{"uid":"cap_1GlA6ge_3WAq9T34EmsIl","slug":"equipment-runtime-secondary-measure-weighted-mean-88b861c8","name":"Equipment Runtime Secondary-Measure Weighted Mean","description":"Equipment runtime - Secondary-measure weighted mean: Secondary-measure weighted mean for Equipment runtime. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded secondary-measure weighted mean deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-analytics-equipment-runtime-weighted-average?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","machine","date","run_hours","downtime_hours"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"machine":{"type":"string","default":"","maxLength":80},"run_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"downtime_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","machine":"group-a","run_hours":10,"downtime_hours":1},{"date":"2026-10-02","row_id":"row-2","machine":"group-b","run_hours":20,"downtime_hours":2},{"date":"2026-10-03","row_id":"row-3","machine":"group-a","run_hours":15,"downtime_hours":3},{"date":"2026-10-04","row_id":"row-4","machine":"group-b","run_hours":30,"downtime_hours":4}],"maxItems":200,"minItems":1},"field":{"enum":["run_hours","downtime_hours"],"type":"string","default":"run_hours"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","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":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_YrDOab9xMSRFMd2-9T395","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Computes a secondary-measure weighted mean of equipment runtime data (run_hours or downtime_hours) across up to 200 typed records using local numeric processing.","exampleAgentPrompt":"Calculate the secondary-measure weighted mean for these 4 equipment records — machine group-a ran 10 hours with 1 downtime hour on 2026-10-01, group-b ran 20 hours with 2 downtime hours on 2026-10-02, group-a ran 15 hours with 3 downtime hours on 2026-10-03, and group-b ran 30 hours with 4 downtime hours on 2026-10-04 — and use run_hours as the target field.","exampleUseCases":[{"title":"Fleet runtime utilization summary","prompt":"I have runtime logs for 50 machines over the past month — each row has a machine ID, date, run_hours, and downtime_hours. Compute the secondary-measure weighted mean of run_hours weighted by downtime_hours so I can benchmark fleet utilization."},{"title":"Downtime-weighted production analysis","prompt":"Take these 120 daily records for our production line machines and calculate the weighted mean of downtime_hours using the secondary-measure weighting — I want to understand average downtime adjusted for machine activity levels."},{"title":"Equipment maintenance planning metric","prompt":"I need a secondary-measure weighted mean of run_hours for these 80 equipment entries (each has a machine name, date, run_hours, and downtime_hours) to feed into our maintenance scheduling model — can you compute that for me?"}],"resultDescription":"Returns a single secondary-measure weighted mean value computed from up to 200 equipment runtime records, with the target field (run_hours or downtime_hours) weighted by the complementary secondary measure. Includes data quality indicators and bounded numeric output derived entirely from local processing.","failureModes":["Missing required fields (row_id, machine, date, run_hours, or downtime_hours) causes validation failure","Supplying more than 200 rows exceeds the maxItems limit and will be rejected","Invalid date format (not YYYY-MM-DD) triggers a pattern validation error","Null values for both run_hours and downtime_hours on a record may produce undefined weighting behavior","Invalid field enum value (not 'run_hours' or 'downtime_hours') causes input rejection","Empty rows array (minItems: 1 not met) returns a validation error"],"whenToPreferThis":"Choose this endpoint when you need a statistically sound weighted mean of equipment runtime or downtime hours using a secondary measure as the weight, for up to 200 records, with no need for external enrichment or forecasting. Prefer it over simple arithmetic mean calculations when the relative magnitude of the secondary field should influence the aggregate result. It is well-suited for fleet-level operational analytics and maintenance planning pipelines where local, deterministic numeric processing is sufficient.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:47:12.418Z","isFirstParty":false,"canonicalSlug":"equipment-runtime-secondary-measure-weighted-mean-88b861c8"}