Claude Skills by brycewang-stanford

Use when positioning a Management Science (INFORMS) manuscript in its literature — joining the right Department's conversation, citing canonical analytical and empirical work in author-year style, and making the cross-department contribution legible so a Department Editor sees both fit and novelty. It positions; it does not state the contribution sentences (mgsci-contribution-framing).

Use when choosing and defending the method for a Management Science (INFORMS) manuscript — selecting an analytical modeling approach (optimization, stochastic, game/economic theory) or an empirical design (econometric identification, lab/field experiment, structural, data science) that matches the question and the Department's standards. It designs; it does not execute the analysis (mgsci-data-analysis).

Use when planning and drafting the revision and point-by-point response for a Management Science (INFORMS) R&R — prioritizing the Department Editor's binding concerns, addressing analytical-proof or empirical-identification objections, preserving double-anonymization, and keeping the revision within the page cap and Data-and-Code-Disclosure requirements. It handles the post-decision response; it does not run a fresh submission (mgsci-submission).

Use to understand how Management Science (INFORMS) review and decisions work — the Department/area-editor desk screen, the high desk-reject rate, double-anonymized refereeing, the cross-department fit bar, turnaround targets, and how to read a decision letter — before or after submitting. It explains the process; it does not draft the response (mgsci-rebuttal).

Use when running the final pre-submission preflight for a Management Science (INFORMS) manuscript — ScholarOne seven-step upload, double-anonymization, author-year house style, the $79 submission fee and waivers, the Data and Code Disclosure package and project-page URL, and conference-proceedings disclosure. It checks readiness to submit; it does not handle the post-decision response (mgsci-rebuttal).

Use when building exhibits for a Management Science (INFORMS) manuscript — propositions and numerical-illustration figures for analytical papers, or result/identification tables and effect plots for empirical papers — keeping notation clean, exhibits self-contained, and the page budget tight for the invited-revision limit. It builds exhibits; it does not run the analysis (mgsci-data-analysis).

Use when building the theoretical core of a Management Science (INFORMS) paper — either a formal analytical model (assumptions, equilibrium, propositions/theorems, comparative statics) or empirically testable hypotheses derived from a clear mechanism. Adapts to the paper's lane; it does not run the analysis (mgsci-data-analysis) or frame the contribution (mgsci-contribution-framing).

Use when shaping or stress-testing a research question for Management Science (INFORMS) — confirming the decision-relevance bar, choosing the right Department lane (analytical vs empirical), and testing fit against sister INFORMS journals (Operations Research, M&SOM, Marketing Science) so the paper is not desk-rejected as "better suited elsewhere".

Use when deciding which mgsci-* sub-skill to invoke next, or when sequencing manuscript work from topic selection through rebuttal for a Management Science (INFORMS) manuscript. Routes — it does not replace — the specialized skills, and helps pick the right Department lane (analytical vs empirical).

Use when polishing the prose of a Management Science (INFORMS) manuscript — front-loading the result, keeping notation lean, writing for a cross-department reader, and conforming to author-year citation house style and the journal's preference for short, focused papers. It polishes prose and style; it does not frame the contribution (mgsci-contribution-framing) or build exhibits (mgsci-tables-figures).

Use when turning analytical or empirical results into an explicit operations contribution for a Manufacturing & Service Operations Management (M&SOM) manuscript — stating the managerial implication, the new operational insight, and why an operations decision is central, including the four-part structured-abstract framing M&SOM requires.

Use when executing and reporting the analysis for a Manufacturing & Service Operations Management (M&SOM) manuscript — proving structural results and running numerical studies for analytical work, or estimating and stress-testing identified effects for empirical work, plus meeting M&SOM's data-and-code replicability policy. Executes the analysis designed in msom-methods.

Use when positioning a Manufacturing & Service Operations Management (M&SOM) manuscript within the operations-management literature — engaging the canonical OM streams (inventory, queueing, supply-chain contracting, revenue management, service operations, empirical OM), selecting the target editorial Department, and stating the operational conversation the paper joins.

Use when matching the method and identification to the operations problem for a Manufacturing & Service Operations Management (M&SOM) manuscript — selecting the analytical model class and solution approach, or the empirical identification strategy. Designs the study; msom-data-analysis executes and reports it.

Use after a Manufacturing & Service Operations Management (M&SOM) revise-and-resubmit — planning the revision around the Department Editor and Associate Editor priorities, then drafting a point-by-point response to referees while preserving operations centrality, the structured abstract, and the 32-page typeset cap. Drives the revision; revise the manuscript before drafting the letter.

Use to understand how Manufacturing & Service Operations Management (M&SOM) review and decisions work — the author-routed six-department structure, the Department Editor / Associate Editor / referee chain, double-anonymous review, special tracks (OM Forum, Practice Platform, OM Grand Challenges), and how to read a decision letter — before or after submitting.

Use when running the final pre-submission preflight for a Manufacturing & Service Operations Management (M&SOM) manuscript — the ScholarOne portal, double-anonymous anonymization, the 32-page typeset cap on the official template, the four-part structured abstract, author-chosen Department routing with two preferred Department Editors, and data/code disclosure. Checks readiness to submit; it does not handle the post-decision response (msom-rebuttal).

Use when building the exhibits for a Manufacturing & Service Operations Management (M&SOM) manuscript — numerical-study tables, policy and sensitivity plots for analytical work, regression and identification tables for empirical work — in INFORMS house style and inside the official template that enforces the 32-page cap.

Use when building the analytical model or operational mechanism at the core of a Manufacturing & Service Operations Management (M&SOM) manuscript — formulating the decision, objective, and uncertainty; deriving structural results; or specifying the operational mechanism behind an empirical hypothesis. Adapts theory work to M&SOM's dominant analytical/stochastic-modeling tradition.

Use when shaping or stress-testing a research question for Manufacturing & Service Operations Management (M&SOM) — confirming an operations decision is central, choosing the analytical-vs-empirical lane, and matching the question to the right editorial Department before any modeling or data work begins.

Use when deciding which msom-* sub-skill to invoke next, or when sequencing manuscript work from topic selection through rebuttal for a Manufacturing & Service Operations Management (M&SOM) manuscript. Routes — it does not replace — the specialized skills.

Use when polishing the prose of a Manufacturing & Service Operations Management (M&SOM) manuscript — front-loading the operational insight, controlling mathematical notation, writing the four-part structured abstract, and applying INFORMS author-year house style within the 32-page typeset cap. Late-stage polish; do not invoke before the model/identification is settled.

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).

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).

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).

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).

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).

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).

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).

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).

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).

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.

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.

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.

Use when articulating the contribution of a Mathematical Finance (Wiley) manuscript — frame the methodological novelty and its payoff for financial modelling (pricing, hedging, risk, portfolio, microstructure) so editor and referees see why the theorem matters, not just that it is true.

Use for the numerical-experiments part of a Mathematical Finance (Wiley) manuscript — adapted for a theory journal, this means illustrative computation that SUPPORTS a proof (convergence, error bounds, qualitative behavior), not empirical data analysis. Keeps numerics rigorous and subordinate to the theory.

Use when the mathematical core of a Mathematical Finance (Wiley) manuscript is the bottleneck — adapted for a theory journal, this means assumptions, theorem statements, proof architecture, and generality, not causal/empirical identification. Stress-tests rigor before exposition is polished.

Use when positioning a Mathematical Finance (Wiley) manuscript against the financial-mathematics frontier — stake the methodological contribution against prior stochastic-analysis, pricing, and control results, citing the precise theorem you sharpen, generalize, or supersede.

Use when responding to a Mathematical Finance revise-and-resubmit, especially comments about theorem novelty, proof gaps, assumptions, exposition, numerical support, or financial-modelling relevance.

Use when preparing Wiley data availability statements and reproducibility notes for a Mathematical Finance manuscript, especially when the paper has no empirical data but includes numerical experiments or illustrative code.

Use to understand the Mathematical Finance review process: single-blind editor screening, associate-editor handling, referee expectations for novelty and rigor, and how to interpret review-stage signals.

Use when running the final Mathematical Finance submission preflight through Wiley Research Exchange, including LaTeX source, compiled PDF, supplementary files, classifications, data availability statement, and single-blind review considerations.

Use when preparing figures, numerical tables, theorem maps, appendix exhibits, and algorithm displays for a Mathematical Finance manuscript, ensuring every exhibit supports a rigorous result rather than acting as stand-alone empirical evidence.

Use when choosing or sharpening a problem for Mathematical Finance (Wiley) — tests whether the question is a methodologically novel, rigorously tractable contribution to financial modelling (stochastic analysis, pricing, risk, portfolio, microstructure) rather than a routine computational application to data.

Router for a Mathematical Finance (Wiley) manuscript — decides which mathfin sub-skill to use next across the theorem-first lifecycle, from problem selection through Wiley Research Exchange submission and revision. Use this first to orient a financial-mathematics paper built on stochastic analysis and proofs.

Use when polishing a Mathematical Finance manuscript's theorem-first exposition: definitions, assumptions, theorem statements, proofs, appendices, numerical-experiment prose, and financial-modelling intuition.

Use when formatting references and applying the MIND house style to a Mind article. Mind provides a MIND Stylesheet and requires accepted papers to be prepared in its house style; line numbering is required for review. Handles citation mechanics and formatting; it does not write the argument.

Use when sharpening the concepts, distinctions, and method of a Mind article — defining key terms precisely, drawing distinctions, deploying thought experiments, and choosing the right philosophical method. Analytic philosophy lives or dies on conceptual precision and parsimony. Tightens the conceptual machinery; it does not settle the substantive question for you.

Use when positioning a Mind article against the existing philosophical literature so the thesis reads as a genuine move in a live debate. Mind readers are expert across analytic philosophy, so the paper must engage the canonical and current statements of the view it targets, not a strawman. Stakes the contribution; it does not write the literature section for you.

Use when stress-testing a Mind argument by raising the strongest objections and constructing replies. At a top analytic-philosophy journal, anticipating and answering the best objection is much of the contribution — referees are expert and will supply the objection if you do not. Builds the dialectic; it does not invent positions to knock down.