Research Paper Extractor

Extract text from cardiology research paper PDFs - FREE, runs locally.

Cost: ZERO

• Text extraction: pdfplumber (free, local)
• Structuring: You ask me (Claude) in this conversation - you're already paying for the subscription

No API calls. No extra costs.

---

How It Works

STEP 1: Extract text (free, local)
python scripts/extract_paper.py trial.pdf --output trial.md

STEP 2: Ask Claude (your existing subscription)
"Read trial.md and structure this for my content workflow"

DONE - No extra cost.

---

Quick Start

Install (one time)

pip3 install pdfplumber

Extract text from PDF

# Save to file
python scripts/extract_paper.py paper.pdf --output extracted.md

# Just first 5 pages (faster)
python scripts/extract_paper.py paper.pdf --pages 5 --output extracted.md

Then ask Claude Code

After extracting, just tell me:

"Read /path/to/extracted.md and give me:

• Study design, population, intervention
• Primary/secondary endpoints with HR, CI, p-values
• Safety data and conclusions
• Content angles for YouTube, Twitter, Newsletter"

I'll structure it for your content workflow.

---

Example Workflow

# 1. Download PDF from NEJM/JACC/Lancet

# 2. Extract text
python scripts/extract_paper.py ~/Downloads/declare-timi-58.pdf --output declare.md

# 3. In Claude Code:
#    "Read declare.md and structure the trial data.
#     Give me content angles for my YouTube channel."

Output you'll get from me:

DECLARE-TIMI 58 Summary:

Study: RCT, N=17,160, T2DM with CV risk
Intervention: Dapagliflozin 10mg vs placebo
Duration: 4.2 years median follow-up

Primary (MACE): HR 0.93 (0.84-1.03), p=0.17 - Non-inferior, not superior
Key Secondary (CV death/HF hosp): HR 0.83 (0.73-0.95), p=0.005 ✓

Content Angles:
🎬 YouTube: "SGLT2 inhibitors: The HF story hidden in a 'negative' trial"
🐦 Twitter: "DECLARE: Primary endpoint NS, but NNT 111 for HF hosp. Bury the lede much?"
📧 Newsletter: "Why 'negative' trials often have positive stories"

---

Why This Approach?

Approach	Cost
❌ Anthropic API per extraction	~$0.05-0.15 per paper
❌ OpenAI API per extraction	~$0.05-0.20 per paper
✅ This approach	$0 - uses your subscription

You're already paying for Claude Code. Use it.

---

Integration with Your Skills

After I structure the data, you can use it with:

• cardiology-trial-editorial → Write 500-word editorial
• x-post-creator-skill → Generate tweets with accurate stats
• youtube-script-master → Script with verified data
• cardiology-newsletter-writer → Deep dive newsletter

---

Limitations

• Works best with native PDFs (not scanned images)
• Very long papers: use --pages 10 to extract key sections
• Tables may need manual review

---

Zero cost. Maximum utility. Uses what you already pay for.