{"uid":"cap_Tdp9qzoEVUfxP3j_1DvU1","slug":"numora-outlier-detection-api-7fd5a327","name":"Numora Outlier Detection API","description":"100 pure math computation endpoints for AI agents. Statistics, financial math, linear algebra, equation solving, calculus, number theory, sequence generation, and unit conversions. Zero external dependencies. x402 micropayments on Base.","url":"https://numomo.vercel.app/api/statistics/outlier","method":"POST","headers":{},"bodySchema":{"type":"object","required":["data"],"properties":{"data":{"type":"array"},"method":{"type":"string"}}},"responseSchema":{"type":"object","required":["success","result","computation"],"properties":{"result":{"type":"object","description":"Computation result varies by endpoint"},"success":{"type":"boolean","description":"Always true on success"},"computation":{"type":"string","description":"Human-readable description of what was computed"}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.1","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"registry","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":"$0.1/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_EyH1lfRj2xUPqC2rdCiPc","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.1","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Detects statistical outliers in a numeric dataset using configurable methods, returning flagged values and their positions.","exampleAgentPrompt":"I have a list of measurements — [12, 14, 13, 15, 100, 12, 14, 11, 13] — can you detect any statistical outliers in that data using the IQR method?","exampleUseCases":[{"title":"Quality control in manufacturing data","prompt":"I have a batch of sensor readings from our production line: [102, 98, 101, 99, 250, 100, 103, 97, 101]. Can you find the outliers so I know which readings to flag for review?"},{"title":"Cleaning student test score data","prompt":"Here are student exam scores: [78, 82, 80, 79, 3, 81, 77, 83, 80, 79]. Can you detect the statistical outliers in this list so I can identify data entry errors?"},{"title":"Financial anomaly detection","prompt":"I have daily transaction amounts for the past two weeks: [500, 520, 510, 505, 4800, 515, 498, 507, 512, 503, 495, 518, 509, 501]. Please detect any outlier transactions using the IQR method."}],"resultDescription":"Returns a JSON object with a 'success' boolean, a 'result' object containing identified outlier values and their indices within the input array, and a 'computation' string describing what was computed in human-readable form.","failureModes":["Empty data array returns an error or empty result","Non-numeric values in the array may cause computation failure","Unrecognized 'method' string may fall back to default or return an error","Datasets that are too small (e.g. fewer than 4 values) may not support meaningful outlier detection","Payment failure via x402 will block the request entirely"],"whenToPreferThis":"Choose this endpoint when you need a fast, serverless, zero-dependency outlier detection computation on a numeric array and want a simple POST interface with micropayment access. Ideal for agents that need on-demand statistical anomaly detection without setting up a data science environment or calling a heavier analytics platform. Prefer it over general-purpose Python execution when you want a deterministic, pre-built statistical computation with predictable cost per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T18:47:05.957Z","isFirstParty":false}