 100-word abstract that may not begin with 'This paper' or 'We', author-date references with journal titles spelled out, and a ScienceDirect/Mendeley Data supplementary-materials deposit policy. Includes the Carnegie-Rochester-NYU Conference Series on Public Policy annual issue. Covers DSGE/quantitative-macro and applied-policy topic selection, monetary-macro identification (high-frequency monetary surprises, narrative shocks, SVARs, local projections), literature positioning, contribution framing, tables/figures, JME house style, the data/replication policy, referee strategy, submission preflight, and 'up or out' rebuttals. Bilingual en / zh-CN docs; Stata / R / Python / Dynare conventions.
A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Comprehensive C4 architecture documentation workflow with bottom-up code analysis, component synthesis, container mapping, and context diagram generation