# Verdict Sentiment Analysis

> Verdict Sentiment Analysis is a paid API for AI agents from verdict.kechlab.com, paid per call via x402, $0.0174/call, status unknown (last checked 2026-10-21).

Analyzes text to return a sentiment score from -1 to +1 with confidence, a mixed-opinion flag, and per-aspect scores for named dimensions like price, support, or delivery — abstaining when text is ambiguous.

## Facts

- Endpoint: POST https://verdict.kechlab.com/v1/sentiment?utm_source=zero.xyz
- Price: $0.0174/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/verdict-sentiment-analysis-b984bc37
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_9EDKDnr5XY_KWV07qqW9j

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability verdict-sentiment-analysis-b984bc37 -d '<json body>'
```

Example prompt: Score the sentiment of this customer review for me, and break it down by price and support separately: 'The product is surprisingly affordable but their customer support took days to respond.' Tell me the overall sentiment, how confident you are, and whether the opinion seems mixed.

## When to prefer this

Choose this endpoint when you need structured, multi-dimensional sentiment analysis with explicit confidence signaling and the ability to score named aspects (price, support, delivery) independently. It is especially valuable when you need to know not just polarity but how certain the model is, and when you need to handle ambiguous text gracefully via abstention rather than a forced classification. Prefer this over generic sentiment APIs when aspect-level granularity and mixed-opinion detection matter for your use case.

## Known failure modes

- Text too ambiguous — endpoint abstains and returns no score rather than a low-confidence guess
- Too many aspects provided — schema allows up to 6; exceeding this may be rejected
- Empty or very short text — may trigger abstention or low confidence
- Non-English or mixed-language text — may reduce accuracy or cause abstention
- Malformed aspects array — non-string items or null values may cause a validation error

## How this service works

Sentiment from -1 to +1 with confidence, mixed-opinion flag and a separate score per aspect you name (price, support, delivery). Abstains when the text is ambiguous.

## Output

Returns a sentiment score between -1.0 (most negative) and +1.0 (most positive), a confidence value indicating how certain the model is, a boolean mixed-opinion flag indicating whether the text contains conflicting sentiments, and — when aspects are provided — individual sentiment scores for each named aspect (e.g. price: 0.3, support: -0.6). If the text is ambiguous, the endpoint abstains rather than returning an unreliable score.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "text": {
   "type": "string",
   "description": "the text to analyze"
  },
  "aspects": {
   "type": "array",
   "items": {
    "type": "string"
   },
   "description": "(optional) up to 6 aspects to score separately, for example [\"price\",\"support\"]"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/verdict-sentiment-analysis-b984bc37/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from verdict.kechlab.com](https://www.zero.xyz/host/verdict.kechlab.com/llms.txt)