name: leads-literature-mining description: Review Automator keywords: - literature-mining - systematic-review - meta-analysis - pubmed - evidence-synthesis measurable_outcome: Complete a systematic review screen of 100+ papers with >90% inclusion/exclusion accuracy compared to human baseline. license: CC-BY-4.0 metadata: author: Nature Communications 2025 version: "1.0.0" compatibility: - system: Python 3.9+ allowed-tools: - run_shell_command - web_fetch
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
- Study Selection: Automated screening based on PICO criteria.
- Data Extraction: Structured extraction of study characteristics and results.
- Quality Assessment: Risk of bias evaluation.
Workflow
- Search: Query PubMed/Embase.
- Screen: Apply inclusion/exclusion criteria to abstracts.
- Extract: Parse full text for data points.
- 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