Claude Skills by brycewang-stanford

Use when executing and reporting the analysis for a Journal of Public Administration Research and Theory (JPART) manuscript so it survives expert, double-blind review and the journal's mandatory data-and-code release. Covers honest uncertainty, robustness, and the PA-specific traps (common-method bias, selection). Guides analysis norms; it does not fabricate results.

Use when positioning a Journal of Public Administration Research and Theory (JPART) manuscript against the public-administration literature so it reads as a theory contribution, not a fresh data point. JPART expects engagement with the specific PA conversation (PSM, red tape, representation, performance, governance) the paper advances. Stakes the contribution; it does not write the lit review.

Use when writing the response to a Journal of Public Administration Research and Theory (JPART) revise-and-resubmit. JPART reviews are detailed and developmental, so the response must convert each reviewer while keeping the theoretical contribution intact. Structures the response letter; it does not fabricate new results.

Use when defending the research design of a Journal of Public Administration Research and Theory (JPART) manuscript — survey/lab/field experiments on public employees and citizens, causal observational designs, multilevel structures, or mixed methods. JPART has moved strongly toward experimental and causal identification. Strengthens the design; it does not write code.

Use to understand how the Journal of Public Administration Research and Theory (JPART) evaluates a manuscript — double-blind review, desk screening on theory and fit, the reject / R&R / accept decision categories, and the PMRA/OUP editorial context. Sets expectations and shapes the paper to survive review; it does not contact editors.

Use when running the final pre-submission preflight for the Journal of Public Administration Research and Theory (JPART) via Editorial Express — word/format limits, double-blind anonymization, OUP author-date style, keywords, Data Availability Statement, and declarations. Final checks; it does not draft content.

Use when building tables and figures for a Journal of Public Administration Research and Theory (JPART) manuscript so exhibits are self-contained, accessible, and fit the 12,000-word budget that counts tables and references. JPART rewards exhibits that show mechanism and magnitude, not stars. Designs exhibits; it does not run the analysis.

Use when building the theoretical argument of a Journal of Public Administration Research and Theory (JPART) manuscript into a public-management contribution. JPART's defining demand is theory — its abstract template asks for the theoretical approach first and the implications for theory last. Structures the argument; it does not run analyses.

Use when deciding whether a public-administration project fits the Journal of Public Administration Research and Theory (JPART) rather than a sibling venue (PAR, JPAM, Governance). JPART rewards a contribution to public-management theory tested with rigor, not a stand-alone policy finding. Helps frame the question; it does not collect data.

Use when preparing the data and replication materials for a Journal of Public Administration Research and Theory (JPART) manuscript. JPART requires authors, where ethically possible, to publicly release all data and software code as a condition of publication, with a mandatory Data Availability Statement. Prepares the package; it does not waive requirements.

Use as the entry point for any Journal of Public Administration Research and Theory (JPART) manuscript. Routes to the right JPART sub-skill based on the lifecycle stage and forces the journal's defining test — a public-management theory contribution, not a bare empirical finding. It dispatches; it does not draft content.

Use when drafting or polishing a Journal of Public Administration Research and Theory (JPART) manuscript so it reads as theory-plus-rigor, follows OUP author-date style, and fits the ~12,000-word cap that includes the abstract, tables, and references. Tightens prose and format; it does not invent content.

Use when sharpening the policy contribution of a Journal of Public Policy & Marketing (JPP&M) manuscript — the 300-word Policy Contribution Statement, regulator-actionable implications, and the line between evidence and advocacy. Frames the contribution; it does not produce the estimates (jppm-data-analysis).

Use when estimating and stress-testing results for a Journal of Public Policy & Marketing (JPP&M) manuscript — treatment effects from experiments, DiD/RDD/synthetic-control policy evaluations, subgroup analyses for vulnerable populations, and policy-interpretable reporting. Runs the analysis; it does not choose the design (jppm-methods).

Use when situating a Journal of Public Policy & Marketing (JPP&M) manuscript against both the marketing-and-policy literature and the regulatory record, and defending the JPP&M lane against siblings. Positions the contribution; it does not build the framework (jppm-theory-development) or design studies (jppm-methods).

Use when choosing and designing the evidence for a Journal of Public Policy & Marketing (JPP&M) manuscript — experiments with policy-realistic stimuli, quasi-experimental policy evaluation (DiD, RDD, synthetic control), surveys, field data, or meta-analysis. Designs the studies; it does not estimate them (jppm-data-analysis).

Use when executing a Journal of Public Policy & Marketing (JPP&M) revise-and-resubmit — the response letter, converting reviewer demands into analyses or studies, and defending policy claims without slipping into advocacy. Drafts the rebuttal; letter-reading and feasibility calls are jppm-review-process.

Use when calibrating expectations for the Journal of Public Policy & Marketing (JPP&M) review cycle — desk-screen logic, the mixed reviewer pool, decision types, and what an R&R typically demands. Reads the process and the letter; drafting the response is jppm-rebuttal.

Use when running the final preflight for a Journal of Public Policy & Marketing (JPP&M) submission — the two-file split, double-anonymization, 50-page cap, Policy Contribution Statement, abstract/keywords, and the SageTrack portal. Final checks only; it does not draft content.

Use when building exhibits for a Journal of Public Policy & Marketing (JPP&M) manuscript — event-study and DiD displays, condition-contrast tables, subgroup forest plots, and stimuli exhibits that a policy reader can act on. Builds the exhibits; it does not produce the estimates (jppm-data-analysis).

Use when building the conceptual backbone of a Journal of Public Policy & Marketing (JPP&M) manuscript — theorizing why a policy lever changes marketplace behavior, for whom, and with what unintended effects. Builds the theory of the lever; it does not design the studies (jppm-methods).

Use when testing whether a research question is policy-first enough for the Journal of Public Policy & Marketing (JPP&M), and which of its domains and paper shapes it fits, before design and data are locked. Settles fit and outlet; it does not build the theory of the policy lever (jppm-theory-development).

Use when deciding which jppm-* sub-skill to invoke next, or when sequencing manuscript work from topic selection through rebuttal for a Journal of Public Policy & Marketing (JPP&M) submission. Routes to the specialized skills — it does not do their work.

Use when drafting or revising the prose of a Journal of Public Policy & Marketing (JPP&M) manuscript — the policy-problem-led introduction, the 200-word abstract, dual-audience clarity, and the evidence-not-advocacy voice. Polishes the writing; it does not change design, analysis, or framing decisions.

Use when identifying a risk or uncertainty parameter is the bottleneck for a Journal of Risk and Uncertainty (JRU) manuscript — incentive-compatible elicitation in an experiment, or structural/empirical estimation of risk preferences, VSL, or insurance demand. Stress-tests how the data pin the primitive; it does not invent evidence or citations.

Use when staking a Journal of Risk and Uncertainty (JRU) manuscript's contribution against the expected-utility-and-alternatives literature. Positions the claim within risk/uncertainty scholarship; it does not invent evidence or citations.

Use when a Journal of Risk and Uncertainty (JRU) decision letter has arrived and you need a response-letter strategy. Triages referee reports into a revision plan and reply; it does not invent evidence or citations.

Use when anticipating likely referee objections for a Journal of Risk and Uncertainty (JRU) manuscript before submission. Wargames the report a risk/uncertainty specialist would write; it does not invent evidence or citations.

Use when assembling the data, code, and experiment materials for a Journal of Risk and Uncertainty (JRU) manuscript and writing its Data Availability Statement. Builds a transparent, reproducible package; it does not invent evidence or citations.

Use when a Journal of Risk and Uncertainty (JRU) result may be sensitive to specification, incentive frame, sample, or inference. Organizes robustness by the threat to the risk/uncertainty parameter; it does not invent evidence or citations.

Use when running the final pre-submission preflight for the Journal of Risk and Uncertainty (JRU) via Springer's portal — file set, anonymization, Data Availability Statement, ethics and AI disclosures, and house-style checks. Final checks; it does not draft content.

Use when exhibits for a Journal of Risk and Uncertainty (JRU) manuscript must make choice patterns and risk-parameter estimates legible. Improves tables and figures for a risk/uncertainty audience; it does not invent evidence or citations.

Use when the decision-theoretic representation is the bottleneck for a Journal of Risk and Uncertainty (JRU) manuscript — axioms, functional form, and behavioral content for choice under risk or uncertainty. Strengthens the model; it does not invent evidence or citations.

Use when deciding whether a question belongs in the Journal of Risk and Uncertainty (JRU) and how to frame it as a risk/uncertainty primitive. Tests scope fit and sibling boundaries; it does not invent evidence or citations.

Use when deciding which jru-* sub-skill to invoke next, or when sequencing manuscript work from question through rebuttal for a Journal of Risk and Uncertainty (JRU) submission. Routes — it does not replace — the specialized skills.

Use when the prose of a Journal of Risk and Uncertainty (JRU) manuscript must convey a decision model and its measurement with precision. Sharpens abstract, intro, and exposition for a risk/uncertainty audience; it does not invent evidence or citations.

当你要判断《软件学报》(Journal of Software, JOS) 对代码与数据可用性（artifact）的现状与要求、并据此准备可评估材料时使用。覆盖本刊尚无强制 artifact 评审轨道的现实、如何把可复现材料做成加分项、专刊（special issue）与 CCF ChinaSoft 联动可能带来的材料要求、归档与许可选择、以及与国际会议 artifact badging 的差异，帮助你在《软件学报》(Journal of Software) 语境下做出恰当而不过度的 artifact 准备。

当你收到《软件学报》(Journal of Software, JOS) 的外审意见、需要撰写修回说明（答复审稿人）并修改稿件时使用。覆盖逐条回应的结构、"必须改/可讨论/礼貌不改"的分级策略、修回说明与稿件修改处的对应标注、补做实验的取舍、多轮修回之间的一致性维护、以及与责任编委和主编终审衔接的中文表达分寸，帮助你把《软件学报》(Journal of Software) 的"修改后再审"稳妥地做成录用，而不是在下一轮被退稿。

当你的稿件被《软件学报》(Journal of Software, JOS) 录用、需要完成定稿、校样与清样并交付出版时使用。覆盖录用后按 2021 版模板的最终排版、中英文摘要与关键词的终校、参考文献 GB/T 7714 复核、图表清晰度与版权、作者与基金信息核对、校样阶段的勘误纪律、以及版面费与版权协议等事务，帮助你把《软件学报》(Journal of Software) 的录用稿干净地送进出版流程。

当你要为投向《软件学报》(Journal of Software, JOS) 的稿件设计或打磨实验与评测时使用。覆盖研究问题 (RQ) 契约、真实系统与数据集的选取、可信基线、评价指标与统计显著性/效应量、消融与抗污染的大模型评测、挖掘类研究的出处锁定、以及威胁有效性 (threats to validity) 的分类论证，帮助你把证据与论点对齐，达到《软件学报》(Journal of Software) 软件学科同行评审对实证严谨性的要求。

当你要为投向《软件学报》(Journal of Software, JOS) 的稿件撰写相关工作或文献综述、并需要把自己的增量讲清楚时使用。覆盖软件学科文献分线（软件工程/系统软件/程序设计语言/数据库/网络与分布式/安全）、以"差异优先"方式定位增量、中英文文献的均衡引用、避免遗漏本刊近期相关论文、以及综述类文章的分类框架构建，帮助你在《软件学报》(Journal of Software) 审稿人面前把"与已有工作的区别"论证到位。

当你要为投向《软件学报》(Journal of Software, JOS) 的软件学科稿件建立可复现性与实验可重复保障时使用。覆盖数据/代码可用性声明、环境与依赖固定、随机性与种子控制、挖掘与大模型实验的出处锁定与输出缓存、可复现材料的目录组织与 README，以及"可根据要求提供"这类弱表述的规避，帮助你让《软件学报》(Journal of Software) 审稿人相信你的实验结果可被他人重复得到。

当你要理解《软件学报》(Journal of Software, JOS) 的审稿流程、稿件状态含义与作者可施力点时使用。覆盖在线投稿系统的状态链（投稿→领域/责任编委初审→外审→复审→主编终审→修回→定稿→录用）、多轮修回机制、6 个月内通知结果的时序、专刊评审差异、以及每个阶段作者能做什么，帮助你在《软件学报》(Journal of Software) 的中文同行评审各环节把握节奏与预期，不误判稿件状态。

当你要把一篇稿件投向《软件学报》(Journal of Software, JOS) 并需要在提交前做一次完整的在线投稿审计时使用。覆盖 jos.org.cn 在线投稿系统的账号与流程、2021 版排版模板与 GB/T 7714 参考文献、中英文题目/摘要/关键词/中图分类号、软件学科栏目定位（研究论文/综述/专刊）、一稿多投与学术规范承诺、基金与通信作者信息、以及退稿风险的自查，帮助你在提交前把《软件学报》(Journal of Software) 会立刻检查的项目逐条清干净。

当你要为投向《软件学报》(Journal of Software, JOS) 的稿件组织附录、补充材料与多媒体附件时使用。覆盖正文与附录的内容切分原则（决定录用的内容不得移出正文）、补充材料的类型与格式、多媒体/在线附件的引用方式、与可复现材料的关系、以及附录在评审与出版两阶段的不同处理，帮助你把《软件学报》(Journal of Software) 稿件的核心留在正文、把支撑细节稳妥地放进补充材料。

当你要判断一个研究项目是否契合《软件学报》(Journal of Software, JOS)、还是更适合投向《计算机学报》《计算机研究与发展》《自动化学报》《电子学报》《计算机科学》或英文会议/期刊时使用。本技能给出软件学科定位判据、与兄弟刊的区分测试、栏目（研究论文/综述/专刊）选择、以及"模型可替换"与"改标题"两个改投信号，帮助你在动笔前把选题对准《软件学报》(Journal of Software) 的软件工程与系统软件侧重，并决定是否走 CCF ChinaSoft 联动的专刊通道。

当你要把投向《软件学报》(Journal of Software, JOS) 的全过程从选题到见刊统筹起来时使用。覆盖从选题定位、中文写作与实验、在线投稿、初审→外审→复审→主编终审的多轮修回、录用后定稿清样直到见刊的完整时间线，说明每一步该调用本包哪个技能、如何倒排计划、如何规避专刊截稿与超期等时序陷阱，帮助你把《软件学报》(Journal of Software) 一次投稿的完整生命周期统筹到位，不遗漏关键环节。

当你要按《软件学报》(Journal of Software, JOS) 的中文科技写作规范撰写或打磨稿件时使用。覆盖中英文题目、结构化中文摘要与 English Abstract、关键词、中图分类号、引言首页弧线（问题→不足→贡献→证据→意义）、术语一致性、图表与公式规范、以及参考文献 GB/T 7714 著录细则，帮助你把稿件写成《软件学报》(Journal of Software) 审稿人一眼认可的软件学科中文论文，而不是英文论文的生硬直译。

Use when designing, reporting, or auditing an exact, decomposition, heuristic, simulation, or learning-based solution route for 《系统工程学报》 (Journal of Systems Engineering, Tianjin University), including pseudocode, convergence or complexity, baselines, ablations, parameter settings, computing environment, scalability, and reproducible computational evidence.

Use when an author is deciding whether a systems, management-science, operations-research, engineering, control, or empirical manuscript genuinely fits 《系统工程学报》 (Journal of Systems Engineering, Tianjin University), or when a concrete rerouting decision is needed among Systems Engineering Theory and Practice, Journal of Management Sciences in China, Chinese Journal of Management Science, Systems Engineering and Electronics, Control and Decision, and Operations Research and Management Science.