{"uid":"cap_QsKCoisnUKMt-QPD1Dgct","slug":"reservoir-observations-string-normalisation-secondary-measure-91538bea","name":"Reservoir Observations — String Normalisation + Secondary-Measure Weighted Mean","description":"Reservoir observations — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied reservoir observations records (stored_m3, capacity_m3). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-weather-19-034?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","stored_m3","capacity_m3"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"stored_m3":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"capacity_m3":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","stored_m3":10,"capacity_m3":1,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","stored_m3":20,"capacity_m3":2,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","stored_m3":15,"capacity_m3":3,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","stored_m3":30,"capacity_m3":4,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["stored_m3","capacity_m3"],"type":"string","default":"stored_m3"}}},"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_q4pGcsvSu5pdVE0DUWcZc","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":"Normalises station/group strings and computes a capacity_m3-weighted mean of stored_m3 (or vice versa) across up to 200 reservoir observation rows.","exampleAgentPrompt":"I have a set of reservoir observation records with stored_m3 and capacity_m3 values across several station groups — can you normalise the station group strings and compute a capacity-weighted mean of stored_m3 for me? I'll send up to 50 rows with fields like row_id, date, station_group, stored_m3, and capacity_m3.","exampleUseCases":[{"title":"Water utility monthly storage summary","prompt":"I have 120 daily reservoir readings from three station groups with stored_m3 and capacity_m3 columns — please normalise the station group labels and give me a capacity-weighted mean of stored_m3 so I can summarise monthly storage levels."},{"title":"Environmental audit of reservoir fill rates","prompt":"Can you clean up the station_group strings in my 80-row reservoir dataset and calculate a weighted mean of stored_m3 using capacity_m3 as the weight? I need this for an environmental audit report across sites."},{"title":"Irrigation planning data quality check","prompt":"I've got reservoir observation data for 4 groups over the past quarter — about 90 rows — and the station names are messy. Normalise the strings and compute the capacity-weighted average stored volume so I can plan irrigation allocations."}],"resultDescription":"Returns two analytical reports: (1) a string normalisation report cleaning the station_group field values, and (2) a secondary-measure weighted mean report computing the weighted average of the selected field (e.g. stored_m3) using the other measure (e.g. capacity_m3) as the weight, across the supplied rows grouped by station_group.","failureModes":["Missing required fields (row_id, station_group, date, stored_m3, capacity_m3) cause validation errors","Submitting more than 200 rows triggers a payload size rejection","Null values in both stored_m3 and capacity_m3 for a row may cause incomplete weighted mean output","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you have reservoir observation data (stored volume and capacity in cubic metres) and need both string normalisation on categorical fields and a secondary-measure weighted mean computed locally — without any external lookup, prediction, or live data fetch. Ideal for batch analytical pipelines on up to 200 rows where reproducibility and low cost matter.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:38:47.068Z","isFirstParty":false,"canonicalSlug":"reservoir-observations-string-normalisation-secondary-measure-91538bea"}