Academic Workflow — Complex Research Tasks

Overview

For complex multi-step tasks (surveys, analyses, paper writing), break them into discrete steps and execute sequentially. This prevents timeouts and allows progress tracking.

When To Use

• User requests a literature survey or review

• User wants benchmark comparison across papers

• User needs end-to-end research workflow (search → analyze → visualize → write)

• Task involves more than 3 tool calls

Strategy: Divide and Conquer

IMPORTANT: For complex tasks, execute ONE step at a time, report progress, then continue.

Example: Paper Survey Workflow

Instead of trying everything at once:

❌ Bad: Try to search, analyze, visualize, and write in one go ✅ Good: Execute step by step with checkpoints

Step-by-Step Template

Step 1: Search and Save

Search papers and save to JSON

paper-search search "your topic" --max 10 --json > /workspace/projects/papers.json echo "Step 1 complete: Found $(cat /workspace/projects/papers.json | python3 -c 'import json,sys; print(len(json.load(sys.stdin)))') papers"

Step 2: Extract Data to CSV

/home/user/.venv/bin/python3 << 'PYTHON' import json import pandas as pd

with open('/workspace/projects/papers.json') as f: papers = json.load(f)

data = [] for p in papers: data.append({ 'id': p['id'], 'title': p['title'][:80], 'authors': ', '.join(p['authors'][:3]), 'published': p['published'], 'categories': ', '.join(p['categories']) })

df = pd.DataFrame(data) df.to_csv('/workspace/output/papers.csv', index=False) print(f"Step 2 complete: Saved {len(df)} papers to CSV") PYTHON

Step 3: Visualize

/home/user/.venv/bin/python3 << 'PYTHON' import pandas as pd import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import seaborn as sns

df = pd.read_csv('/workspace/output/papers.csv')

fig, ax = plt.subplots(figsize=(10, 6))

Your visualization code here

plt.savefig('/workspace/output/analysis.png', dpi=150, bbox_inches='tight') print("Step 3 complete: Saved visualization") PYTHON

Step 4: Generate LaTeX

cat > /workspace/projects/survey.tex << 'LATEX' \documentclass{article} \usepackage{graphicx} \begin{document} \title{Survey Title} \maketitle % Content here \end{document} LATEX echo "Step 4 complete: Generated LaTeX"

Step 5: Compile PDF

cd /workspace/projects && pdflatex -interaction=nonstopmode survey.tex cp survey.pdf /workspace/output/ echo "Step 5 complete: PDF at /workspace/output/survey.pdf"

Progress Reporting

After each step, report:

• What was completed

• Output file locations

• What comes next

Example output:

✅ Step 1/5: Found 10 papers on VLA → /workspace/projects/papers.json

✅ Step 2/5: Extracted benchmark data → /workspace/output/benchmarks.csv

Continuing to Step 3: Visualization...

Common Workflows

Literature Survey

• Search papers (paper-search)

• Extract metadata to CSV

• Analyze trends (pandas)

• Create visualizations (seaborn)

• Write LaTeX survey

• Generate BibTeX

• Compile PDF

Benchmark Comparison

• Search papers with benchmark mentions

• Extract performance metrics

• Create comparison table

• Visualize results

• Write analysis

Replication Study

• Download paper PDF

• Extract methodology

• Implement code

• Run experiments

• Compare results

• Write report

Timeout Prevention

• Break tasks into 2-3 minute chunks

• Save intermediate results to files

• Use --json output for programmatic processing

• Avoid downloading large files mid-workflow

File Organization

/workspace/ ├── projects/ │ └── my-survey/ │ ├── papers.json # Raw search results │ ├── survey.tex # LaTeX source │ ├── references.bib # BibTeX │ └── figures/ # Generated plots └── output/ ├── survey.pdf # Final PDF ├── data.csv # Extracted data └── analysis.png # Visualizations