Claude Skills by brycewang-stanford

Use when a POPL paper is conditionally accepted — planning the mandatory revision the Review Committee must approve, de-anonymizing for PACMPL Issue POPL, handling ORCID/open-access/APC steps on the ACM side, syncing the paper with its proof artifact, and preparing the January talk.

Use when designing the empirical component of a POPL paper — deciding whether evidence should be a mechanization, a prototype, case studies, or benchmarks; reporting proof effort and case-study coverage honestly; and keeping performance numbers in a supporting role so the formal claim stays the paper's center of gravity.

Use when positioning a POPL paper in the semantics, type-systems, and verification literature — stating per-line technical deltas against the nearest formal systems, covering the PACMPL family and LICS/CAV/CPP/TOPLAS neighbors, citing PACMPL-era papers in journal form, and dblp-verifying every classic before it is attributed to POPL.

Use when making a POPL paper's results independently checkable — deciding which theorems to mechanize versus hand-prove, maintaining a paper-to-proof correspondence table from day one, keeping on-paper proofs auditable with explicit assumption tracking, and making any accompanying prototype's numbers regenerable.

Use when interpreting where a POPL submission stands — the full double-blind pipeline from the July HotCRP deadline through reviews, the optional author response, October conditional-acceptance decisions, the mandatory revision gate, Distinguished Paper selection, and publication as PACMPL Issue POPL in January.

Use when preparing a POPL submission for the single July HotCRP deadline — auditing the 25-pages-of-text acmsmall cap, summary-rejection format rules, full double-blind hygiene for theory papers with public proof repositories, dual-submission exposure, and the final-days upload order before the AoE cutoff.

Use when splitting a POPL paper across the 25-page body, the proof appendix, and anonymous supplementary material — deciding which proofs and auxiliary judgments leave the text, packaging proof scripts without identity leaks under full double-blind, and keeping every artifact self-consistent with the submission PDF.

Use when deciding whether a project is POPL-shaped — a principle about programming languages carried by definitions and theorems — or better aimed at PLDI's implementation bar, OOPSLA's breadth, ICFP's paradigm focus, or LICS, CAV, CPP, ESOP, and journal outlets, judged by what the decisive evidence is.

Use when planning a POPL campaign calendar — backward-scheduling theory and mechanization from the July deadline, riding the October notification into the conditional-acceptance revision and artifact evaluation, landing the January conference, and retargeting across the SIGPLAN/PACMPL deadline wheel if July slips.

Use when drafting or revising POPL prose — building the informal-to-formal ramp from a motivating program to definitions to a sharply stated main theorem, keeping notation coherent across 25 pages of text, writing proof sketches that name the hard case, and framing significance as an idea other PL researchers can reuse.

Use when packaging a PPoPP artifact for the post-acceptance, CGO-shared artifact-evaluation track, covering PPoPP's specific badge policy (Functional or Reusable plus Results Reproduced, no "Results Replicated"; Available granted by the publisher from a deposit link), reproducible parallel measurements on evaluators' hardware, and the separate AE deadline.

Use when writing a PPoPP author-response rebuttal, covering the short fixed word-capped window, answering the recurring "does it scale?" and "what about baseline X?" questions with pre-run numbers, correcting factual misreadings of a concurrency argument, staying double-blind, and prioritizing the points that can actually move a decision.

Use when preparing a PPoPP camera-ready, covering systematic de-anonymization, ACM rights/eRights and CCS concepts metadata, restoring the named hardware and acknowledgements, permanentizing the artifact DOI and any earned badges, and passing ACM production checks for the two-column acmart sigplan proceedings.

Use when designing or auditing a PPoPP paper's evaluation, covering the twin bar of concurrency correctness and measured scalability — speedup curves, strong vs weak scaling, core/thread sweeps, NUMA and GPU effects, contention microbenchmarks plus real workloads, variance and measurement hygiene, and honest strong baselines.

Use when writing or auditing a PPoPP paper's related-work and positioning, covering the parallel-programming literature lanes (concurrent data structures, runtimes/schedulers, GPU/accelerators, memory models, parallel algorithms), delta-first comparison against the nearest competitor, double-blind self-citation, and separating PPoPP work from CGO/PLDI/POPL/SC neighbors.

Use when making a PPoPP paper's parallel-performance results reproducible, covering the hardware and topology description reviewers re-run, thread pinning and NUMA control, seeds and warm-up, compiler/driver/flag provenance, and building an environment that reproduces the paper's scaling trend on different machines.

Use when reasoning about how a PPoPP submission is evaluated, covering double-blind review, the Program Committee plus External/Extended Review Committee model, TPMS reviewer matching, the author-response rebuttal, the accept/reject decision with automatic poster consideration, and how PPoPP's process differs from PLDI's and CGO's.

Use when auditing a PPoPP research-paper submission for HotCRP readiness, covering the two-column acmart sigplan template, the 10-page text+figures budget with unlimited references, the 100-400 word abstract, double-blind anonymity for parallel-systems work, conflict declaration against the PC and External Review Committee, and desk-reject triage before the AoE cutoff.

Use when deciding what belongs in a PPoPP paper's 10 reviewed pages versus the artifact or appendix, splitting content by decision-criticality so proofs, full core sweeps, and correctness arguments that determine acceptance stay legible in the body, while bulk data and extended runs move out.

Use when deciding whether a parallel/concurrent-computing project belongs at PPoPP or should be routed to PLDI, CGO, POPL, ASPLOS, HPCA, SC, SPAA, or OOPSLA, and when distinguishing PPoPP's "the parallelism is the point" scope from a compiler contribution (CGO/PLDI), a concurrency logic (POPL), or a microarchitecture result (ASPLOS/HPCA).

Use when planning a PPoPP submission campaign end to end, sequencing the summer paper deadline, the author-response rebuttal window, notification, the post-acceptance CGO-shared artifact-evaluation round, the camera-ready, and the presentation inside the co-located HPCA/CGO/PPoPP/CC week.

Use when drafting or tightening a PPoPP paper's prose and structure, covering the two-column acmart sigplan layout, the 10-page text+figures budget, stating the concurrency-correctness and scalability claim up front, presenting speedup curves and core sweeps, and the parallel-programming conventions PPoPP reviewers expect.

在为《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 处理代码与数据可用性、撰写可用性声明时调用。本刊作为中文期刊是否设立独立的制品评审徽章(artifact badge)制度目前待核实——本技能讲清现状与稳妥做法：如何写诚实的代码/数据可用性声明、如何组织可供外审核验的复现仓库、如何在不可公开时说明原因与替代验证途径、如何与审稿匿名要求(是否双盲待核实)协调。用于让模式识别/机器学习论文的制品支撑而非拖累评审，避免可用性声明与实际提供的材料不一致。

在为《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 撰写审稿意见答复(rebuttal)与修回说明时调用。覆盖如何逐条回应外审与编辑意见、如何组织答复信结构、如何在修订稿中标注并定位修改、如何礼貌而有据地处理不同意的意见、如何应对"较大修改重新送审"、以及补做实验/改写后的证据呈现。用于把一轮大修/小修转化为经得起复审的答复信与修订稿，提升再审通过率；本刊多轮修回为常态，答复质量直接影响录用。

在《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 稿件被录用后做定稿、校样(清样)核对与出版准备时调用。覆盖录用后按主编终审与编辑意见定稿、恢复作者信息与致谢/基金显名、校样阶段的图表公式参考文献终检、GB/T 7714 与中图分类号复核、版面费/审理费缴纳(金额待核实)、著作权授权、出版排期与月刊见刊节奏，以及录用后不得实质改动内容的纪律。用于把一篇已录用的模式识别/人工智能长文平稳送到见刊，避免校样阶段引入新错误或流程延误。

在为《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 设计与呈现模式识别/机器学习实验证据时调用。覆盖研究问题(RQ)拆解、公平基线与相同划分/算力、评测指标选择(准确率/F1/mAP/IoU/AUC 等)、多次运行的均值±标准差与统计显著性检验、消融实验、复杂度与开销报告、数据泄漏与评测污染的防范，以及把每条主张绑定到证据的呈现方式。用于把 AI 细分方向的实证部分做到经得起外审对"基线是否公平、结果是否可信、消融是否充分"的质询。

在为《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 撰写相关工作/文献综述并确立创新性时调用。本刊要求成果具原创创新价值，相关工作须 delta 优先——把本文相对最接近工作的增量讲清，而非文献罗列。覆盖如何组织相关工作、如何在模式识别/机器学习/视觉/NLP 语境中定位 delta、如何用 GB/T 7714 规范引用中英文文献并给中文文献英文对照、如何避免"综述式罗列"与"漏引近作"两类退稿风险。用于把创新性写到经得起外审质疑的水准。

在为《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 准备可复现性与实验可重复材料时调用。覆盖固定随机种子、锁定软硬件环境与依赖版本、固定数据集划分与预处理、预训练权重与大模型版本的记录、复现包(脚本/配置/环境文件)的组织、大数据与权重的稳定托管、以及可复现自查冒烟测试。用于让本刊模式识别/机器学习论文的实验结果能被外审与后续读者重复，降低"结果无法复现"的信任风险；本刊是否设强制复现要求以官网当期须知为准(待核实)。

在需要理解《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 的同行评审流程并识别各环节作者杠杆时调用。覆盖编辑初审(宗旨/体例/字数/查重)→专家外审(官方口径一般6个月内给评审结果)→修回(可能多轮，较大修改重新送审)→主编终审→录用的完整链路、各环节的退稿/退修理由、超过6个月作者可通知编辑部自行处理的官方口径、以及作者在每个环节能施加影响的着力点。用于把审稿流程建模为可预期的阶段并规划应对；审稿是否双盲等细节以官网当期须知为准(待核实)。

在向《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 正式提交稿件前做投稿就绪审计时调用。覆盖官方投稿系统 manu46.magtech.com.cn/Jweb_prai 的"作者中心"在线投稿、上传前病毒检查、字数 18000~44000 字长文体例、中文摘要(约200字)+英文摘要(约200词)报道性四要素、中英文关键词(3~5)、中图分类号(TP)、GB/T 7714 参考文献中英文对照、编辑部重复率检测红线、栏目归属与稿件类型，并在提交前做退稿风险分诊。适用于把一份模式识别/人工智能方向的中文原创长文打磨到符合本刊同行评审门槛的场景。

在为《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 划分正文与附录/补充材料/多媒体附件时调用。覆盖以"决定性"为原则区分哪些内容必须进正文(支撑核心主张)、哪些可移入附录(证明细节、额外实验、超参表、更多可视化)、如何组织补充材料使外审无需附录也能判断主要贡献、以及附件(数据样例、演示视频)的提交与匿名注意事项。用于在 18000~44000 字长文体例下合理编排信息密度，避免正文臃肿或关键证据缺失，本刊附件政策以官网当期须知为准(待核实)。

在为《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 判断一个选题是否契合、以及该写成何种稿件类型时调用。本刊专注模式识别、人工智能、机器学习、计算机视觉、自然语言处理、智能系统等 AI 细分方向，比综合性计算机刊更聚焦 AI，与《自动化学报》(控制为主)、《计算机学报》(全学科)、《软件学报》(系统软件)分工不同。用于评估贡献是否有原创增量、是否落在本刊 AI 学科范围、该投研究论文还是综述、以及是否更适合改投兄弟刊，避免因不符宗旨在初审被退。

在为《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 规划或推进一次完整投稿(从选题、写作、实证、投稿、外审修回到录用见刊)时调用，作为编排其余 11 个技能的总线。覆盖本刊编辑初审→专家外审→主编终审的同行评审时间线、官方约 6 个月审稿口径、18000~44000 字长文节奏、多轮修回预算与各阶段应触发的子技能。用于把一份模式识别/人工智能中文长文的全生命周期拆解为可执行的阶段清单与里程碑，避免遗漏关键环节。

在为《模式识别与人工智能》(Pattern Recognition and Artificial Intelligence, PR&AI) 撰写或打磨中文长文体例时调用。覆盖报道性中文摘要(约200字)与English Abstract(约200词)的四要素、中英文关键词(3~5)、中图分类号(TP)、作者简介与基金项目、参考文献 GB/T 7714 且中文文献中英文对照、量与单位法定用法、首页范式(问题→现状不足→贡献→证据→意义)，以及模式识别/机器学习论文的公式、算法、图表规范。用于把一份 AI 细分方向的中文稿件写到符合本刊体例、经得起编辑初审与外审的水准。

Use when packaging an IEEE PerCom sensing artifact and dataset for reproducibility and any badging (IEEE Open Research Objects / Results Reproduced, IEEE DataPort or Zenodo deposit), covering what a ubicomp evaluator checks first for human-subjects sensing data, cross-subject reproduction, de-identification, and honest degrees of reproducibility.

Use when drafting an IEEE PerCom rebuttal after being invited following the initial reviews, covering the bounded single-round reply that answers explicit reviewer questions, corrects misreadings, points to evidence already in the paper without promising new experiments, and preserves double-blindness.

Use when preparing an accepted IEEE PerCom paper for its IEEE Xplore camera-ready, covering de-anonymization, the IEEEtran compsocconf template and page budget, IEEE Xplore metadata (PDF eXpress, eCopyright, ORCID, index terms), integrating reviewer-required changes without scope creep, permanentizing the dataset links, and IEEE production checks.

Use when designing or auditing IEEE PerCom empirical evaluations, covering real human subjects, leave-one-subject-out / cross-subject evaluation, F1 and event-level metrics on imbalanced activity classes, deployment realism (free-living vs. lab), fair baselines, contamination-aware model ablations, and matching evidence to the shape of each pervasive-computing claim.

Use when positioning an IEEE PerCom submission against the pervasive/ubiquitous-computing literature across PerCom, ACM UbiComp/IMWUT, MobiCom, MobiSys, SenSys, and IPSN, writing delta-first contrast rather than a citation catalog, keeping self-citations double-blind, and handling concurrent, preprint, and prior-version overlap.

Use when strengthening IEEE PerCom reproducibility and open-data evidence for human-subjects sensing, covering the dataset-availability statement, de-identified datasets with IRB/consent handling, sensing provenance (devices, sampling, labeling), cross-subject reproducibility, honest degrees of reproducibility, and consistency between what the paper says and what the dataset contains.

Use when reasoning about how an IEEE PerCom research submission is evaluated, covering double-blind review, the three-TPC-member model, the early-rejection stage, the single-round bounded rebuttal gated by a "weak accept," the accept/reject decision, and how PerCom's process differs from ACM UbiComp/IMWUT's journal revise cycle.

Use when auditing an IEEE PerCom research-track submission for HotCRP readiness, covering the mandatory paper-registration step, the IEEEtran 9+1 two-column page budget, double-blind anonymization, the open-data / human-subjects plan, IEEE Xplore publication, and desk-reject triage before the AoE cutoff.

Use when deciding what belongs in an IEEE PerCom paper body versus its dataset/artifact and any appendix, covering the tight IEEEtran 9+1 page budget, the rule that decision-critical evidence stays inside the reviewed pages, double-blind supplementary material, and how to split a human-subjects sensing paper between body and dataset.

Use when deciding whether a pervasive-computing project belongs at IEEE PerCom or should be routed to ACM UbiComp/IMWUT, MobiCom, MobiSys, SenSys, or IPSN, and when distinguishing PerCom's human-centric ubicomp focus from networked-sensor-systems venues by contribution shape, the human-centricity test, and the IEEE-conference vs. IMWUT-journal model.

Use when planning an IEEE PerCom project timeline from venue fit through paper registration, the September submission, the early-rejection gate, the bounded rebuttal, the IEEE Xplore camera-ready, and in-person presentation, with backward-planning offsets for a human-subjects sensing paper and honest handling of the single-annual-deadline cycle.

Use when revising an IEEE PerCom paper for a pervasive-computing contribution on the first page, cross-subject claims stated precisely, a limitations section that argues rather than recites, evidence proportional to the claim, double-blind wording, and disciplined use of the tight IEEEtran 9-page budget.

Use when appraising the credibility of the studies a Perspectives on Psychological Science (PoPS) piece synthesizes and calibrating comprehensiveness, balance, and fair treatment of competing camps — including reform-minded but evidence-based critique. Weighs evidence and audits even-handedness; it does not design the spine (ppsych-organizing-framework) or run new analyses.

Use when working with the Perspectives on Psychological Science (PoPS) editor and editorial team — proposal-stage scope, what review referees of a perspective evaluate, suggesting reviewers, and the author–editor relationship. Plans the interaction; it does not run the submission preflight (ppsych-submission) or draft the response letter (ppsych-revision).

Use when systematically gathering and synthesizing literature across psychology sub-areas for a Perspectives on Psychological Science (PoPS) integrative review, theoretical statement, or meta-science piece — coverage discipline, and for meta-science the systematic evidence about the field's practices. Builds the evidence corpus; it does not impose the analytical spine (ppsych-organizing-framework) or audit balance (ppsych-comprehensiveness-and-balance).

Use when imposing an analytical or conceptual structure on a body of psychology research for a Perspectives on Psychological Science (PoPS) integrative review or theoretical statement — the unifying argument or "spine" that turns a reading list into a claim about the field. Designs the framework; it does not gather the literature (ppsych-literature-synthesis) or audit balance (ppsych-comprehensiveness-and-balance).