What is multi-llm-agent-cli-poc?
68/100
Trust Score (C)
⚠️ Use Caution
multi-llm-agent-cli-poc is a coding that 一个利用Ollama API进行多大语言模型间协作对话的概念证明项目。. It has a Nerq Trust Score of 68/100 (C). 0 GitHub stars. Published by aoitan. Last analyzed September 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 1/100 — Maintenance activity is low
- ⚠️ Community: 0 stars, 0 downloads — Growing community
- ✅ Transparency: License: MIT — Clear licensing
Trust & Safety Overview
68
TRUST SCORE
C
GRADE
0
STARS
0
DOWNLOADS
What multi-llm-agent-cli-poc Does
multi-llm-agent-cli-poc is a agent in the coding category. 一个利用Ollama API进行多大语言模型间协作对话的概念证明项目。. It is published by aoitan and is open source. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.
Who Should Use multi-llm-agent-cli-poc
multi-llm-agent-cli-poc is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.
Details
| Author | aoitan |
|---|---|
| Category | coding |
| License | MIT |
| Type | agent |
| Source | View on GitHub |
| Security Score | 0/100 |
| Activity Score | 1/100 |
How to Get Started
Check the trust score before installing:
curl nerq.ai/v1/preflight?target=multi-llm-agent-cli-poc
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
| Tool | Trust | Stars |
|---|---|---|
| AutoGPT | 65 | 181.9K |
| ollama | 64 | 163.0K |
| langchain | 77 | 127.8K |
| system-prompts-and-models-of-ai-tools | 64 | 115.3K |
| opencode | 78 | 108.1K |
Frequently Asked Questions
What is multi-llm-agent-cli-poc used for?
multi-llm-agent-cli-poc is a coding tool. 一个利用Ollama API进行多大语言模型间协作对话的概念证明项目。.
Is multi-llm-agent-cli-poc free?
License: MIT. multi-llm-agent-cli-poc has 0 GitHub stars.
Is multi-llm-agent-cli-poc safe?
multi-llm-agent-cli-poc has a Nerq Trust Score of 68/100 (C). Use with caution.
What are alternatives to multi-llm-agent-cli-poc?
Top alternatives: AutoGPT, ollama, langchain. See full comparison.
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Last updated September 2026. Trust scores based on automated analysis of public data.