agentutility(7)$ man sentiment
/sentiment
NAME
sentiment — score how positive, negative, or mixed a piece of text reads, down to the emotion level
SYNOPSIS
POST https://x402.agentutility.ai/sentiment
Content-Type: application/json
X-PAYMENT: <signed-transferWithAuthorization>
{ ... }↳ first call →
402 Payment Required. Sign USDCtransferWithAuthorization, retry with theX-PAYMENT header.DESCRIPTION
Score how positive, negative, or mixed a piece of text reads, down to the emotion level. Send text with an optional aspects array (up to 15 specific things to evaluate separately, like "service" or "price"), and get back overall_sentiment, an overall_score from -1 to +1, a confidence value, a short summary, and a per-emotion breakdown covering joy, anger, sadness, fear, surprise, and disgust. When aspects are supplied, each one gets its own sentiment, score, and supporting quote. Use it as a sentiment analysis API, emotion detection tool, or review and support-ticket triage system for gauging customer feedback or social mentions at scale.
INPUT — request schema
| property | type | description | req? |
|---|---|---|---|
| text | string | Text to analyze. Max 12k chars. | required |
| aspects | array | Optional array of up to 15 aspect names to score individually alongside the overall sentiment. | optional |
OUTPUT — response shape
| field | type | description |
|---|---|---|
| overall_sentiment | string | Overall sentiment label for the input text, such as positive, negative, neutral, or mixed. |
| overall_score | number | Signed sentiment score from -1 (most negative) to +1 (most positive) for the full input. |
| confidence | number | Model confidence in the overall sentiment classification, from 0 to 1. |
| summary | string | Short natural-language summary of the sentiment and emotional tone detected in the text. |
| emotions | object | Per-emotion scores covering joy, anger, sadness, fear, surprise, and disgust (each 0..1). |
| aspects | object | Optional aspect-based breakdown mapping extracted aspects or topics to their own sentiment scores. |
| input_chars | number | Character count of the submitted text, used for size accounting. |
| model | string | Identifier of the underlying model that produced the sentiment and emotion analysis. |
EXAMPLES — two ways to call
EXAMPLE 1 · curl
curl -X POST https://x402.agentutility.ai/sentiment \
-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 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 | Rewrite AI-generated text so it reads like a person wrote it. | $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