Evaluating Paper Relevance

What problem does it solve?

Sifting through vast search results to find papers that contain specific data or methods is a time-consuming and often imprecise task. This skill automates a two-stage screening process to efficiently identify and extract critical information, ensuring you get exactly what you need.

Core Features & Use Cases

• Two-Stage Screening: Quickly scores abstracts for initial relevance, then performs a deep dive into full text for promising papers.
• Integrated Access: Automatically checks ChEMBL for curated data and uses Unpaywall to find free versions of paywalled papers.
• Structured Extraction: Extracts specific data (measurements, protocols, datasets) and organizes findings in SUMMARY.md.
• Use Case: After a literature search, ask Claude to "evaluate these 50 papers for IC50 data." This skill will systematically screen each paper, fetch full text (even from paywalls), extract the specific data you need, and organize it in your research summary.

Quick Start

Example: Evaluate a list of papers for specific data

"Evaluate these papers for IC50 values: PMID1, PMID2, PMID3."