{"uid":"cap_M-lqanSCvwt7HJmRfjoQV","slug":"kihustle-mad-outlier-clip-statistical-outlier-detection-07adcd1b","name":"KiHustle Mad Outlier Clip — Statistical Outlier Detection","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/bot-bazaar/api/v1/json-mad-outlier-clip?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"k":{"type":"number"},"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_igA7lsP01NLeHYrdU0SpL","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":"Identifies outlier values from a numeric array using a parameterized threshold k, returning a processed result indicating which values deviate significantly from the dataset.","exampleAgentPrompt":"Can you run outlier detection on this array [12, 14, 13, 200, 11, 15, 9] with a threshold k of 3 and tell me which values are flagged as outliers?","exampleUseCases":[{"title":"Flag anomalous sensor readings","prompt":"I have temperature sensor readings [22.1, 21.8, 22.3, 98.7, 21.9, 22.0] and I want to find any outliers using a k threshold of 2.5 — which values are abnormal?"},{"title":"Clean financial data before modeling","prompt":"Before I run my regression model, can you detect outliers in this revenue dataset [1050, 1100, 980, 1070, 15000, 1020] using a k value of 3 so I can exclude the weird ones?"},{"title":"Quality control on survey scores","prompt":"I have a set of survey scores [7, 8, 6, 9, 7, 8, 1, 8, 7] — run outlier detection with k equal to 2 and tell me which responses look suspicious."}],"resultDescription":"Returns a JSON object with a 'result' field (e.g. 'processed') and a 'status' field indicating success. The actual outlier information is embedded in the processed result, though the exact format of flagged values is not fully documented.","failureModes":["Missing or non-numeric values array causes invalid input error","k parameter not provided or set to zero may produce undefined behavior","Empty array input may return an error or trivial result","Malformed JSON body returns 400 or similar error","Very large arrays may time out or be truncated"],"whenToPreferThis":"Choose this endpoint when you need a lightweight, pay-per-call outlier detection computation on a numeric array with a configurable sensitivity parameter k, especially in automated pipelines where spinning up a local stats library is impractical. It is less appropriate when you need detailed per-element outlier scores, visualization, or access to the underlying statistical method used.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-14T00:36:57.272Z","isFirstParty":false,"canonicalSlug":"kihustle-mad-outlier-clip-statistical-outlier-detection-07adcd1b"}