Typst Papers (typst-paper)
Modern academic paper writing assistant with Typst.
Overview
The typst-paper skill provides comprehensive support for academic paper writing using Typst, a modern typesetting system that compiles in milliseconds. Supports both English and Chinese papers for major publication venues.
Key Features
- Lightning-fast compilation (millisecond-level vs LaTeX's seconds)
- Clean, intuitive syntax (easier learning curve than LaTeX)
- Real-time preview with watch mode
- Format checking with venue-specific rules
- Grammar analysis for English papers
- Academic expression optimization for both languages
- Chinese-to-English translation (Deep Learning, Time Series, Industrial Control)
- De-AI writing analysis for reducing AI-generated text traces
- Template support (IEEE, ACM, Springer, NeurIPS, etc.)
Environment Requirements
Installation:
# Using Cargo (Rust package manager)
cargo install typst-cli
# Using Homebrew (macOS)
brew install typst
# Using package manager (Linux)
sudo pacman -S typst # Arch Linux
Verify installation:
typst --version
Using the Skill in Claude Code
This skill is designed to work with Claude Code and similar AI assistants. Simply mention the relevant trigger words in your conversation, and the assistant will activate the appropriate module.
Argument Conventions
Provide clear inputs in your request:
- Main
.typpath (required for tool execution) - Target scope (section/chapter or full document)
- Module choice (compile / format / grammar / template / etc.)
If any of these are missing or ambiguous, the assistant will ask for clarification instead of guessing.
Execution Guardrails
- Tools/scripts run only when you explicitly request execution.
- Operations that overwrite outputs require explicit confirmation.
Trigger Words
| Module | Triggers | Function |
|---|---|---|
| Compile | compile, 编译, typst compile | Typst compilation |
| Format Check | format, lint, style check | Format checking |
| Grammar Analysis | grammar, proofread | Grammar analysis |
| Long Sentence | long sentence, simplify | Sentence decomposition |
| Expression | academic tone, improve writing | Expression optimization |
| Logic & Methodology | logic, coherence, 逻辑, 衔接, methodology | Logical coherence & methodological depth |
| Translation | translate, 翻译, 中译英 | Chinese-English translation |
| Bibliography | bib, bibliography, citation | Bibliography checking |
| De-AI Polishing | deai, 去AI化, humanize | Reduce AI writing traces |
| Template | template, IEEE, ACM | Template configuration |
| Title Optimization | title, 标题, title optimization 🆕 | Generate and optimize titles |
Example Usage
Compile your paper:
Please compile my Typst paper main.typ
Check grammar:
Can you check the grammar in my introduction section?
Translate to English:
Translate this Chinese text to academic English (Deep Learning domain):
本文提出了一种基于Transformer的方法...
Quick Examples by Module
Check format compliance for main.typ
Simplify long sentences in the introduction section
Improve academic tone in the abstract
Verify references.bib and check citations in main.typ
Reduce AI writing traces in the methods section
Provide an IEEE template setup for Typst
Compilation Module
Basic Commands
| Command | Purpose | Notes |
|---|---|---|
typst compile main.typ |
Single compilation | Generates PDF |
typst watch main.typ |
Watch mode | Auto-recompile on changes |
typst compile main.typ output.pdf |
Custom output | Specify output filename |
typst compile --format png main.typ |
Other formats | PNG, SVG support |
typst fonts |
List fonts | Show available system fonts |
Usage Examples
# Basic compilation (recommended)
typst compile main.typ
# Watch mode (real-time preview)
typst watch main.typ
# Specify output directory
typst compile main.typ --output build/paper.pdf
# Export as PNG (for preview)
typst compile --format png main.typ
# View available fonts
typst fonts
# Use custom font path
typst compile --font-path ./fonts main.typ
Compilation Speed
- Typst compiles in milliseconds (vs LaTeX's seconds)
- Incremental compilation: only recompiles changed parts
- Perfect for real-time preview and rapid iteration
Chinese Support
// Chinese font configuration
#set text(
font: ("Source Han Serif", "Noto Serif CJK SC"),
lang: "zh",
region: "cn"
)
Format Check Module
Checks
| Category | Items | Standards |
|---|---|---|
| Margins | Top/bottom/left/right | Usually 1 inch (2.54cm) |
| Line Spacing | Single/double spacing | Per journal requirements |
| Font | Body font and size | Times New Roman 10-12pt |
| Headings | Heading hierarchy | Clear levels, proper numbering |
| Figures/Tables | Caption format | Figures below, tables above |
| Citations | Citation consistency | Numeric/author-year format |
Typst Format Configuration
// Page setup
#set page(
paper: "a4", // or "us-letter"
margin: (x: 2.5cm, y: 2.5cm)
)
// Text setup
#set text(
font: "Times New Roman",
size: 11pt,
lang: "en"
)
// Paragraph setup
#set par(
justify: true,
leading: 0.65em,
first-line-indent: 1.5em
)
// Heading setup
#set heading(numbering: "1.1")
Grammar Analysis Module
LLM-based grammar checking focusing on:
- Subject-verb agreement
- Article usage (a/an/the)
- Tense consistency (methods in past tense, results in present)
- Chinglish detection
Common Grammar Issues
| Error Type | Example | Correction |
|---|---|---|
| Missing article | propose method | propose a method |
| Subject-verb disagreement | The data shows | The data show |
| Tense inconsistency | We proposed... The results shows | We proposed... The results show |
| Chinglish | more and more | increasingly |
Long Sentence Analysis Module
Trigger Conditions
- English: Sentences >50 words OR >3 clauses
- Chinese: Sentences >60 characters OR >3 clauses
Output Format
// Long sentence detected (Line 45, 67 words) [Severity: Minor] [Priority: P2]
// Main structure: [Subject + Verb + Object]
// Modifiers:
// - [Relative clause] which...
// - [Purpose clause] to...
// Suggested rewrite: [Simplified version]
Academic Expression Module
English Academic Expressions
| ❌ Weak Verbs | ✅ Academic Alternatives |
|---|---|
| use | employ, utilize, leverage |
| get | obtain, achieve, acquire |
| make | construct, develop, generate |
| show | demonstrate, illustrate, indicate |
Chinese Academic Expressions
| ❌ Colloquial | ✅ Academic |
|---|---|
| 很多研究表明 | 大量研究表明 |
| 效果很好 | 具有显著优势 |
| 我们使用 | 本文采用 |
| 可以看出 | 由此可见 |
Logic & Methodology Module
Ensure logical flow between paragraphs and strengthen methodological rigor in academic writing.
AXES Model for Paragraph Coherence
| Component | Description | Example |
|---|---|---|
| Assertion | Clear topic sentence stating the main claim | "Attention mechanisms improve sequence modeling." |
| Xample | Concrete evidence or data supporting the claim | "In our experiments, attention achieved 95% accuracy." |
| Explanation | Analysis of why the evidence supports the claim | "This improvement stems from the ability to capture long-range dependencies." |
| Significance | Connection to broader argument or next paragraph | "This finding motivates our proposed architecture." |
Transition Signals
| Relationship | English Signals | Chinese Signals |
|---|---|---|
| Addition | furthermore, moreover | 此外、进一步 |
| Contrast | however, nevertheless | 然而、但是 |
| Cause-Effect | therefore, consequently | 因此、由此可见 |
| Sequence | first, subsequently, finally | 首先、随后、最后 |
| Example | for instance, specifically | 例如、具体而言 |
Methodological Depth Checklist
- Each claim is supported by evidence (data, citation, or logical reasoning)
- Method choices are justified (why this approach over alternatives?)
- Limitations are acknowledged explicitly
- Assumptions are stated clearly
- Reproducibility details are sufficient (parameters, datasets, metrics)
Common Issues
| Issue | Problem | Fix |
|---|---|---|
| Logical gap | Missing connection between paragraphs | Add transition sentence |
| Unsupported claim | Assertion without evidence | Add citation, data, or reasoning |
| Shallow methodology | "We use X" without justification | Explain why X is appropriate |
| Hidden assumptions | Implicit prerequisites | State assumptions explicitly |
Usage in Claude Code
Check logical coherence in my introduction section
Analyze methodological depth in the methods section
Add transition signals between paragraphs
Translation Module (Chinese → English)
Supported Domains
| Domain | Keywords |
|---|---|
| Deep Learning | neural networks, attention, loss functions |
| Time Series | forecasting, ARIMA, temporal patterns |
| Industrial Control | PID, fault detection, SCADA |
Translation Workflow
- Domain Identification - Identify technical terms
- Terminology Confirmation - Confirm translations
- Translation with Annotations - Translate with notes
- Chinglish Check - Detect and fix common errors
- Academic Polish - Final review
Common Academic Phrases
| Chinese | English |
|---|---|
| 本文提出... | We propose... / This paper presents... |
| 实验结果表明... | Experimental results demonstrate that... |
| 与...相比 | Compared with... / In comparison to... |
| 综上所述 | In summary / In conclusion |
Bibliography Module
Typst Bibliography Management
Method 1: Using BibTeX files
#bibliography("references.bib", style: "ieee")
Method 2: Using Hayagriva format
#bibliography("references.yml", style: "apa")
Supported Citation Styles
ieee- IEEE numeric citationsapa- APA author-yearchicago-author-date- Chicago author-yearmla- MLA humanitiesgb-7714-2015- Chinese national standard
Citation Examples
// In-text citations
According to @smith2020, the method...
Recent studies @smith2020 @jones2021 show...
// Bibliography list
#bibliography("references.bib", style: "ieee")
De-AI Polishing Module
Reduce AI writing traces while preserving Typst syntax and technical accuracy.
Input Requirements
- Source type (required): Typst
- Section (required): Abstract / Introduction / Related Work / Methods / Experiments / Results / Discussion / Conclusion
- Source snippet (required): Paste directly with original indentation
Workflow
1. Syntax Structure Identification Preserve all Typst constructs:
- Functions:
#set,#show,#let - References:
@cite,@ref,@label - Math:
$...$,$ ... $(block-level) - Markup:
*bold*,_italic_,`code` - Custom functions (unchanged by default)
2. AI Pattern Detection:
| Type | Examples | Issue |
|---|---|---|
| Empty phrases | significant, comprehensive, effective | Lack specificity |
| Over-confident | obviously, necessarily, completely | Too absolute |
| Mechanical structures | Empty three-part parallelisms | Lack depth |
| Template expressions | in recent years, more and more | Clichés |
3. Text Rewriting (visible text only):
- Split long sentences (English >50 words, Chinese >50 characters)
- Adjust word order for natural flow
- Replace vague claims with specific statements
- Delete redundant phrases
- Add necessary subjects without introducing new facts
4. Output Generation:
// ============================================================
// DE-AI EDITING (Line 23 - Introduction)
// ============================================================
// Original: This method achieves significant performance improvement.
// Revised: The proposed method improves performance in the experiments.
//
// Changes:
// 1. Removed vague phrase: "significant" → deleted
// 2. Kept the claim without adding new metrics or baselines
//
// ⚠️ [PENDING VERIFICATION]: Add exact metrics/baselines only if supported by data
// ============================================================
= Introduction
The proposed method improves performance in the experiments...
Hard Constraints
- Never modify:
@cite,@ref,@label, math environments - Never add: new data, metrics, comparisons, contributions, experimental settings, citation numbers
- Only modify: visible paragraph text, section titles
Section-Specific Guidelines
| Section | Focus | Constraints |
|---|---|---|
| Abstract | Purpose/Method/Key Results (with numbers)/Conclusion | No generic claims |
| Introduction | Importance → Gap → Contribution (verifiable) | Restrain claims |
| Related Work | Group by line, specific differences | Concrete comparisons |
| Methods | Reproducibility (process, parameters, metrics) | Implementation details |
| Results | Report facts and numbers only | No interpretation |
| Discussion | Mechanisms, boundaries, failures, limitations | Critical analysis |
| Conclusion | Answer research questions, no new experiments | Actionable future work |
Template Configuration Module
Template examples are maintained in:
references/TEMPLATES.md
Venue-Specific Rules
IEEE
- Two-column format, 0.33 inch column gap
- Times New Roman 10pt
- Active voice, methods in past tense
- Figure/table numbering: Fig. 1, Table I
ACM
- Two-column format, A4 or US Letter
- Present tense for general truths
- Citation format: numeric or author-year
Springer
- Figure captions below, table captions above
- References in alphabetical order
NeurIPS/ICML
- 8-page limit (excluding references)
- Anonymous submission (double-blind review)
- Specific formatting requirements
Typst Advantages
vs LaTeX
| Feature | Typst | LaTeX |
|---|---|---|
| Compilation Speed | Milliseconds | Seconds |
| Syntax | Clean and intuitive | Complex and verbose |
| Error Messages | Clear and friendly | Cryptic and confusing |
| Learning Curve | Gentle | Steep |
| Real-time Preview | Native support | Requires additional tools |
Use Cases
- ✅ Rapid prototyping and drafts
- ✅ Documents requiring frequent modifications
- ✅ Team collaboration (simple syntax)
- ✅ Small to medium papers (<100 pages)
- ⚠️ Complex mathematical formulas (LaTeX more mature)
- ⚠️ Specific journal templates (may require LaTeX)
Quick Start
Install Typst:
# Using Cargo (Rust package manager)
cargo install typst-cli
# Using Homebrew (macOS)
brew install typst
# Using package manager (Linux)
sudo pacman -S typst # Arch Linux
Create your first paper:
# Initialize from template
typst init @preview/charged-ieee
# Compile
typst compile main.typ
# Watch mode (recommended)
typst watch main.typ
Common commands:
# View help
typst --help
# View available fonts
typst fonts
# Specify output format
typst compile --format png main.typ
# Use custom fonts
typst compile --font-path ./fonts main.typ
Reference Files
references/TYPST_SYNTAX.md: Typst syntax guidereferences/STYLE_GUIDE.md: Academic writing rulesreferences/COMMON_ERRORS.md: Common mistakesreferences/VENUES.md: Conference/journal requirementsreferences/DEAI_GUIDE.md: De-AI writing guidereferences/TEMPLATES.md: Typst template examples
Title Optimization Module
Generate and optimize paper titles for both English and Chinese papers following best practices.
Key Principles
Based on IEEE/ACM/Springer/NeurIPS guidelines and GB/T 7713.1-2006 (for Chinese):
English Papers:
- Conciseness: Remove "A Study of", "Research on", "Novel", "New"
- Searchability: Key terms (Method + Problem) in first 65 characters
- Length: Optimal 10-15 words
- Specificity: Concrete method/problem names
- Jargon-Free: Avoid obscure abbreviations
Chinese Papers:
- 简洁性: Remove "关于...的研究", "新型", "改进的"
- 可搜索性: Key terms in first 20 characters
- 长度: Optimal 15-25 characters
- 具体性: Concrete terms
- 规范性: Follow standards
Quality Scoring
Each title receives a score (0-100) based on five criteria with language-specific thresholds.
Usage in Claude Code
Check existing title:
Check the quality of my paper title
检查我的论文标题质量
Generate title candidates:
Generate title candidates for my paper
根据摘要生成标题候选方案
Optimize existing title:
Optimize my paper title to follow IEEE best practices
优化我的论文标题
The assistant will:
- Auto-detect language (English/Chinese)
- Provide quality score with breakdown
- Generate multiple ranked candidates
- Suggest Typst code for the best title
Title Patterns
English:
- Method for Problem: "Transformer for Time Series Forecasting"
- Method: Problem in Domain: "Graph Neural Networks: Fault Detection in Industrial Systems"
- Problem via Method: "Time Series Forecasting via Attention Mechanisms"
Chinese:
- 问题的方法: "时间序列预测的Transformer方法"
- 方法及应用: "注意力机制及其在工业控制中的应用"
- 面向领域的方法: "面向智能制造的深度学习方法"
Good vs Bad Examples
English:
Good: "Transformer for Time Series Forecasting in Industrial Control"
Bad: "A Novel Study on Improved Time Series Forecasting Using Transformers"
Chinese:
好:工业控制系统时间序列预测的Transformer方法
差:关于基于Transformer的工业控制系统时间序列预测的研究
Typst Title Configuration
English Paper:
#align(center)[
#text(size: 18pt, weight: "bold")[
Transformer-Based Time Series Forecasting for Industrial Control
]
]
Chinese Paper:
#align(center)[
#text(size: 18pt, weight: "bold", font: "Source Han Serif")[
工业控制系统时间序列预测的Transformer方法
]
#v(0.5em)
#text(size: 14pt, font: "Times New Roman")[
Transformer-Based Time Series Forecasting for Industrial Control Systems
]
]
Best Practices
English:
- Start with keywords (Method + Problem in first 10 words)
- Be specific ("Transformer" > "Deep Learning")
- Remove fluff ("Novel", "Study", "Research")
- Target 10-15 words
- Match venue style
Chinese:
- 关键词前置(方法+问题在前20字)
- 具体明确("Transformer" > "深度学习")
- 删除冗余("关于"、"研究"、"新型")
- 目标 15-25 字
- 符合规范
References
- IEEE Author Center
- Royal Society Blog on Title Optimization
- GB/T 7713.1-2006 (Chinese thesis standards)
Recommended Workflows
Fast Iteration (Drafting)
- Compile or watch mode
- Format check (basic)
- Grammar analysis (abstract + intro)
Pre-Submission Pass
- Format check (venue-specific)
- Expression optimization
- De-AI polishing
- Bibliography verification
- Template check (if required by venue)