document-workflow
v1.3.1Academic paper research workflow. Use when searching, downloading, or analyzing arXiv papers. Triggers: "search papers", "download paper", "arxiv", "latex source", "paper summary", "read paper".
Installation
Document Workflow
Academic paper research: Search → Download LaTeX → Read & Summarize
Quick Start
1. Search Papers
python -m skills.document-workflow.scripts.search_papers --query "world model" --max_results 5 --year_from 2024
2. Download LaTeX Source
python -m skills.document-workflow.scripts.latex_reader "2301.07088" --keep
3. Read & Summarize
Read the LaTeX source files and summarize following the reading guide below.
Reading Guide
After downloading LaTeX source to arxiv_{id}/, read the .tex files in this order:
Step 1: Get Metadata
Read the main .tex file (usually main.tex, root.tex, or {paper-id}.tex) for:
- title{} - Paper title
- author{} - Authors
- begin{abstract}...end{abstract} - Abstract
Step 2: Understand the Problem
Read the Introduction section (usually intro.tex, 1-introduction.tex, or first section):
- What problem does this paper solve?
- What are the key contributions?
- How does it relate to prior work?
Step 3: Understand the Method
Read the Method/Approach section:
- What is the proposed approach?
- Key equations in begin{equation}...end{equation} or begin{align}...end{align}
- Algorithm pseudocode in begin{algorithm}...end{algorithm}
Step 4: Check Experiments
Read the Experiments section:
- Datasets used
- Baselines compared
- Metrics in begin{table}...end{table} with results
- Key findings
Step 5: Check References
Read the .bib or .bbl file for:
- Related work citations
- Key papers in the field
Output Schema
Summarize the paper in this JSON format(see more details in ./references/output_schema.json):
{
"paper_title": "Full title",
"authors": ["Author 1", "Author 2"],
"source": "arXiv:XXXX.XXXXX",
"task_definition": {
"domain": "Research domain",
"task": "Specific task",
"problem_statement": "What problem this paper solves",
"key_contributions": ["Contribution 1", "Contribution 2"]
},
"experiments": {
"datasets": ["Dataset 1", "Dataset 2"],
"baselines": ["Baseline 1", "Baseline 2"],
"metrics": [
{"name": "Metric name", "description": "What it measures","definition":"Mathematical definition or formula for the metric"}
],
"results": [
{"setting": "Dataset", "metric": "Metric", "proposed_method": "Score", "best_baseline": "Score"}
],
"key_findings": ["Finding 1", "Finding 2"]
}
}
Scripts
| Script | Function |
|---|---|
search_papers.py |
Search papers (Tavily + Semantic Scholar) |
download_paper.py |
Download PDF (for human reading) |
latex_reader.py |
Download LaTeX source (for AI reading) |
Tips for Reading LaTeX
| LaTeX Command | Meaning |
|---|---|
section{Title} |
Section heading |
subsection{Title} |
Subsection heading |
textbf{text} |
Bold text (often important) |
cite{key} |
Citation reference |
begin{equation}...end{equation} |
Numbered equation |
begin{table}...end{table} |
Table |
begin{figure}...end{figure} |
Figure |
input{file} or subfile{file} |
Include another .tex file |
Config
# Optional: Semantic Scholar API key
export SEMANTIC_SCHOLAR_API_KEY="your-key"
# Default download path
C:UsersLenovoDesktoppapers