agentutility(7)$ man sentiment-analysis
/sentiment-analysis
NAME
sentiment-analysis — analyzes sentiment in arbitrary text, returning overall sentiment, a score (-1 to +1), per-emotion labels (joy/anger/sadness/fear/surpris…
SYNOPSIS
POST https://x402.agentutility.ai/sentiment-analysis
Content-Type: application/json
X-PAYMENT: <signed-transferWithAuthorization>
{ ... }↳ first call →
402 Payment Required. Sign USDCtransferWithAuthorization, retry with theX-PAYMENT header.DESCRIPTION
Analyzes sentiment in arbitrary text, returning overall sentiment, a score (-1 to +1), per-emotion labels (joy/anger/sadness/fear/surprise/disgust), and optional aspect-based scoring. A text-only analysis endpoint for product reviews, tickets, comments, and support logs. Use it as a sentiment analyzer, text sentiment classifier, emotion classifier, or aspect-based sentiment API.
INPUT — request schema
| property | type | description | req? |
|---|---|---|---|
| text | string | — | required |
| aspects | array | — | optional |
OUTPUT — response shape
| field | type | description |
|---|---|---|
| overall_sentiment | string | Overall sentiment label such as positive, negative, neutral, or mixed. |
| overall_score | number | Overall sentiment score from -1 (most negative) to +1 (most positive). |
| confidence | number | Confidence in the overall sentiment classification, from 0 to 1. |
| summary | string | Short natural-language summary of the sentiment and key emotional tone in the text. |
| emotions | object | Per-emotion scores for joy, anger, sadness, fear, surprise, and disgust. |
| aspects | object | Aspect-based sentiment scores, mapping each detected aspect or topic to its sentiment. |
| input_chars | number | Character count of the input text that was analyzed. |
| model | string | Model identifier used to produce the sentiment and emotion classification. |
EXAMPLES — two ways to call
EXAMPLE 1 · curl
curl -X POST https://x402.agentutility.ai/sentiment-analysis \
-H 'Content-Type: application/json' \
-d '{ }'first response =
402 Payment Required with payment requirements; sign + retry with X-PAYMENT.EXAMPLE 2 · mcp
# Install the MCP package for this endpoint's cluster npx -y @agentutility/mcp-<cluster> # Required: EVM private key with USDC on Base export X402_PRIVATE_KEY=0x... # Then call the sentiment-analysis tool from your MCP-aware agent.
MCP server handles payment automatically — your coding agent just calls the tool by name.
METADATA
- tags
- sentimentemotionnlpai
- env
- VENICE_API_KEY
- methods
- POST
- cluster
- wordmint
- price
- $0.01 USDC per call
ADJACENT — other endpoints in wordmint
| endpoint | description | price |
|---|---|---|
| ai-to-human-text | AI text humanizer / GPT detector bypass. | $0.01 |
| app-review-sentiment | Scores app-store reviews by onboarding, stability, pricing, performance, and feature requests. | $0.01 |
| brand-bootstrap | Bootstraps a brand kit for a new business or product in one call. | $0.01 |
| brand-launch-brief | Generates a structured brand launch brief for a new company or product from name, concept, audience, and tone. | $0.01 |
| brand-positioning-brief | Generates a brand positioning brief covering messaging pillars, taglines, launch channels, and a logo prompt. | $0.01 |
| brand-sentiment-analysis | Scores comments, mentions, survey verbatims, and campaign feedback for sentiment. | $0.01 |
| candidate-feedback-sentiment | Summarizes candidate experience, recruiter feedback, and hiring-process comments by sentiment. | $0.01 |
| churn-risk-sentiment | Analyzes support tickets, chats, and emails for negative sentiment, urgency, and at-risk churn themes. | $0.01 |
SEE ALSO