pharmaclaw-literature-agent

name

pharmaclaw-literature-agent

description

Literature mining agent v2.0.0 for novel drug discovery: PubMed/Semantic Scholar + ClinicalTrials Phase II/III + bioRxiv preprints. Novelty scoring, phase/FDA query boosts. Best for latest breakthroughs. Searches PubMed (NCBI E-utilities) and Semantic Scholar for papers related to compounds, targets, diseases, mechanisms, reactions, and catalysts. Returns structured results with titles, authors, abstracts, DOIs, MeSH terms, citation counts, TLDR summaries, and open-access PDFs. Supports paper lookup by DOI/PMID, citation tracking, and related paper discovery. Chains from any PharmaClaw agent (compound name, target, disease) and recommends next agents based on findings. No API keys required. Triggers on literature, papers, publications, PubMed, search papers, citations, references, what's published, research on, studies about, review articles, recent papers, state of the art.

Literature Agent v1.0.0

Overview

Dual-source literature search combining PubMed (biomedical focus) and Semantic Scholar (broader CS/ML/AI coverage). Deduplicates across sources, enriches with citation metrics and TLDR summaries.

Key capabilities:

• PubMed search with MeSH terms, abstracts, publication types
• Semantic Scholar search with citation counts, influential citations, TLDR
• Paper lookup by DOI or PMID
• Citation tracking (who cited this paper?)
• Related paper discovery (what did this paper reference?)
• Automatic query construction from compound/target/disease inputs
• Cross-source deduplication and enrichment

Quick Start

# Search by topic
python scripts/pubmed_search.py --query "KRAS G12C inhibitor" --max-results 5

# Search Semantic Scholar (includes ML/AI papers)
python scripts/semantic_scholar.py --query "graph neural network drug discovery"


python scripts/chain_entry.py --input-json 


python scripts/semantic_scholar.py --paper-id  --citations


python scripts/pubmed_search.py --query  --years 3