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AmanChain Sentiment Analysis
x402
AmanChain Sentiment Analysis is a paid API for AI agents from preview-chat-701ec510-82d7-4ee3-ae9d-8fdb8c4f421b.space-z.ai, paid per call via x402, $0.00311/call, status unknown (last checked 2026-09-15).
Analyzes any input text for sentiment (positive/negative/neutral), polarity score, and detected emotions
Price / call$0.00311
Success—
StatusUnknown
How this service works
Sentiment Analysis: sentiment, polarity score and emotions for any text Executed deterministically by the AmanChain node against live consensus state (real blocks, pools, balances) — paid per call via x402, settled in USDC on Base. Input: JSON body {"serviceId":"aman-sentiment","request":"<input>"}. No account, no API key.
Output
Returns a sentiment label (positive, negative, or neutral), a numeric polarity score indicating sentiment strength and direction, and a set of detected emotions (e.g. joy, anger, sadness, fear, surprise) present in the input text.
Example use cases
Customer review sentiment triage
“Analyze the sentiment of this customer review and tell me the polarity score and emotions: 'I've been using this app for a month and it crashes every other day — completely unreliable.'”
Social media brand monitoring
“Check the sentiment and emotions in this tweet about our brand: 'Just tried @BrandX's new coffee blend and honestly it's the best thing I've tasted all year! #obsessed'”
Support ticket emotion detection
“What's the emotional tone and sentiment of this support message — is the customer angry, frustrated, or neutral? Text: 'This is the third time I've contacted support about the same issue and nothing has been fixed.'”
Technical details
Endpoint
POSThttps://preview-chat-701ec510-82d7-4ee3-ae9d-8fdb8c4f421b.space-z.ai/api/x402/aman-sentimentWhen to prefer
Choose this endpoint when you need a quick, pay-per-call sentiment and emotion analysis without managing API keys or subscriptions. It is well-suited for agents processing individual text items in real time and requiring both a polarity score and emotion labels in a single call. Prefer alternatives if you need batch processing at high volume or require fine-tuned domain-specific sentiment models.
Side effects
- Empty or missing 'request' field returns an error or empty result
- Extremely short or ambiguous text may yield low-confidence or neutral scores
- Non-English text may produce less accurate sentiment and emotion detection
- Malformed JSON body returns a parse error
- Payment failure via x402 results in a 402 response and no analysis
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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