Marketing Science Skills

Agent skill stack for manuscripts targeted at Marketing Science, the flagship quantitative-marketing journal of the INFORMS Society for Marketing Science (ISMS), published by INFORMS. Built around the journal's modeling core: structural econometric models, analytical (game-theoretic) models, econometric/statistical estimation, and machine-learning tools applied rigorously to marketing problems (pr

by @brycewang-stanford 12 skills

Install

npx skillmds@latest add plugin:brycewang-stanford/marketing-science-skills

One command, no setup. In Claude Code it lands as a managed plugin you can enable, disable or remove with /plugin. On any other agent it installs the 12 skills into that agent's own folder.

Or inside Claude Code

In the Plugins tab, add this marketplace:

skillmds/skillmd
/plugin install brycewang-stanford-marketing-science-skills@skillmd

Adds the marketplace once; later plugins need the second line only.

Or install by hand

Download the plugin and unzip its skills/ folder into your agent's skills directory. Works with every agent, no CLI needed.

Download plugin Paths per agent

Just the markdown? SKILL.md files only.

This plugin

skills: 12
authors: 1

Published by a registry member. Review its skills before installing.

Skills in this plugin

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Mksc Methods · brycewang-stanford
Use when the empirical/analytical approach is the bottleneck for a Marketing Science manuscript — choosing among structural econometrics, analytical modeling, and model-disciplined causal/ML methods, and making the model estimable and identified. Designs the approach; it does not execute the estimation and counterfactuals (mksc-data-analysis).

1k repo stars
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Mksc Rebuttal · brycewang-stanford
Use when drafting the revision and response letter after a Marketing Science revise-and-resubmit — structuring point-by-point responses to the Senior/Associate Editor and reviewers across a multi-round process, especially on assumptions, identification, counterfactuals, computation, and replication. Drafts the response after revising; it does not interpret the decision (mksc-review-process).

1k repo stars
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Mksc Workflow · brycewang-stanford
Use when deciding which mksc-* sub-skill to invoke next, or when sequencing a Marketing Science manuscript from modeling-driven topic selection through R&R rebuttal. Routes — it does not replace — the specialized skills.

1k repo stars
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Mksc Submission · brycewang-stanford
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).

1k repo stars
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Mksc Data Analysis · brycewang-stanford
Use when estimating and validating the model for a Marketing Science manuscript — running structural estimation (GMM/MLE/SMM/Bayes), checking identification empirically, assessing model fit, computing counterfactuals, and preparing the replication package. Executes the analysis; it does not design the model (mksc-theory-development) or choose the genre (mksc-methods).

1k repo stars
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Mksc Writing Style · brycewang-stanford
Use when polishing the prose of a Marketing Science manuscript — front-loading model intuition before notation, managing the formal apparatus for readability, and following INFORMS author-year style and formatting. Late-stage polish; do not invoke while the model or identification is still unsettled.

1k repo stars
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Mksc Review Process · brycewang-stanford
Use when understanding how Marketing Science evaluates a manuscript — the double-anonymous Senior-Editor / Associate-Editor routing, what the first-pass and review look for, and how to read a decision letter. Explains the process; it does not draft the revision response (mksc-rebuttal).

1k repo stars
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Mksc Tables Figures · brycewang-stanford
Use when building the exhibits for a Marketing Science manuscript — estimate tables, model-fit tables, comparative-statics figures, and counterfactual/policy-simulation exhibits in INFORMS house style. Designs the exhibits; it does not run the estimation (mksc-data-analysis) or write the prose (mksc-writing-style).

1k repo stars
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Mksc Topic Selection · brycewang-stanford
Use when choosing or sharpening the research question for a Marketing Science manuscript — testing whether a marketing problem is important AND admits a formal model (structural or analytical), and whether Marketing Science (not JCR/JMR/Management Science) is the right venue.

1k repo stars
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Mksc Theory Development · brycewang-stanford
Use when building the formal model for a Marketing Science manuscript — turning a marketing phenomenon into an analytical (game-theoretic) model or a structural econometric model with a clear identification argument. Develops the model and mechanism; it does not run the estimation (mksc-data-analysis) or pick the empirical genre at a high level (mksc-methods).

1k repo stars
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Mksc Contribution Framing · brycewang-stanford
Use when stating the headline contribution of a Marketing Science manuscript — naming the primary dimension (substantive marketing insight, modeling, methodology, data, or practice) and writing the contribution and managerial-implication paragraphs. Frames the contribution; it does not build the model (mksc-theory-development) or run the analysis (mksc-data-analysis).

1k repo stars
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Mksc Literature Positioning · brycewang-stanford
Use when positioning a Marketing Science manuscript in its literature — locating the contribution among structural and analytical modeling precedents and the relevant substantive stream (pricing, advertising/digital, channels/retail, branding, platforms, analytics), and disclosing self-overlap. Positions the paper; it does not state the headline contribution (mksc-contribution-framing).

1k repo stars