What is ip-composition-adapter?
57/100
Trust Score (D)
⚠️ Use Caution
ip-composition-adapter is a AI tool that ostris/ip-composition-adapter. It has a Nerq Trust Score of 57/100 (D). 179 GitHub stars. Published by ostris. Last analyzed July 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 0/100 — Maintenance activity is low
- ⚠️ Community: 179 stars, 0 downloads — Growing community
- ⚠️ Transparency: License: Not specified — No license specified
Trust & Safety Overview
57
TRUST SCORE
D
GRADE
179
STARS
0
DOWNLOADS
What ip-composition-adapter Does
ip-composition-adapter is a model in the AI tool category. ostris/ip-composition-adapter. It is published by ostris and has no specified license. With 179 GitHub stars and 0 downloads, it has a growing community of users and contributors.
Who Should Use ip-composition-adapter
ip-composition-adapter is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.
Details
| Author | ostris |
|---|---|
| Category | AI tool |
| License | Not specified |
| Type | model |
| 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=ip-composition-adapter
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
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|---|---|---|
| openclaw | 59 | 218.2K |
| tensorflow | 57 | 193.9K |
| AutoGPT | 62 | 181.9K |
| ollama | 56 | 163.0K |
| stable-diffusion-webui | 62 | 160.7K |
Frequently Asked Questions
What is ip-composition-adapter used for?
ip-composition-adapter is a AI tool tool. ostris/ip-composition-adapter.
Is ip-composition-adapter free?
License: Check project page. ip-composition-adapter has 179 GitHub stars.
Is ip-composition-adapter safe?
ip-composition-adapter has a Nerq Trust Score of 57/100 (D). Use with caution.
What are alternatives to ip-composition-adapter?
Top alternatives: openclaw, tensorflow, AutoGPT. See full comparison.
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Last updated July 2026. Trust scores based on automated analysis of public data.