{"uid":"cap_dKx5gFVTTxrQ4v6eC2SEO","slug":"one-engine-linear-scale-t5-6f189c22","name":"ONE Engine Linear Scale (T5)","description":"Low-cost pay-per-call utility APIs for autonomous agents using x402 on Base.","url":"https://one-search.one-engine.workers.dev/v3/numeric/linear-scale/t5?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","required":["values"],"properties":{"max":{"type":"number"},"min":{"type":"number"},"size":{"type":"integer"},"digits":{"type":"integer"},"factor":{"type":"number"},"offset":{"type":"number"},"values":{"type":"array","description":"Finite numbers, maximum 1000"}}},"responseSchema":{"type":"object","additionalProperties":true},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.0025","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":"$0.0025/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.0025","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.0025","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_iPcWZhOucb56C-1fgpMmT","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.0025","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Linearly rescales an array of numeric values to a target range, with optional rounding, offset, and factor controls.","exampleAgentPrompt":"Scale these numbers [12, 45, 7, 98, 33] to a range of 0 to 100, rounded to 2 decimal places.","exampleUseCases":[{"title":"Normalize ML features before training","prompt":"I have a list of raw feature values [0.5, 120, 3.7, 88, 14] that need to be normalized between 0 and 1 with 4 decimal places — can you rescale them for me?"},{"title":"Rescale survey scores for display","prompt":"Take these survey response scores [1, 3, 2, 5, 4, 3, 1] and map them onto a 0 to 100 scale rounded to whole numbers so I can show them in a bar chart."},{"title":"Apply linear offset and factor to sensor data","prompt":"I've got sensor readings [10, 20, 30, 40, 50] and need to apply a scale factor of 1.5 and an offset of -5 to each, keeping 3 digits of precision — can you run that transformation?"}],"resultDescription":"A JSON object containing the rescaled numeric values array, transformed according to the specified min/max bounds, optional factor, offset, and digit rounding. The output array maps the input values linearly into the target range.","failureModes":["Input array exceeds 1000 elements — request rejected","Non-finite numbers (NaN, Infinity) in the values array cause errors","Invalid min/max range (min >= max) may produce undefined scaling behavior","Missing required 'values' field returns a validation error","Payment failure via x402 prevents execution"],"whenToPreferThis":"Choose this endpoint when you need a simple, fast, pay-per-call linear scaling of a numeric array without setting up your own math infrastructure. Ideal for agents doing on-the-fly normalization of ML features, sensor data, or display values where a local computation would add complexity. Best for arrays up to 1000 elements needing min/max normalization with optional rounding.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-02T12:44:04.587Z","isFirstParty":false,"canonicalSlug":"one-engine-linear-scale-t5-6f189c22"}