{"uid":"cap_WPnrDnrgSSKLELHHZhQzM","slug":"delx-numeric-outlier-scan-b3bc9607","name":"Delx Numeric Outlier Scan","description":"Identify statistical outlier indexes in bounded numeric samples. Use it as a bounded preflight or analysis step inside an enterprise agent workflow before data, policy, integration, security, or commercial decisions reach production. Returns deterministic machine-readable JSON for $0.003 USDC via x402 on Base. Execution is first-party, local-only, stateless, memory-only, and has no paid upstream or input retention. Results are advisory; the caller remains responsible for authorization and produ…","url":"https://api.delx.ai/api/v1/x402/numeric-outlier-scan","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"values":{"type":"array","description":"Input field: values."},"z_threshold":{"type":"number","description":"Input field: z_threshold."}}},"responseSchema":{"type":"json","example":{"mean":48.6,"count":5,"schema":"delx/util-numeric-outlier-scan/v1","z_threshold":2,"outlier_count":0,"outlier_indexes":[],"standard_deviation":75.703633}},"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_5iWqgcivqBn-PAkop-Gdf","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":"Identifies statistical outlier indexes in a bounded numeric array using z-score thresholding, returning machine-readable JSON results.","exampleAgentPrompt":"Scan this list of numbers for statistical outliers using a z-score threshold of 2.5: [12, 13, 11, 14, 98, 12, 13, 10, 11, 200] — tell me which indexes are anomalous.","exampleUseCases":[{"title":"Preflight sensor data before alerting","prompt":"Before firing any alerts, scan these temperature sensor readings for outliers with a z-threshold of 3.0: [72, 71, 73, 70, 74, 210, 72, 71] — flag any suspicious indexes so I can ignore bad readings."},{"title":"Clean financial data before modeling","prompt":"I have this list of transaction amounts and need to catch any outliers before feeding them into my risk model — run an outlier scan with z-threshold 2.0 on [450, 470, 460, 455, 3200, 462, 448]."},{"title":"Validate user input scores before aggregation","prompt":"Check these user-submitted quality scores for statistical outliers before I average them — use a z-threshold of 2.5 on [8, 7, 9, 8, 7, 10, 8, 1, 9, 8] and tell me which indexes to exclude."}],"resultDescription":"Returns deterministic machine-readable JSON indicating which indexes in the input array are statistical outliers based on the specified z-score threshold, along with supporting z-score values for each element.","failureModes":["Empty or null values array returns an error or empty results","z_threshold not provided may default to a standard value or return a validation error","Non-numeric values in the array cause a type error","Array with fewer than 3 elements may produce unreliable z-score statistics","Payment failure via x402 returns 402 status and no result"],"whenToPreferThis":"Choose this endpoint when you need a fast, stateless, deterministic outlier detection step on a bounded numeric array as part of an automated agent workflow — especially as a preflight check before downstream data, policy, or commercial decisions. It is ideal when you want a simple z-score-based approach without spinning up a data science stack, and when reproducibility and machine-readable JSON output matter. Prefer it over general-purpose analytics APIs when cost predictability ($0.003 per call) and stateless execution with no data retention are requirements.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T12:40:46.549Z","isFirstParty":false}