{"uid":"cap_9EDKDnr5XY_KWV07qqW9j","slug":"verdict-sentiment-analysis-b984bc37","name":"Verdict Sentiment Analysis","description":"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.","url":"https://verdict.kechlab.com/v1/sentiment?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"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\"]"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.0174","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.0174/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.0174","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.0174","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_9aBmP0tVLIWYMyIwvXkKH","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.0174","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"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.","exampleAgentPrompt":"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.","exampleUseCases":[{"title":"E-commerce review aspect scoring","prompt":"Analyze this product review and give me sentiment scores for price, quality, and delivery separately: 'Shipping was lightning fast and the build quality is excellent, but honestly I thought it was overpriced for what you get.' Also flag whether the opinion is mixed."},{"title":"Support ticket sentiment triage","prompt":"Can you score the sentiment of this incoming support ticket and break it out by support and product aspects? The message is: 'Your team was really helpful and friendly, but the software keeps crashing every morning.' I want to know the overall score, confidence, and whether the customer has conflicting feelings."},{"title":"Survey response ambiguity detection","prompt":"Run sentiment analysis on this survey response and tell me if it's too ambiguous to score confidently: 'It was okay I guess, some parts were good and some weren't really what I expected.' Break down price and experience as separate aspects if you can."}],"resultDescription":"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.","failureModes":["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"],"whenToPreferThis":"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.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T07:20:49.907Z","isFirstParty":false,"canonicalSlug":"verdict-sentiment-analysis-b984bc37"}