{"uid":"cap_L92BEwK32wceKzw4E1OTQ","slug":"rainfall-observations-duplicate-key-report-numeric-row-ordering-783187a7","name":"Rainfall Observations — Duplicate Key Report + Numeric Row Ordering","description":"Rainfall observations — Duplicate key report + Numeric row ordering: Duplicate key report + Numeric row ordering for supplied rainfall observations records (rainfall_mm, duration_hours). 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-02-058?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","rainfall_mm","duration_hours"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"rainfall_mm":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80},"duration_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","rainfall_mm":10,"station_group":"group-a","duration_hours":1},{"date":"2026-10-02","row_id":"row-2","rainfall_mm":20,"station_group":"group-b","duration_hours":2},{"date":"2026-10-03","row_id":"row-3","rainfall_mm":15,"station_group":"group-a","duration_hours":3},{"date":"2026-10-04","row_id":"row-4","rainfall_mm":30,"station_group":"group-b","duration_hours":4}],"maxItems":200,"minItems":1},"field":{"enum":["rainfall_mm","duration_hours"],"type":"string","default":"rainfall_mm"}}},"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_7Td9X55l7lg4VYIRL8fFE","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":"Analyzes supplied rainfall observation records to identify duplicate keys and produce a numerically ordered ranking of rows by a chosen field (rainfall_mm or duration_hours), returning two reports for up to 200 rows.","exampleAgentPrompt":"Can you check my rainfall observation records for duplicate row IDs and also sort them by rainfall_mm? Here are the rows: row-1, station-group-A, 2026-10-01, 12.5mm, 2 hours; row-2, station-group-B, 2026-10-02, 8.0mm, 1 hour; row-1, station-group-A, 2026-10-01, 12.5mm, 2 hours — that last one might be a duplicate.","exampleUseCases":[{"title":"Audit rain gauge data for duplicates","prompt":"I have a batch of 50 rainfall observation records from our monitoring network — can you run a duplicate key check on them to flag any rows that share the same row_id, and also rank all the rows by rainfall_mm so I can see which stations recorded the most rain?"},{"title":"Rank weather station readings by duration","prompt":"I've collected hourly rainfall logs from several station groups over the past month. Can you order all these rows numerically by duration_hours and also tell me if any row IDs are repeated in the dataset?"},{"title":"Pre-import data quality check for hydrology pipeline","prompt":"Before I import these 120 rainfall records into our database, can you check them for duplicate keys and give me a numeric ordering by rainfall_mm so I can spot anomalies? I'll paste the rows with their row_id, station_group, date, rainfall_mm, and duration_hours fields."}],"resultDescription":"Returns two structured reports: (1) a duplicate key report identifying any rows with repeated identifiers across the supplied dataset, and (2) a numeric row ordering ranking all supplied rows by the chosen field (rainfall_mm or duration_hours), covering up to 200 input rows.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, rainfall_mm, duration_hours) cause validation errors","Invalid date format (not YYYY-MM-DD) causes schema rejection","Null values in the selected numeric field may affect ordering output","Empty rows array (minItems:1 not met) causes rejection"],"whenToPreferThis":"Choose this endpoint when you need offline, deterministic data-quality analysis on rainfall observation records — specifically a duplicate key check and a numeric field sort — without any live weather lookup, prediction, or external data enrichment. Best suited for pre-import audits, data pipeline validation, or batch QA on station-group rainfall logs of up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:39:03.685Z","isFirstParty":false,"canonicalSlug":"rainfall-observations-duplicate-key-report-numeric-row-ordering-783187a7"}