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content.hugen.tokyo Content Analyzer
x402
content.hugen.tokyo Content Analyzer is a paid API for AI agents from content.hugen.tokyo, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-15).
Performs comprehensive AI content analysis on a URL, returning sentiment score, topic classification, named entity extraction, content type detection, and credibility assessment.
Price / call$0.02
Success—
StatusUnknown
How this service works
Comprehensive AI content analysis — sentiment scoring (-1.0 to 1.0), topic classification, named entity extraction, content type detection (news/blog/docs/tutorial), and credibility assessment. Returns structured analysis ready for immediate use. No LLM integration needed. Accepts USDC payments on Base and Solana
Output
Returns a structured analysis object including: a sentiment score between -1.0 (most negative) and 1.0 (most positive), topic classification labels, named entities (people, organizations, locations, products, events), content type detection (news, blog, documentation, tutorial), and a credibility assessment score — all ready for immediate downstream use without additional LLM processing.
Example use cases
Example prompt
“Can you fully analyze this article for me — https://example.com/article — I want to know its sentiment score, what type of content it is (news, blog, tutorial, etc.), the main topics, any named entities like people or organizations, and how credible it seems?”
Technical details
Endpoint
GEThttps://content.hugen.tokyo/content/analyzeWhen to prefer
Choose this endpoint when you need a multi-dimensional content analysis in a single call — specifically when you need sentiment, topic, entities, content type, and credibility all at once without setting up your own LLM pipeline or prompt engineering. Ideal for content moderation pipelines, news feed analysis, research aggregation, or any workflow that needs to quickly classify and evaluate web content at scale. Prefer this over general-purpose LLM calls when you want structured, consistently formatted output at low cost ($0.02/call).
Side effects
- URL is inaccessible or returns non-200 status — analysis cannot be performed
- URL points to non-text content (e.g. PDF, image) — extraction may fail or return empty results
- Page content is too short or lacks meaningful text — low-confidence or empty analysis returned
- Payment not included or invalid — 402 Payment Required response
- Rate limit exceeded — too many requests in a short period
Input
{
"url": "https://www.wikipedia.org/wiki/Artificial_intelligence",
"strip_query": false
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | — |
Output
{
"url": "https://en.wikipedia.org/wiki/Artificial_intelligence",
"topics": [
"artificial-intelligence",
"machine-learning",
"deep-learning",
"generative-ai",
"computer-science"
],
"summary": "Artificial intelligence (AI) is the capability of machines to perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving. The field, founded in 1956, has evolved through cycles of optimism and funding shifts, with significant acceleration in recent years due to advances in deep learning and generative AI. AI research encompasses various subfields like natural language processing, perception, and planning, utilizing diverse techniques such as neural networks and probabilistic methods, with applications ranging from search engines to autonomous vehicles.",
"entities": [
{
"name": "OpenAI",
"type": "org"
},
{
"name": "Google DeepMind",
"type": "org"
},
{
"name": "Meta",
"type": "org"
},
{
"name": "ChatGPT",
"type": "product"
},
{
"name": "Claude",
"type": "product"
},
{
"name": "Gemini",
"type": "product"
},
{
"name": "Copilot",
"type": "product"
},
{
"name": "Meta AI",
"type": "product"
},
{
"name": "Nvidia",
"type": "org"
},
{
"name": "Gordon Moore",
"type": "person"
},
{
"name": "Jensen Huang",
"type": "person"
},
{
"name": "Google",
"type": "org"
},
{
"name": "Netflix",
"type": "org"
},
{
"name": "YouTube",
"type": "org"
},
{
"name": "Amazon",
"type": "org"
},
{
"name": "Facebook",
"type": "org"
},
{
"name": "Siri",
"type": "product"
},
{
"name": "Alexa",
"type": "product"
},
{
"name": "Microsoft",
"type": "org"
},
{
"name": "Apple",
"type": "org"
},
{
"name": "TikTok",
"type": "org"
},
{
"name": "AlphaFold 2",
"type": "product"
},
{
"name": "Alan Turing",
"type": "person"
},
{
"name": "Noam Chomsky",
"type": "person"
},
{
"name": "Margaret Masterman",
"type": "person"
},
{
"name": "Ray Solomonoff",
"type": "person"
},
{
"name": "Ilya Sutskever",
"type": "person"
},
{
"name": "Stephen W. Smoliar",
"type": "person"
},
{
"name": "HongJiang Zhang",
"type": "person"
},
{
"name": "Jon Stewart",
"type": "person"
},
{
"name": "Geoffrey Hinton",
"type": "person"
},
{
"name": "Jianhua Tao",
"type": "person"
},
{
"name": "Tieniu Tan",
"type": "person"
},
{
"name": "Josh Taylor",
"type": "person"
},
{
"name": "Alex Hern",
"type": "person"
},
{
"name": "Derek Thompson",
"type": "person"
},
{
"name": "Ellen Thro",
"type": "person"
},
{
"name": "Rob Toews",
"type": "person"
},
{
"name": "Fabio Urbina",
"type": "person"
},
{
"name": "Filippa Lentzos",
"type": "person"
},
{
"name": "Cédric Invernizzi",
"type": "person"
},
{
"name": "Sean Ekins",
"type": "person"
},
{
"name": "Christ Valance",
"type": "person"
},
{
"name": "Jordan Valinsky",
"type": "person"
},
{
"name": "Yugesh Verma",
"type": "person"
},
{
"name": "James Vincent",
"type": "person"
},
{
"name": "Vernor Vinge",
"type": "person"
},
{
"name": "Kaveh Waddell",
"type": "person"
},
{
"name": "Wendell Wallach",
"type": "person"
},
{
"name": "P. C. Wason",
"type": "person"
},
{
"name": "D. Shapiro",
"type": "person"
},
{
"name": "J. Weng",
"type": "person"
},
{
"name": "McClelland",
"type": "person"
},
{
"name": "A. Pentland",
"type": "person"
},
{
"name": "O. Sporns",
"type": "person"
},
{
"name": "I. Stockman",
"type": "person"
},
{
"name": "M. Sur",
"type": "person"
},
{
"name": "E. Thelen",
"type": "person"
},
{
"name": "Scientific American",
"type": "org"
},
{
"name": "Rhiannon Williams",
"type": "person"
},
{
"name": "Bernd W. Wirtz",
"type": "person"
},
{
"name": "Jan C. Weyerer",
"type": "person"
},
{
"name": "Carolin Geyer",
"type": "person"
},
{
"name": "Matteo Wong",
"type": "person"
},
{
"name": "E. Yudkowsky",
"type": "person"
},
{
"name": "Larry Hauser",
"type": "person"
},
{
"name": "James Fieser",
"type": "person"
},
{
"name": "Bradley Dowden",
"type": "person"
}
],
"language": "en",
"sentiment": {
"label": "neutral",
"score": 0
},
"key_points": [
"AI enables computational systems to perform tasks associated with human intelligence, including learning, reasoning, and perception.",
"The field of AI research has experienced significant growth, particularly since 2012 with the advent of deep learning and further acceleration in the 2020s due to generative AI.",
"Key subfields of AI include reasoning, knowledge representation, planning, learning, natural language processing, and perception.",
"Diverse techniques are employed in AI, such as artificial neural networks, probabilistic methods, logic, and search algorithms.",
"AI has a wide range of applications, from advanced search engines and virtual assistants to autonomous vehicles and drug discovery."
],
"word_count": 27340,
"content_type": "docs",
"credibility_signals": {
"has_date": false,
"has_author": false,
"has_sources": true,
"word_count_adequate": true
}
}Tags
x402
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