- name
- document-workflow
- description
- Academic paper research workflow. Use when searching, downloading, or analyzing arXiv papers. Triggers: "search papers", "download paper", "arxiv", "latex source", "paper summary", "read paper".
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 20242. Download LaTeX Source
python -m skills.document-workflow.scripts.latex_reader "2301.07088" --keep3. 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:
\ itle{}- 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 |
\ extbf{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:\Users\Lenovo\Desktop\papers