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drunkcodingdrunkcoding/AgentSkillsArxiv/skills/academic-writing/SKILL.md

academic-writing

Skill4 starsChanged 9 months agoNo licenceView on GitHub

Use when writing, drafting, structuring, or formatting papers for systems venues (OSDI, NSDI, SIGCOMM, MOBICOM, SOSP, FAST) or AI/ML venues (AAAI, ICML, ICLR, NeurIPS), including venue-specific structure, templates, page limits, citations, reproducibility/checklist requirements, OpenReview mechanics, and reciprocal reviewing.

26 other projects use a version of this.

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Projects with it also use scipilot-figure-skill and grill-me.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • HaojaeSkill

    scipilot-figure-skill

    SciPilot Skills 家族成员,负责科研数据可视化——但定位不是"画图工具", 而是"可视化顾问"。先做数据剖析(列类型/样本量/分布/异常值/分组结构/相关性), 再结合用户的论证目标推荐图型,主动拦截科研画图的经典错误(小样本画均值柱掩盖 分布、双 Y 轴、饼图、Y 轴不当截断、rainbow 色图、把分类点连成折线等),最后 产出 Nature / Science / IEEE / Elsevier / PNAS / 中文核心期刊级别的成图。 覆盖纯数据图:折线、柱状、散点、箱线 / 小提琴、热力图、误差棒、分布图(直方 图 / KDE)、相关性矩阵 / 散点矩阵、多面板组合。技术栈 matplotlib + seaborn + SciencePlots(静态)+ plotly(交互)。中英文双语,中文模式自动配置 Noto Sans CJK / Source Han Sans / SimHei 并修复负号方框,支持中文期刊"宋体正文 + Times New Roman 数字"混排。默认色盲安全配色 + 冗余编码 + 灰度预览。出图后做 "视觉自检闭环":渲染 PNG 预览→程序自检缺字/文字裁切/刻度重叠→AI 读图复核遮盖 与子图对齐→回改重渲,直到通过。 当用户的任务涉及以下任何情况时主动触发:论文配图、科研画图、数据可视化、 不知道用什么图、怎么展示数据、用什么图好、期刊投稿图、figure、出版级图表、 matplotlib、seaborn、plotly、误差棒、显著性标注、色盲安全配色、矢量图导出、 中文论文图表、多面板。**即使用户只是给一批数据问"这个怎么画"或"用什么图 好",也应使用本技能——本技能首要能力是"判断该用什么图",其次才是绘制。** 不做示意图、流程图、架构图。

    Also in 3 projects that use this

  • GoogleSkill

    grill-me

    A relentless interview to sharpen a plan or design.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 7 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 18 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 18 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

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