L

latex-paper-en

by @bahayonghangv
4.3(64)

既存の英語LaTeX学術論文プロジェクトを支援し、ワークフローを簡素化し、モジュールの特定とタスクの実行を支援し、論文執筆効率を向上させます。

latexacademic-writingscientific-publishingtypesettingresearch-papersGitHub
インストール方法
npx skills add bahayonghang/academic-writing-skills --skill latex-paper-en
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Before / After 効果比較

1
使用前

英文のLaTeX学術論文を作成する際、複雑な組版や引用管理のために多くの時間を費やしがちです。モジュールやタスクの手動処理は煩雑で間違いやすく、執筆効率の低下を招き、論文提出の遅延に影響を与えます。

使用後

英文のLaTeX学術論文プロジェクトを支援し、ワークフローを簡素化します。著者がモジュールを特定し、タスクを実行するのを助け、論文執筆効率を大幅に向上させ、著者がコンテンツ作成により集中できるようにし、学術成果の創出を加速させます。

SKILL.md

latex-paper-en

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.

  • 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

  • translation of academic prose

  • title optimization

  • figure or caption quality checks

  • 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

Module Router

Module Use when Primary command Read next

compile Build fails or the user wants a fresh compile uv run python -B $SKILL_DIR/scripts/compile.py main.tex references/modules/COMPILE.md

format User asks for LaTeX or venue formatting review uv run python -B $SKILL_DIR/scripts/check_format.py main.tex references/modules/FORMAT.md

bibliography Missing citations, unused entries, BibTeX validation uv run python -B $SKILL_DIR/scripts/verify_bib.py references.bib --tex main.tex references/modules/BIBLIOGRAPHY.md

grammar Grammar and surface-level language fixes uv run python -B $SKILL_DIR/scripts/analyze_grammar.py main.tex --section introduction references/modules/GRAMMAR.md

sentences Long, dense, or hard-to-read sentences uv run python -B $SKILL_DIR/scripts/analyze_sentences.py main.tex --section introduction references/modules/SENTENCES.md

logic Weak argument flow, unclear transitions, coherence issues uv run python -B $SKILL_DIR/scripts/analyze_logic.py main.tex --section methods references/modules/LOGIC.md

expression Academic tone polish without changing claims uv run python -B $SKILL_DIR/scripts/improve_expression.py main.tex --section related references/modules/EXPRESSION.md

translation Chinese-to-English academic translation or bilingual polishing uv run python -B $SKILL_DIR/scripts/translate_academic.py input.txt --domain deep-learning references/modules/TRANSLATION.md

title Generate, compare, or optimize paper titles uv run python -B $SKILL_DIR/scripts/optimize_title.py main.tex --check references/modules/TITLE.md

figures Figure existence, extension, DPI, or caption review uv run python -B $SKILL_DIR/scripts/check_figures.py main.tex references/REVIEWER_PERSPECTIVE.md

deai Reduce AI-writing traces while preserving LaTeX syntax uv run python -B $SKILL_DIR/scripts/deai_check.py main.tex --section introduction references/modules/DEAI.md

experiment Inspect experiment design/write-up quality uv run python -B $SKILL_DIR/scripts/analyze_experiment.py main.tex --section experiments references/modules/EXPERIMENT.md

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, ask only for the file path and the target module.

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.

Workflow

  • Parse $ARGUMENTS and identify the smallest matching module.

  • Read only the reference file needed for that module.

  • Run the module script with uv run python -B ....

  • Summarize issues, suggested fixes, and blockers in LaTeX-friendly comments.

  • 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.

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.”

  • “Review the experiments section for overclaiming, missing ablations, and weak baseline comparisons.”

See examples/ for complete request-to-command walkthroughs. Weekly Installs381Repositorybahayonghang/ac…g-skillsGitHub Stars65First SeenJan 27, 2026Security AuditsGen Agent Trust HubPassSocketPassSnykWarnInstalled onopencode356gemini-cli341codex339cursor332github-copilot322kimi-cli307

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統計データ

インストール数2.2K
評価4.3 / 5.0
バージョン
更新日2026年5月23日
比較事例1 件

ユーザー評価

4.3(64)
5
36%
4
48%
3
14%
2
2%
1
0%

この Skill を評価

0.0

対応プラットフォーム

🔧Claude Code
🔧OpenClaw
🔧OpenCode
🔧Codex
🔧Gemini CLI
🔧GitHub Copilot
🔧Amp
🔧Kimi CLI

タイムライン

作成2026年3月17日
最終更新2026年5月23日