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x402.slinkylayer.ai Entity Sentiment Analysis
x402
x402.slinkylayer.ai Entity Sentiment Analysis is a paid API for AI agents from x402.slinkylayer.ai, paid per call via x402, $0.05/call, status unknown (last checked 2026-10-11).
Analyzes sentiment expressed about specific named entities within a provided text using Google's NLP provider
Price / call$0.05
Success—
StatusUnknown
How this service works
Accepts JSON input and analyzes the sentiment expressed about entities within the provided text using Google as the provider.
Output
Returns a structured JSON response containing a list of entities detected in the text, each with their entity type (person, organization, location, etc.), a sentiment score (ranging from -1.0 very negative to 1.0 very positive), and a magnitude value indicating the strength of the sentiment. May also include salience scores indicating how prominent each entity is in the document.
Example use cases
Brand reputation monitoring from reviews
“Analyze this product review for entity-level sentiment and tell me how customers feel about each brand or product mentioned: 'Samsung's camera was outstanding but the battery life disappointed, while Google Photos made everything seamless.'”
News article entity sentiment extraction
“Break down the sentiment expressed about each named organization in this news paragraph: 'Tesla surged ahead in EV sales while Ford struggled with supply chain issues and GM remained cautiously optimistic.'”
Social media mention analysis
“Tell me how positive or negative the sentiment is toward each person or company mentioned in this tweet: 'Loving what Elon is doing with SpaceX but really disappointed in how Twitter has been managed lately.'”
Technical details
Endpoint
POSThttps://x402.slinkylayer.ai/api/v1/proxy/:id/entity-sentiment?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need sentiment broken down per named entity rather than a single document-level sentiment score. It is ideal for competitive analysis, brand monitoring, review mining, or news parsing where multiple entities appear and you need to know how each one is perceived individually. Prefer this over general sentiment endpoints when entity attribution matters, and over keyword extraction endpoints when emotional tone is the goal.
Side effects
- Empty or missing text body returns 400 Bad Request
- Text exceeding provider character limits may return 413 or truncation error
- Non-JSON content-type headers cause parsing failures
- Proxy ID (:id) not found or unauthorized returns 404 or 403
- Google NLP API downstream outage returns 502 or 503
- Insufficient USDC balance or failed x402 payment returns 402 Payment Required
- Text with no recognizable named entities returns empty entity list
Tags
x402
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