Agentic Synthesis of Open-Source Biomedical Repositories and Clinical Literature into Interactive Diagnostic & Medical Learning Tools for Low-Resource Healthcare Settings

Frontline community health workers (CHWs) and rural clinics in low-resource settings—particularly across underserved municipalities in South Asia and rural regions of the United States—face a severe clinical knowledge bottleneck. While peer-reviewed biomedical literature, genomic variant databases, and open-source clinical calculators expand exponentially, these resources remain fragmented across unstructured texts and incompatible software repositories that require high-bandwidth connectivity and specialized bioinformatics literacy. This research protocol introduces **`gwf-clinical-synthesis`**, a non-commercial, computational dry-lab framework developed at GoWithFund Inc. Leveraging long-context multi-agent reasoning in **Google Antigravity** powered by **Gemini 4 Argon** (1M-token unified context window) and the **Google DeepMind (GDM) Science Skills** ecosystem, our pipeline orchestrates parallel literature retrieval across PubMed/NCBI Entrez, OpenAlex, ClinVar, and ChEMBL, fuses fragmented open-source clinical simulation repositories into lightweight offline-capable web applications, and executes automated multi-agent citation-verification loops to eliminate large language model (LLM) hallucinations. Concurrently, we integrate geospatial and socio-economic vulnerability indicators via AlphaEarth Foundations to model optimal healthcare resource allocation across high-burden districts. All resulting datasets, verification benchmarks, and interactive medical learning modules are released open-source under Apache 2.0 and CC BY 4.0 licenses.