{"uid":"cap_pbjfWI5lNudVTeyKylFyU","slug":"vextorium-text-similarity-102ee3e7","name":"Vextorium Text Similarity","description":"244 pay-per-call data APIs for AI agents: official statistics and economy (ECB, Fed, Eurostat, World Bank, SEC, BOE, INE), crypto prices and sentiment, Spanish public data, compliance (sanctions, VAT, IBAN, LEI), science, weather, web and developer tools and local AI text tools. Pay in USDC via x402.","url":"https://api.vextorium.com/v1/text-similarity?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"text_a":{"type":"string"},"text_b":{"type":"string"}}},"responseSchema":{"type":"json","example":{"verdict":"distintos","most_common":["pay","per"],"tfidf_cosine":0.2316,"words_in_common":3,"characters_jaccard":0.2609,"vocabulary_jaccard":0.3}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.003","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":"$0.003/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_QzoeRRVz8WJHG5tc7C6IE","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.003","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Computes multi-metric text similarity between two strings, returning TF-IDF cosine, Jaccard scores, common words, and a similarity verdict","exampleAgentPrompt":"Compare these two texts for similarity and tell me the cosine score, Jaccard overlap, and whether they're considered similar or different: text A is 'pay per call APIs for AI agents' and text B is 'per call payment APIs for developers'.","exampleUseCases":[{"title":"Duplicate content detection pipeline","prompt":"Check if these two product descriptions are basically the same thing: 'Wireless noise-cancelling headphones with 30-hour battery life and premium sound' vs 'Premium over-ear headphones featuring noise cancellation and 30 hours of playback' — give me the similarity scores and verdict."},{"title":"Plagiarism check on student essays","prompt":"I need to know how similar these two essay excerpts are — text A is 'The industrial revolution transformed society by shifting labor from farms to factories' and text B is 'Society was transformed during the industrial revolution as workers moved from agricultural to factory labor'. Show me the TF-IDF cosine, Jaccard, and whether they're flagged as similar."},{"title":"Search query relevance scoring","prompt":"Score the similarity between the search query 'best Italian restaurants in New York' and this document snippet 'Top-rated Italian dining spots across Manhattan and Brooklyn' — I want the cosine similarity, vocabulary Jaccard, and the verdict."}],"resultDescription":"Returns a JSON object with: a text verdict (e.g. 'similar' or 'distintos'), an array of the most common shared words, TF-IDF cosine similarity score (0–1), count of words in common, characters Jaccard similarity (0–1), and vocabulary Jaccard similarity (0–1).","failureModes":["Missing text_a or text_b fields returns a validation error","Empty strings may produce zero-score outputs with a dissimilar verdict","Very long texts may degrade performance or hit payload limits","Non-UTF-8 or malformed input may cause parsing errors"],"whenToPreferThis":"Choose this endpoint when you need multi-dimensional text similarity covering lexical overlap (Jaccard) and semantic frequency weighting (TF-IDF cosine) together in a single call, without standing up your own NLP infrastructure. It is especially useful for lightweight duplicate detection, content matching, or relevance scoring tasks where you need a fast, pay-per-call solution without managing embeddings or vector databases.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T18:45:15.068Z","isFirstParty":false,"canonicalSlug":"vextorium-text-similarity-102ee3e7"}