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:

python -m leads.review --topic "CAR-T solid tumors" --criteria ./criteria.json