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