Best use case
deep-research-swarm is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
COPYRIGHT NOTICE
Teams using deep-research-swarm should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/deep-research-swarm/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How deep-research-swarm Compares
| Feature / Agent | deep-research-swarm | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
COPYRIGHT NOTICE
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA --> --- 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. ## Core Capabilities 1. **Parallel Search**: Querying multiple databases simultaneously. 2. **Evidence Synthesis**: Combining facts into a coherent narrative. 3. **Citation Verification**: Ensuring all claims are backed by sources. ## Example Usage **User**: "Research the latest advancements in mRNA cancer vaccines." **Agent Action**: ```bash python3 src/research/agents/agent_coordinator.py --topic "mRNA cancer vaccines" --depth "deep" ``` <!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->
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