name: deep-research-swarm
description: Multi-agent research literature analysis
keywords:
- research
- literature
- swarm
- multi-agent
- hypothesis
measurable_outcome: Generates comprehensive literature review with >50 citations in <5 minutes.
license: MIT
metadata:
author: Biomedical OS Team
version: "1.0.0"
compatibility:
- system: Python 3.10+
allowed-tools:
- run_shell_command
- read_file
- google_web_search
DeepResearch Swarm
A coordinated swarm of agents designed to perform deep, parallelized research into biomedical literature, aggregating findings into comprehensive reports.
When to Use This Skill
When you need an exhaustive review of a specific medical topic.
When connecting disparate pieces of evidence across thousands of papers.
When generating hypotheses based on recent literature.
Evidence Synthesis: Combining facts into a coherent narrative.
Citation Verification: Ensuring all claims are backed by sources.
Example Usage
User: "Research the latest advancements in mRNA cancer vaccines."
Agent Action:
python3 src/research/agents/agent_coordinator.py --topic "mRNA cancer vaccines" --depth "deep"
1---2name: deep-research-swarm3description: <!--4---5<!--6# COPYRIGHT NOTICE7# This file is part of the "Universal Biomedical Skills" project.8# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>9# All Rights Reserved.10#11# This code is proprietary and confidential.12# Unauthorized copying of this file, via any medium is strictly prohibited.13#14# Provenance: Authenticated by MD BABU MIA1516-->1718---19name: deep-research-swarm20description: Multi-agent research literature analysis21keywords:22 - research23 - literature24 - swarm25 - multi-agent26 - hypothesis27measurable_outcome: Generates comprehensive literature review with >50 citations in <5 minutes.28license: MIT29metadata:30 author: Biomedical OS Team31 version: "1.0.0"32compatibility:33 - system: Python 3.10+34allowed-tools:35 - run_shell_command36 - read_file37 - google_web_search38---3940# DeepResearch Swarm4142A coordinated swarm of agents designed to perform deep, parallelized research into biomedical literature, aggregating findings into comprehensive reports.4344## When to Use This Skill4546* When you need an exhaustive review of a specific medical topic.47* When connecting disparate pieces of evidence across thousands of papers.48* When generating hypotheses based on recent literature.4950## Core Capabilities51521. **Parallel Search**: Querying multiple databases simultaneously.532. **Evidence Synthesis**: Combining facts into a coherent narrative.543. **Citation Verification**: Ensuring all claims are backed by sources.5556## Example Usage5758**User**: "Research the latest advancements in mRNA cancer vaccines."5960**Agent Action**:61```bash62python3 src/research/agents/agent_coordinator.py --topic "mRNA cancer vaccines" --depth "deep"63```646566<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->
Run npx skillmds@latest add biotender-max/deep-research-swarm in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.
<!-- It is listed under Research & Search on SkillMD.
This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.
This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.
Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.
BioTender-max (@biotender-max) published this skill. Their other Agent Skills are listed on their SkillMD profile.
BioTender-max