What is agentfield-hackathon?
53/100
Trust Score (D)
⚠️ Use Caution
agentfield-hackathon is a finance that Trading bot for financial markets.. It has a Nerq Trust Score of 53/100 (D). 0 GitHub stars. Published by jason-hum. Last analyzed October 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: Not specified — No license specified
Trust & Safety Overview
53
TRUST SCORE
D
GRADE
0
STARS
0
DOWNLOADS
What agentfield-hackathon Does
agentfield-hackathon is a agent in the finance category. Trading bot for financial markets.. It is published by jason-hum and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.
Who Should Use agentfield-hackathon
agentfield-hackathon is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.
Details
| Author | jason-hum |
|---|---|
| Category | finance |
| License | Not specified |
| 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=agentfield-hackathon
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
| Tool | Trust | Stars |
|---|---|---|
| OpenBB | 69 | 61.0K |
| qlib | 82 | 37.6K |
| TradingAgents | 78 | 30.3K |
| TradingAgents-CN | 73 | 17.2K |
| dexter | 64 | 16.4K |
Frequently Asked Questions
What is agentfield-hackathon used for?
agentfield-hackathon is a finance tool. Trading bot for financial markets..
Is agentfield-hackathon free?
License: Check project page. agentfield-hackathon has 0 GitHub stars.
Is agentfield-hackathon safe?
agentfield-hackathon has a Nerq Trust Score of 53/100 (D). Use with caution.
What are alternatives to agentfield-hackathon?
Top alternatives: OpenBB, qlib, TradingAgents. See full comparison.
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Last updated October 2026. Trust scores based on automated analysis of public data.