{"uid":"cap_FyR5f9k7vjXSzI15iR6_Z","slug":"fittings-text-similarity-f2e4ee7d","name":"fittings Text Similarity","description":"Similarity of two records from 0 to 1: Jaro-Winkler, token-sorted and Levenshtein ratios, and the strongest of the three as the headline score.","url":"https://fittings.sh/v1/text/similarity?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"a":{"type":"string","description":"Up to 512 characters"},"b":{"type":"string","description":"Up to 512 characters"},"threshold":{"type":"number","description":"Match cutoff from 0 to 1. Default 0.85."}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.004052","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":"$0.004052/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.004052","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.004052","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_4Z45-nrPR_lhlRcrss_0F","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.004052","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Computes Jaro-Winkler, token-sorted, and Levenshtein similarity ratios between two text strings, returning all three scores plus the strongest as the headline match score.","exampleAgentPrompt":"How similar are the strings 'Jonathan Smith' and 'Jon Smyth'? Give me the Jaro-Winkler, token-sorted, and Levenshtein scores, and flag it as a match if the headline score is above 0.85.","exampleUseCases":[{"title":"Customer record deduplication","prompt":"I have two customer entries — 'Acme Corp. LLC' and 'ACME Corporation' — can you check how similar they are using all three fuzzy match algorithms and tell me the strongest score so I can decide whether to merge them?"},{"title":"Address typo detection","prompt":"Someone submitted '123 Elm Streeet, Springfield' but our database has '123 Elm Street, Springfield' — how similar are these two strings? Use a match threshold of 0.9 so I know if it's close enough to accept."},{"title":"Drug name variant matching","prompt":"Check if 'acetaminophen' and 'Acetaminofen' are similar enough to be the same drug — give me all three similarity scores and the headline match score."}],"resultDescription":"Returns a JSON object containing three similarity scores (Jaro-Winkler ratio, token-sorted ratio, and Levenshtein ratio), each as a float between 0 and 1, plus a headline score representing the strongest of the three. Optionally includes a boolean match result if a threshold was supplied.","failureModes":["Input string exceeds 512 characters — request rejected","Missing required field 'a' or 'b' — validation error returned","Threshold outside 0–1 range — bad request error","Non-string input for 'a' or 'b' — type error"],"whenToPreferThis":"Choose this endpoint when you need multi-algorithm fuzzy string similarity in a single call — especially when Jaro-Winkler alone is insufficient for token-order-variant inputs (e.g. 'Smith, John' vs 'John Smith'), or when you want to pick the strongest of three algorithms without running them separately. Prefer over single-metric APIs when robustness across different string variation types matters.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T06:47:19.961Z","isFirstParty":false,"canonicalSlug":"fittings-text-similarity-f2e4ee7d"}