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: COPYRIGHT NOTICE4---56<!--
7# COPYRIGHT NOTICE
8# This file is part of the "Universal Biomedical Skills" project.
9# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>
10# All Rights Reserved.
11#
12# This code is proprietary and confidential.
13# Unauthorized copying of this file, via any medium is strictly prohibited.
14#
15# Provenance: Authenticated by MD BABU MIA
1617-->
1819---
20name: deep-research-swarm
21description: Multi-agent research literature analysis
22keywords:
23 - research
24 - literature
25 - swarm
26 - multi-agent
27 - hypothesis
28measurable_outcome: Generates comprehensive literature review with >50 citations in <5 minutes.
29license: MIT
30metadata:
31 author: Biomedical OS Team
32 version: "1.0.0"
33compatibility:
34 - system: Python 3.10+
35allowed-tools:
36 - run_shell_command
37 - read_file
38 - google_web_search
39---
4041# DeepResearch Swarm
4243A coordinated swarm of agents designed to perform deep, parallelized research into biomedical literature, aggregating findings into comprehensive reports.
4445## When to Use This Skill
4647* When you need an exhaustive review of a specific medical topic.
48* When connecting disparate pieces of evidence across thousands of papers.
49* When generating hypotheses based on recent literature.
5051## Core Capabilities
52531. **Parallel Search**: Querying multiple databases simultaneously.
542. **Evidence Synthesis**: Combining facts into a coherent narrative.
553. **Citation Verification**: Ensuring all claims are backed by sources.
5657## Example Usage
5859**User**: "Research the latest advancements in mRNA cancer vaccines."
6061**Agent Action**:
62```bash
63python3 src/research/agents/agent_coordinator.py --topic "mRNA cancer vaccines" --depth "deep"
64```
656667<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->
Run npx skillmds@latest add beita6969/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.
COPYRIGHT NOTICE It is listed under Research & Search on SkillMD.
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beita6969 (@beita6969) published this skill. Their other Agent Skills are listed on their SkillMD profile.
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