{"uid":"cap_32sHrmQkFzMaP_TKlT2-E","slug":"manylives-me-text-sentiment-analysis-0447f8bf","name":"manylives.me Text Sentiment Analysis","description":"Sentiment of a text: positive, negative, neutral or mixed, a score from -1 to 1, the emotions present and a one-line reason.","url":"https://manylives.me/paid/text/sentiment?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"text":{"type":"string","examples":["The delivery was fast and the result was exactly what we needed. Great service!"],"description":"the text (required, max 20,000 chars)"}}},"responseSchema":{"type":"json","example":{"score":0.7,"reason":"…","emotions":["joy"],"sentiment":"positive"}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","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":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_oQRCxr-ujGNIS2vDs0--i","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","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 label (positive/negative/neutral/mixed), a numeric score from -1 to 1, detected emotions, and a one-line reason.","exampleAgentPrompt":"Can you analyze the sentiment of this customer review: 'The delivery was fast and the result was exactly what we needed. Great service!' — I want to know if it's positive, negative, neutral, or mixed, get a score from -1 to 1, see what emotions are in it, and get a one-line reason.","exampleUseCases":[{"title":"Customer review sentiment scoring","prompt":"Analyze the sentiment of this product review: 'The packaging was nice but the item broke after two days, very disappointed.' Tell me if it's positive, negative, neutral, or mixed, give me a score, and list the emotions."},{"title":"Social media tone monitoring","prompt":"What's the sentiment of this tweet: 'Just tried the new menu at my favorite spot and honestly blown away — best meal I've had all year!'? Give me a score, the label, and whatever emotions you detect."},{"title":"Support ticket triage by tone","prompt":"Classify the tone of this support message: 'I've been waiting three weeks for a response and nobody has helped me. This is completely unacceptable.' Is it positive, negative, neutral, or mixed? Include the score and a reason."}],"resultDescription":"A JSON object containing: a 'sentiment' field (one of positive, negative, neutral, or mixed), a 'score' float from -1.0 (most negative) to 1.0 (most positive), an 'emotions' array listing detected emotions (e.g. joy, anger, frustration), and a 'reason' string with a one-line explanation of the classification.","failureModes":["Text exceeds 20,000 character limit — request rejected","Empty or missing 'text' field — validation error","Payment not provided or insufficient — HTTP 402 returned","Network timeout for very long texts near the character limit","Ambiguous or multilingual text may produce lower-confidence mixed results"],"whenToPreferThis":"Choose this endpoint when you need a structured sentiment breakdown — label, numeric score, emotion tags, and a human-readable reason — in a single call. Ideal for agent pipelines processing user feedback, reviews, or messages where both classification and emotional nuance matter. At $0.01 per call it suits moderate-volume workloads. Prefer this over generic LLM prompting when you want a consistent, schema-stable sentiment output without prompt engineering.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-13T00:40:38.924Z","isFirstParty":false,"canonicalSlug":"manylives-me-text-sentiment-analysis-0447f8bf"}