Agent Skills
› brycewang-stanford/Awesome-Journal-Skills
› mksc-submission
mksc-submission
GitHub用于准备向Marketing Science期刊提交稿件。涵盖ScholarOne系统双盲处理、选择投稿轨道（常规/前沿/数据库/实践）、整理复制包、撰写封面信及可选开放获取选项，确保符合格式与审查要求。
Trigger Scenarios
稿件完成准备通过ScholarOne提交
不确定适合哪种投稿轨道或所需文件
需要对稿件进行双盲处理并组装复制材料
考虑是否选择开放获取（Open Option）
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mksc-submission -g -y
SKILL.md
Frontmatter
{
"name": "mksc-submission",
"description": "Use when preparing to submit a Marketing Science manuscript through ScholarOne — blinding for double-anonymous review, choosing the track (regular \/ Frontiers \/ Database \/ Practice), assembling the replication package, the cover letter, preferred AEs\/reviewers, and the optional Open Option. Preflight only; it does not interpret decisions (mksc-review-process)."
}
Submission Preflight (mksc-submission)
When to trigger
- The manuscript is finished and you are ready to submit
- You are unsure which track fits or what files ScholarOne expects
- You need to blind the manuscript and assemble the replication materials
- You are weighing the Open Option (gold OA)
Submission system and blinding
- Submit through ScholarOne Manuscripts at mc.manuscriptcentral.com/mksc.
- Regular submissions use double-anonymous review: remove author names, institutions, and acknowledgments from the manuscript; phrase self-citations in the third person.
- The cover letter is visible to the Editor and AE but not reviewers — use it for context, prior-review history, and self-overlap disclosure, while keeping the manuscript itself blinded.
Choose the right track
- Regular (Original Article) — no fixed length cap, but write succinctly.
- Frontiers in Marketing Science — Science-like, faster review, strict 6,000-word total cap (including references, tables, graphs, appendices); requires a major contribution on one primary dimension.
- Database — built around a novel dataset.
- Practice Paper / Practice Prize — requires a 500–1,000-word Impact Statement and uses a single-blind process; Science-to-Practice is a related track.
Format and front matter
- Double-spaced, single column, 11- or 12-point font, one-inch margins; Word or LaTeX (INFORMS style files), uploaded as Word or PDF.
- Abstract ≤ 200 words on the first page; 3–6 keywords (theoretical and methodological orientation).
- INFORMS author-year citations; alphabetical reference list.
- You may suggest 2 preferred Associate Editors and 3 preferred reviewers.
- Disclose any self-overlap with your published or under-review work and how this paper goes beyond it.
Replication package
Although the deposit is required on acceptance (Replication and Disclosure Policy), assemble it now: estimation code and a master script that reproduces every table/figure/counterfactual; for licensed data (NielsenIQ, Compustat, CRSP, Census), access instructions and linking/build code rather than raw data.
Fees / Open Option
No mandatory submission or publication fee for standard subscription publication. Open Option (gold OA) is optional: a one-time US$3,000 fee charged only after acceptance, before publication; it does not affect peer review.
Checklist
- Manuscript blinded (names, affiliations, acknowledgments, self-citations)
- Track chosen; Frontiers within 6,000-word total cap; Practice has Impact Statement
- Abstract ≤ 200 words; 3–6 keywords; INFORMS author-year + alphabetical refs
- Format: double-spaced 11–12 pt, one-inch margins; Word/LaTeX → Word/PDF
- Cover letter (Editor/AE-only) with self-overlap disclosure
- 2 preferred AEs and 3 preferred reviewers suggested
- Replication package assembled (code + licensed-data access/build)
- Open Option decision noted (US$3,000, post-acceptance, optional)
Anti-patterns
- Leaving author identifiers or "our prior paper" phrasing in a double-anonymous manuscript.
- Submitting an over-length Frontiers paper.
- Treating replication as an afterthought; "code on request."
- Confusing the single-blind Practice track rules with regular double-anonymous submission.
Replication package layout (assemble before you submit)
The deposit is required on acceptance, but reviewers increasingly probe reproducibility during review. Build the package now so the master script already reproduces every exhibit:
mksc-replication/
├── README.md # data provenance, software + versions, run order, expected runtime
├── run_all.{R,py,do} # master script: raw → estimates → every table/figure/counterfactual
├── data/
│ ├── build/ # linking + cleaning code (NOT licensed raw data)
│ └── access.md # how to obtain NielsenIQ / Compustat / CRSP / Census + license notes
├── estimation/ # model estimation code, starting values, solver settings
├── counterfactuals/ # policy simulations that re-solve firm optimization
└── output/
├── tables/ # table_1.tex ... mapped 1:1 to the manuscript
└── figures/ # fig_1.pdf ... regenerated by run_all
Map each output file to its manuscript exhibit by name; a reviewer or the AE should reproduce Table 3 without emailing you. For licensed data, ship build/linking code and access instructions, never the raw proprietary extract.
Output format
【Track】regular / Frontiers / Database / Practice
【Blinding】manuscript anonymized? self-cites third-person?
【Front matter】abstract ≤200w; 3–6 keywords; INFORMS format
【Handlers】2 preferred AEs + 3 reviewers; cover letter (Editor/AE-only)
【Replication】code + data access/build ready
【Fees】subscription (none) / Open Option US$3,000
【Next step】mksc-review-process
Version History
- 1839142 Current 2026-07-05 14:04
