Claude Skills by thedixitjain

Use after PNAS reviews arrive to triage the decision, prioritize experiments, and draft a point-by-point response that is respectful, evidence-led, and honest about limits. Do not run before the main text is actually revised.

Use to write the mandatory PNAS Significance Statement — ≤120 words, written so an educated reader outside the field (down to an undergraduate) understands why the work matters. Distinct from the abstract. The highest-value PNAS-specific artifact.

Use after PNAS Nexus reviews arrive to triage the decision, prioritize experiments, and draft a point-by-point response that is respectful, evidence-led, and honest about limits. Covers the case where reviews were carried over from a PNAS transfer. Do not run before the main text is actually revised.

Play Pokemon via headless emulator + RAM reads.

Use when running the pre-submission preflight for a Production and Operations Management (POM) manuscript on ScholarOne — Department Editor routing, 32-page limit, double-blind files, e-companion designation, 350-word abstract, same-data disclosure, and the no-resubmission-after-rejection rule. Preflights the submission; it does not interpret decisions (pom-review-process).

Use when building the model or mechanism for a Production and Operations Management (POM) manuscript — formalizing assumptions, deriving equilibria/propositions for analytical work, or developing OM hypotheses for empirical/behavioral work. Builds the argument; it does not run the analysis (pom-data-analysis) or frame the contribution (pom-contribution-framing).

Use when deciding whether an operations-management project fits Production and Operations Management (POM), which POM Department to route it to, or whether to target M&SOM, Management Science, JOM, or another venue. Sets the question and venue; it does not build the model (pom-theory-development).

Use when deciding which pom-* sub-skill to invoke next, or when sequencing manuscript work from topic selection through rebuttal for a Production and Operations Management (POM) manuscript. Routes — it does not replace — the specialized skills, and it identifies your method track (analytical / empirical / behavioral / data-science).

> Quick-reference card for all ponytail modes, skills, and commands. One-shot display, not a persistent mode. Trigger: /ponytail-help, \"ponytail help\", \"what ponytail commands\", \"how do I use ponytail\".

Use when building tables and figures for a Population and Development Review (PDR, Wiley / Population Council) manuscript so exhibits are self-contained, accessible, and legible to a broad demography-and-development readership. Covers distinctive demographic graphics (population pyramids, age schedules, survival curves, projection fans) and cross-country comparative exhibits. Designs exhibits; it does not run the analysis.

Use when drafting a POPL author response during the optional multi-day window — triaging soundness objections against misread definitions, answering \"what does Theorem 3 actually assume\" questions with pointers rather than new material, staying concise per the CFP, and protecting the path to conditional acceptance.

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.

Make a PortalJS portal harvestable by national/EU/US open-data portals — emit standards-compliant DCAT catalog feeds (DCAT 2/3, DCAT-AP, DCAT-US, national profiles) in JSON-LD, Turtle, and RDF/XML at build, with autodiscovery and per-profile conformance checking. Use when a portal needs to be harvested by data.europa.eu, data.gov, or a national open-data catalog.

Convert OpenAPI 3.x or Swagger 2.0 specs (YAML or JSON) into complete, import-ready Postman Collection v2.1 JSON files. Use this skill whenever the user provides or references an OpenAPI spec, Swagger file, openapi.yaml, swagger.json, or uses phrases like \"convert my OpenAPI spec\",...

When the user wants to identify and nurture developer advocates, build champion programs, or turn active users into contributors and evangelists. Trigger phrases include \"power users,\" \"developer advocates,\" \"ambassador program,\" \"champion program,\" \"community contributors,\" \"referral...

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.

Create pull requests following Sentry's engineering practices.

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。

A ship gate that runs before any production deploy: checks the silent failure modes that make a deploy 'succeed' while prod stays broken, then verifies the live revision instead of trusting deploy output.

Problem-solving strategies for predicate logic in mathematical logic

Creates or reviews the required Clean Room preflight goal contract before source discovery, decomposition, attended execution, or unattended execution.

Identify failure modes before they occur using structured risk analysis

One sentence - what this skill does and when to invoke it

Problem-solving strategies for prime numbers in graph number theory

Use when choosing suggested and opposed referees for a Physical Review Letters submission and pre-empting the objections APS referees are likely to raise. Plans referee handling; does not write the manuscript or the rebuttal.

Use when responding to Physical Review Letters referee reports or editor decisions — point-by-point reply, resubmission, and the APS appeal route. Structures the response and revision; does not redraft the science from scratch.

Use when partitioning content between the Physical Review Letters body and its Supplemental Material, ensuring the Letter stands alone while derivations and extended data live in the SM. Organizes the SM; does not write the Letter body.

Use when deciding which prl-* sub-skill to invoke next, or when sequencing manuscript work from scope-fit through revision for a Physical Review Letters (PRL) manuscript. Routes — does not replace — the specialized skills.

Generate a complete, week-by-week launch playbook for any product, service, or feature launch. This skill produces a tactical plan with templates, checklists, email sequences, social posts, and metrics tracking -- everything needed to execute a successful launch.

Implements hub-and-spoke lazy loading to minimize token usage in large skills. Use when building multi-module skills that need conditional on-demand loading.

Generate and publish a project status artifact — an opinionated, tabbed status page for a project too big for one update (overview & success criteria, the workstream sequence, next steps, plus background, plan, risks & open questions, and decisions/FAQ when they earn a tab) — published with the built-in Artifact tool to a default-private claude.ai page the user can share with teammates. Use when a piece of work spans several workstreams and you want a shareable overview kept current. Each art...

Executes implementation plans with progress tracking, checkpoint validation, and quality gates. Use after planning is complete and tasks are ready to implement.

> 作为 Team Skills Platform 中的 Project Manager（项目管理），负责排期、依赖协调、风险跟踪、里程碑推进与跨角色节奏管理。 当用户明确点名该角色，或当前任务需要该角色承担主责时使用。

Converts a specification into a phased, dependency-ordered implementation plan. Use after specification is complete and before execution begins.

Enforces validation and evidence before claiming work complete. Use before declaring implementation done, creating a PR, or submitting deliverables for review.

Problem-solving strategies for proof theory in mathematical logic

Problem-solving strategies for propositional logic in mathematical logic

Starter: one-screen provider health summary — availability, auth method, version drift, and cost posture for every seatable provider

Use when defining eligibility criteria and coding studies for a Psychological Bulletin review or meta-analysis — inclusion/exclusion rules, a codebook, double-coding, and inter-rater reliability. Governs how studies enter and are coded; effect-size modeling lives in psychbull-meta-analysis-methods.

Use when computing effect sizes and fitting the meta-analytic model for a Psychological Bulletin manuscript — effect-size metrics, random-effects vs. fixed-effect choice, dependent effect sizes (RVE / multilevel), and heterogeneity (Q, I², τ², prediction interval). Guides the core synthesis; moderators and bias diagnostics live in psychbull-moderators-and-bias.

Use when setting the scope of a Psychological Review theory — what it explains, what it does NOT, and (for formal models) whether its parameters are identifiable. Bounds the theory; it does NOT derive its predictions (psychrev-argument-development) or frame its advance over rivals (psychrev-contribution-framing).

Use when a Psychological Review decision letter (usually a major revision) has arrived and you must write the response document and revise the theory. Drafts the response and revision plan; it does NOT run the resubmission preflight (psychrev-submission) or build new theory from scratch (psychrev-theory-construction).

Use when deciding which psychrev-* sub-skill to invoke next, or when sequencing a theory or formal-model manuscript from problem framing through masked-review revision for a Psychological Review submission. Routes — does not replace — the specialized skills.