What is POCO LEE?
39/100
Trust Score (E)
🔴 Avoid
POCO LEE is a community that An AI agent. It has a Nerq Trust Score of 39/100 (E). 0 GitHub stars. Published by 6253fc073b577ecadee1494fb94202d0ef41add41db00dd3. Last analyzed November 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 0/100 — Maintenance activity is low
- ⚠️ Community: 0 stars, 0 downloads — Growing community
- ⚠️ Transparency: License: Not specified — No license specified
Trust & Safety Overview
39
TRUST SCORE
E
GRADE
0
STARS
0
DOWNLOADS
What POCO LEE Does
POCO LEE is a agent in the community category. An AI agent. It is published by 6253fc073b577ecadee1494fb94202d0ef41add41db00dd3 and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.
Who Should Use POCO LEE
POCO LEE is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.
Details
| Author | 6253fc073b577ecadee1494fb94202d0ef41add41db00dd3 |
|---|---|
| Category | community |
| License | Not specified |
| Type | agent |
| Source | View on GitHub |
| Security Score | 0/100 |
| Activity Score | 0/100 |
How to Get Started
Check the trust score before installing:
curl nerq.ai/v1/preflight?target=poco-lee
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
| Tool | Trust | Stars |
|---|---|---|
| Pillow Night Coordinator | 68 | 0 |
| CalHacks Fetch Merch | 67 | 0 |
| CalHacks Hacker Personality | 67 | 0 |
| CalHacks AI Investor | 67 | 0 |
| ASI-Kagaz | 68 | 0 |
Frequently Asked Questions
What is POCO LEE used for?
POCO LEE is a community tool. An AI agent.
Is POCO LEE free?
License: Check project page. POCO LEE has 0 GitHub stars.
Is POCO LEE safe?
POCO LEE has a Nerq Trust Score of 39/100 (E). Evaluate carefully.
What are alternatives to POCO LEE?
Top alternatives: Pillow Night Coordinator, CalHacks Fetch Merch, CalHacks Hacker Personality. See full comparison.
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Last updated November 2026. Trust scores based on automated analysis of public data.