Multi-Agent-RAG-Template: This template demonstrates how to create a collaborative team of AI agents that work together to process

by The-Swarm-Corporation · Agent Tool · ★ 60

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install Multi-Agent-RAG-Template

git clone https://github.com/The-Swarm-Corporation/Multi-Agent-RAG-Template.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 73/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

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Quick Facts

Stars60
Forks11
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score73/100
Open Issues2
Last Updated2025-01-13
Created2024-11-11
Platformspython
Est. Tokens~3k

About Multi-Agent-RAG-Template

Multi-Agent-RAG-Template A production-ready template for building Multi-Agent RAG (Retrieval-Augmented Generation) systems using the Swarms Framework. This template demonstrates how to create a collaborative team of AI agents that wo

Compatible Skills

These tools work well together with Multi-Agent-RAG-Template for enhanced workflows:

  • Agent-Wiz — semantic(0.15)+complementary+rare_topics+same_lang+similar_pop+shared_platform (59%)
  • agentops — semantic(0.21)+complementary+rare_topics+same_lang+shared_platform (51%)
  • oreilly-ai-agents — semantic(0.19)+complementary+rare_topics+similar_pop (46%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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