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latex-paper-en乳胶纸 en

Agent Skill

latex-paper-en 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

25,608

周安装

1,137

GitHub Stars

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下载量

8,976
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:latex-paper-en(乳胶纸 en)
来源仓库:https://github.com/bahayonghang/academic-writing-skills
仓库路径:skills/latex-paper-en
安装命令:
npx skills add https://github.com/bahayonghang/academic-writing-skills --skill latex-paper-en
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/bahayonghang/academic-writing-skills --skill latex-paper-en

简介

通过有针对性的基于模块的检查来编译、审核和改进英语 LaTeX 会议和期刊论文。

  • 支持12个专业模块,涵盖编译、格式化、参考书目验证、语法、句子清晰度、逻辑流程、表达修饰、翻译、标题优化、图形质量、伪代码审查和实验部分分析。
  • 默认保留 LaTeX 语法、引文、参考文献、标签和数学环境;以差异注释风格返回结果,以便于集成。
  • 专为 IEEE、ACM、Springer、NeurIPS 和 ICML 提交工作流程而设计;包括特定于场地的格式期望和审稿人视角启发法。
  • 将请求路由到最小的匹配模块,以保持工作流程低摩擦;支持特定于章节的分析和可选的参考书目路径。

SKILL.md

LaTeX Academic Paper Assistant (English)

Use this skill for targeted work on an existing English LaTeX paper project. Keep the workflow low-friction: identify the right module, run the smallest useful check, and return actionable comments in LaTeX-friendly review format.

Capability Summary

  • Compile and diagnose LaTeX build failures.
  • Audit formatting, bibliography, grammar, sentence length, argument logic, and figure quality.
  • Diagnose and rewrite-plan literature review sections around thematic synthesis, comparison, and gap derivation.
  • Review IEEE-style pseudocode blocks, figure-wrapped algorithms, captions, labels, comments, and algorithm package choices.
  • Improve expression, translate academic prose, optimize titles, and reduce AI-writing traces.
  • Review experiment sections without rewriting citations, labels, or math.

Triggering

Use this skill when the user has an existing English .tex paper project and wants help with:

  • compiling or fixing build errors
  • format or venue compliance
  • bibliography and citation validation
  • grammar, sentence, logic, or expression review
  • literature review restructuring, related-work synthesis, or research-gap derivation
  • translation of academic prose
  • title optimization
  • figure or caption quality checks
  • pseudocode and algorithm-block review
  • de-AI editing of visible prose
  • experiment-section analysis

Do Not Use

Do not use this skill for:

  • planning or drafting a paper from scratch
  • deep literature research or fact-finding without a paper project
  • Chinese thesis-specific structure/template work
  • Typst-first paper workflows
  • DOCX/PDF conversion tasks that do not involve the LaTeX source
  • multi-perspective review, scoring, or submission gate decisions (use paper-audit)
  • standalone algorithm design from scratch without a paper project

Module Router

ModuleUse whenPrimary commandRead next
compileBuild fails or the user wants a fresh compileuv run python -B $SKILL_DIR/scripts/compile.py main.texreferences/modules/COMPILE.md
formatUser asks for LaTeX or venue formatting reviewuv run python -B $SKILL_DIR/scripts/check_format.py main.texreferences/modules/FORMAT.md
bibliographyMissing citations, unused entries, BibTeX validationuv run python -B $SKILL_DIR/scripts/verify_bib.py references.bib --tex main.texreferences/modules/BIBLIOGRAPHY.md
grammarGrammar and surface-level language fixesuv run python -B $SKILL_DIR/scripts/analyze_grammar.py main.tex --section introductionreferences/modules/GRAMMAR.md
sentencesLong, dense, or hard-to-read sentencesuv run python -B $SKILL_DIR/scripts/analyze_sentences.py main.tex --section introductionreferences/modules/SENTENCES.md
logicWeak argument flow, unclear transitions, introduction funnel problems, or abstract/conclusion misalignmentuv run python -B $SKILL_DIR/scripts/analyze_logic.py main.tex --section methodsreferences/modules/LOGIC.md
literatureRelated Work is list-like, under-compared, or missing an evidence-backed research gapuv run python -B $SKILL_DIR/scripts/analyze_literature.py main.tex --section relatedreferences/modules/LITERATURE.md
expressionAcademic tone polish without changing claimsuv run python -B $SKILL_DIR/scripts/improve_expression.py main.tex --section relatedreferences/modules/EXPRESSION.md
translationChinese-to-English academic translation or bilingual polishinguv run python -B $SKILL_DIR/scripts/translate_academic.py input.txt --domain deep-learningreferences/modules/TRANSLATION.md
titleGenerate, compare, or optimize paper titlesuv run python -B $SKILL_DIR/scripts/optimize_title.py main.tex --checkreferences/modules/TITLE.md
figuresFigure existence, extension, DPI, or caption reviewuv run python -B $SKILL_DIR/scripts/check_figures.py main.texreferences/REVIEWER_PERSPECTIVE.md
pseudocodeIEEE-safe pseudocode review, algorithm2e cleanup, caption/label/reference checks, and comment-length reviewuv run python -B $SKILL_DIR/scripts/check_pseudocode.py main.tex --venue ieeereferences/modules/PSEUDOCODE.md
deaiReduce AI-writing traces while preserving LaTeX syntaxuv run python -B $SKILL_DIR/scripts/deai_check.py main.tex --section introductionreferences/modules/DEAI.md
experimentInspect experiment design/write-up quality, discussion depth, discussion layering, and conclusion completenessuv run python -B $SKILL_DIR/scripts/analyze_experiment.py main.tex --section experimentsreferences/modules/EXPERIMENT.md
tablesTable structure validation, three-line table generation, or booktabs reviewuv run python -B $SKILL_DIR/scripts/check_tables.py main.texreferences/modules/TABLES.md
abstractAbstract five-element structure diagnosis and word count validationuv run python -B $SKILL_DIR/scripts/analyze_abstract.py main.texreferences/modules/ABSTRACT.md
adaptJournal adaptation: reformat paper for a different venue(LLM-driven workflow)references/modules/ADAPT.md

Routing Rules

  • Infer the module from the user request before asking follow-up questions. Ask for the module only when two or more modules are equally plausible after keyword routing.
  • If the user asks for 2-3 compatible checks in one turn, run them sequentially instead of forcing a single-module reply.
  • Use this execution order when multiple modules are needed: compile -> bibliography -> format -> figures / tables / pseudocode -> grammar / sentences / deai -> logic / literature / experiment -> title / expression / translation / adapt.
  • Prefer logic for cross-section alignment requests (abstract vs introduction vs conclusion), introduction funnel issues, or contribution drift; prefer literature only when the problem is specifically about Related Work organization, comparison, or gap derivation.
  • Keep experiment for results, discussion, baseline, ablation, significance, limitation, and conclusion-completeness concerns even if the user phrases them as "logic" problems.
  • When a script fails, stop the current module, report the exact command plus exit code, and recommend the next smallest useful fallback instead of silently switching modules.

Required Inputs

  • main.tex or the paper entrypoint.
  • Optional --section SECTION when the request is section-specific.
  • Optional bibliography path when the request targets references.
  • Optional venue/context when the user cares about IEEE, ACM, Springer, NeurIPS, or ICML conventions.

If arguments are missing, preserve the inferred module and ask only for the missing file path, section, bibliography path, or venue context.

Output Contract

  • Return findings in LaTeX diff-comment style whenever possible: % MODULE (Line N) [Severity] [Priority]: Issue...
  • Keep comments surgical and source-aware.
  • Report the exact command used and the exit code when a script fails.
  • Preserve \cite{}, \ref{}, \label{}, custom macros, and math environments unless the user explicitly asks for source edits.
  • For literature, default to diagnosis + rewrite blueprint first; only produce paragraph-level rewriting when the user explicitly asks for prose.

Workflow

  1. Parse $ARGUMENTS, infer the smallest matching module, and keep that inference unless the user explicitly redirects you.
  2. Read only the reference file needed for that module.
  3. If the request contains multiple compatible concerns, run them in the routing order above and keep the output grouped by module.
  4. Run the module script with uv run python -B....
  5. Summarize issues, suggested fixes, and blockers in LaTeX-friendly comments.
  6. If the user asks for a different concern, switch modules instead of overloading one run.

Safety Boundaries

  • Never invent citations, metrics, baselines, or experimental results.
  • Never rewrite bibliography keys, references, labels, or math by default.
  • Treat generated text as proposals; keep source-preserving checks separate from prose rewriting.

Reference Map

  • references/STYLE_GUIDE.md: tone and style defaults.
  • references/VENUES.md: venue-specific expectations.
  • references/CITATION_VERIFICATION.md: citation verification workflow.
  • references/REVIEWER_PERSPECTIVE.md: reviewer-style heuristics for figures and clarity.
  • references/modules/: module-by-module commands and decision notes.
  • references/modules/PSEUDOCODE.md: IEEE-safe defaults for LaTeX pseudocode.

Read only the file that matches the active module.

Example Requests

  • “Compile my IEEE paper and tell me why main.tex still fails after BibTeX.”
  • “Check the introduction section for grammar and sentence length, but do not rewrite equations.”
  • “Audit figures and references in this ACM submission before I submit.”
  • “Rewrite the related work so it reads like a synthesis instead of a paper-by-paper list, but keep all citation anchors intact.”
  • “Check whether this IEEE pseudocode still uses algorithm2e floats and tell me how to make it IEEE-safe.”
  • “Review the experiments section for overclaiming, missing ablations, and weak baseline comparisons.”

See examples/ for complete request-to-command walkthroughs.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.64%
按下载量换算3,199

Claude

29.47%
按下载量换算2,645

Cursor

17.55%
按下载量换算1,575

Gemini CLI

7.77%
按下载量换算697

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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