{"uid":"cap_iyhYvJEFN__yscSHyiGJq","slug":"json-outlier-detector-iqr-method-a03e3a69","name":"JSON Outlier Detector (IQR Method)","description":"Kostenlose Guides, Solo-Playbooks und Artikel zu KI, Automation und Side Hustles — für Menschen, die mit echten Systemen online Einkommen aufbauen wollen. Transparent finanziert über faire Affiliate-Links.","url":"https://kihustle.tech/agents/api/v1/json-outlier-detector-iqr","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"values":{"type":"array","items":{"type":"number"}}}},"responseSchema":{"type":"json","example":{"result":"processed","status":"success"}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.002","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":"$0.002/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_kBvRUaaQwgwhmHQ6KXUWr","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.002","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Detects statistical outliers in a numeric array using the interquartile range (IQR) method","exampleAgentPrompt":"Can you check this list of numbers for outliers using the IQR method? The values are [12, 14, 13, 15, 100, 11, 13, 200, 12, 14].","exampleUseCases":[{"title":"Sales data anomaly detection","prompt":"I have monthly sales figures — [1200, 1350, 1280, 1400, 9500, 1310, 1290] — can you check which ones are statistical outliers using IQR so I can flag them before reporting?"},{"title":"Sensor reading quality check","prompt":"Here are temperature sensor readings from my IoT device: [22.1, 22.4, 21.9, 22.3, 85.0, 22.0, 22.6, -40.5]. Can you run outlier detection on these to find any bad readings?"},{"title":"Exam score data cleanup","prompt":"I've got a set of student exam scores [55, 60, 58, 62, 57, 61, 3, 59, 99, 60] and I need to know which ones are outliers before I calculate the class average."}],"resultDescription":"Returns a JSON object indicating whether the request was processed successfully, along with outlier detection results identifying which values in the input array fall outside the IQR-defined bounds (typically Q1 - 1.5×IQR and Q3 + 1.5×IQR).","failureModes":["Empty or null values array returns an error or undefined behavior","Non-numeric elements in the array may cause processing failure","Array with fewer than 4 values may yield unreliable IQR calculation","Malformed JSON input returns a 400-level error","Service unavailability returns a 402 or 5xx response if payment or server issues occur"],"whenToPreferThis":"Choose this endpoint when you need a quick, stateless, pay-per-call outlier detection service using the well-established IQR (box plot) method on a flat numeric array. It is ideal for lightweight data cleaning pipelines, pre-processing steps before analytics, or ad-hoc anomaly checks where you do not need a full ML-based anomaly detection system. Prefer this over heavier statistical libraries when operating in an agent workflow that needs a simple, fast API call rather than embedded computation.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T00:58:29.689Z","isFirstParty":false}