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GG402 Sentiment Analysis
x402
GG402 Sentiment Analysis is a paid API for AI agents from gg402.vercel.app, paid per call via x402, $0.010000/call, status unknown (last checked 2026-09-15).
Analyzes the sentiment of a given text string, returning a numeric score, sentiment label, and natural language explanation.
Price / call$0.010000
Success—
StatusUnknown
How this service works
Real-time sentiment analysis of text, news, and social media to gauge market and community sentiment.
Output
Returns the original text, the model used (gpt-4o-mini), a numeric sentiment score (0–1 scale), a sentiment label (e.g. 'positive', 'negative', 'neutral'), and a plain-English explanation of why the text received that sentiment rating.
Example use cases
Example prompt
“Can you analyze the sentiment of this text and give me a score and explanation: 'The Fed's latest rate decision rattled investors, with markets closing sharply lower amid widespread uncertainty about future policy direction.'”
Technical details
Endpoint
POSThttps://gg402.vercel.app/sentimentWhen to prefer
Choose this endpoint when you need a fast, affordable ($0.01 USDC), single-call sentiment classification with a human-readable explanation — especially for financial text, news snippets, or social media content. Prefer it over heavyweight NLP pipelines when simplicity and speed matter more than batch throughput or fine-grained emotion categories.
Side effects
- Missing 'text' field returns a validation error
- Empty string input may return an undefined or neutral result
- Extremely long text may be truncated or cause a timeout
- Non-English text may produce less accurate sentiment classification
- Ambiguous or sarcastic text may result in incorrect sentiment labeling
Input
{
"text": "The new product launch exceeded expectations with strong customer feedback and positive market reception."
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| textrequired | string |
Output
{
"text": "The new product launch exceeded expectations with strong customer feedback and positive market reception.",
"model": "gpt-4o-mini",
"score": 0.9,
"sentiment": "positive",
"explanation": "The text expresses enthusiasm and satisfaction regarding the new product launch, highlighting strong customer feedback and positive market reception, which indicates a favorable outcome."
}Schema · Response
| Field | Type | Description |
|---|---|---|
| textrequired | string | |
| modelrequired | string | |
| scorerequired | number | |
| sentimentrequired | string | |
| explanationrequired | string |
Tags
x402
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