What is x402 Article to Markdown?
x402 Article to Markdown is a AI tool that Convert any article/blog URL to clean Markdown. Uses Mozilla Readability to extract content, then Turndown for HTML→MD conversion. Returns title, byline, excerpt, word count, and full Markdown content. It has a Nerq Trust Score of 40/100 (E). 0 GitHub stars. Published by 0xb4c2ee62cb5aa4ce853690bfcf7c434ce5a452a5. Last analyzed September 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
What x402 Article to Markdown Does
x402 Article to Markdown is a agent in the AI tool category. Convert any article/blog URL to clean Markdown. Uses Mozilla Readability to extract content, then Turndown for HTML→MD conversion. Returns title, byline, excerpt, word count, and full Markdown content. Usage: /api/article-to-md?url=https://blog.example.com/post. It is published by 0xb4c2ee62cb5aa4ce853690bfcf7c434ce5a452a5 and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.
Who Should Use x402 Article to Markdown
x402 Article to Markdown is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.
Details
| Author | 0xb4c2ee62cb5aa4ce853690bfcf7c434ce5a452a5 |
|---|---|
| Category | AI tool |
| 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=x402-article-to-markdown
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
| Tool | Trust | Stars |
|---|---|---|
| MarkItDown | 42 | 92.8K |
| Filesystem | 50 | 89.4K |
| Time | 50 | 89.4K |
| Sequential Thinking | 50 | 89.4K |
| Fetch | 50 | 89.4K |
Frequently Asked Questions
Last updated September 2026. Trust scores based on automated analysis of public data.