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Leads literature mining

Skill FridrichMethod/awesome-skills/skills/leads-literature-mining

Review AutomatorFrom its SKILL.md

Install
npx -y skills add FridrichMethod/awesome-skills --skill leads-literature-mining

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 13 stars13 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its file declares

Copied from the file, not written here

The file declares its own license as CC-BY-4.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.0 KB, 379 tokens by cl100k_base, as published. Nobody here has run it

<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA -->

LEADS (Literature Mining Agent)

A specialized LLM agent for automating systematic reviews and meta-analyses, capable of high-accuracy study selection and data extraction.

When to Use

  • Systematic Reviews: Screening thousands of abstracts for inclusion criteria.
  • Data Extraction: Pulling specific metrics (e.g., hazard ratios, sample sizes) from full-text PDFs.
  • Evidence Synthesis: Aggregating findings across multiple studies.

Core Capabilities

  1. Study Selection: Automated screening based on PICO criteria.
  2. Data Extraction: Structured extraction of study characteristics and results.
  3. Quality Assessment: Risk of bias evaluation.

Workflow

  1. Search: Query PubMed/Embase.
  2. Screen: Apply inclusion/exclusion criteria to abstracts.
  3. Extract: Parse full text for data points.
  4. Report: Generate PRISMA flow diagram and evidence table.

Example Usage

User: "Perform a systematic review on the efficacy of CAR-T in solid tumors."

Agent Action:

python -m leads.review --topic "CAR-T solid tumors" --criteria ./criteria.json
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.