{"uid":"cap_qd8f_9ifaJXYXgtOvUo1_","slug":"pennyrail-number-stats-80b001d7","name":"PennyRail Number Stats","description":"Machine-readable settlement service","url":"https://pennyrail.vercel.app/api/f/number.stats","method":"POST","headers":{},"bodySchema":{"type":"object","required":["input"],"properties":{"input":{"type":"array","description":"number[]"}}},"responseSchema":{"type":"object","required":["operation","result"],"properties":{"result":{},"operation":{"type":"string"}},"additionalProperties":true},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.001","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":"$0.001/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_MezG6P6IWcgJo-CGDapYc","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.001","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Computes descriptive statistics (e.g. mean, median, min, max, std dev) over an array of numbers","exampleAgentPrompt":"Can you compute the descriptive statistics — mean, min, max, and standard deviation — for this list of numbers: [4, 7, 13, 2, 19, 8, 5]?","exampleUseCases":[{"title":"Summarize sensor reading dataset","prompt":"I have a batch of temperature sensor readings — [22.1, 23.4, 21.8, 24.0, 22.9] — can you give me the summary stats like mean, min, max, and std dev?"},{"title":"Quick stats check on survey scores","prompt":"I collected these NPS scores from our last survey: [8, 9, 7, 10, 6, 8, 9, 7]. What are the basic descriptive statistics for them?"},{"title":"Validate numeric distribution before ML training","prompt":"Before I feed this feature column into my model, can you calculate the mean and standard deviation for these values: [0.5, 1.2, 0.8, 1.5, 0.3, 1.1, 0.9]?"}],"resultDescription":"Returns a JSON object with an 'operation' string identifying the statistical operation performed and a 'result' field containing the computed value(s), such as mean, median, min, max, count, sum, or standard deviation. Additional fields may be present depending on the operation.","failureModes":["Empty input array returns an error or undefined result","Non-numeric values in the array cause a type error or malformed response","Missing 'input' field in request body returns a 400-level error","Very large arrays may time out or exceed payload limits","Payment failure (402) if USDC balance is insufficient"],"whenToPreferThis":"Choose this endpoint when you need fast, lightweight descriptive statistics on a numeric array without standing up your own computation infrastructure. It is ideal for agents that process small-to-medium numeric datasets on demand and want a pay-per-call model at $0.001 USDC, avoiding heavier analytics APIs or local code execution.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T18:46:15.791Z","isFirstParty":false}