Phildram1/myantfarm-ai

Multi-Agent LLM Orchestration for High-Quality Incident Response - 100% actionable recommendations vs 1.7% for single-agent

35
/ 100
Emerging

When critical IT incidents strike, getting actionable recommendations quickly is paramount. This project helps Site Reliability Engineers (SREs), DevOps teams, or IT Operations managers evaluate and implement multi-agent AI systems that process incident alerts and generate concrete, high-quality steps to resolve issues. It takes incident scenarios as input and produces a detailed list of actionable recommendations for resolution.

Use this if you are building or evaluating AIOps tools for incident response and need to benchmark the effectiveness of multi-agent LLM approaches for generating highly actionable remediation plans.

Not ideal if you are looking for a standalone incident response tool ready for production use, as this is an experimental framework for research and evaluation.

incident-response AIOps site-reliability-engineering IT-operations devops
No Package No Dependents
Maintenance 10 / 25
Adoption 4 / 25
Maturity 13 / 25
Community 8 / 25

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Stars

8

Forks

1

Language

TeX

License

MIT

Last pushed

Feb 04, 2026

Commits (30d)

0

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