{"uid":"cap_DZ_kPRQ0GI6kOCfcDEaTc","slug":"coordinate-quality-checks-numeric-distribution-adjacent-row-changes-6680e3a4","name":"Coordinate Quality Checks — Numeric Distribution + Adjacent Row Changes","description":"Coordinate quality checks — Numeric distribution + Adjacent row changes: Numeric distribution + Adjacent row changes for supplied coordinate quality checks records (checked_points, flagged_points). 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-23-077?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","checked_points","flagged_points"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"station_group":{"type":"string","default":"","maxLength":80},"checked_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"flagged_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","station_group":"group-a","checked_points":10,"flagged_points":1},{"date":"2026-10-02","row_id":"row-2","station_group":"group-b","checked_points":20,"flagged_points":2},{"date":"2026-10-03","row_id":"row-3","station_group":"group-a","checked_points":15,"flagged_points":3},{"date":"2026-10-04","row_id":"row-4","station_group":"group-b","checked_points":30,"flagged_points":4}],"maxItems":200,"minItems":1},"field":{"enum":["checked_points","flagged_points"],"type":"string","default":"checked_points"}}},"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_pdsy15_Kal9LJNdunuHrv","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 coordinate quality check records (checked_points, flagged_points) by producing two local analytical reports: numeric distribution statistics and adjacent row change analysis, for up to 200 rows.","exampleAgentPrompt":"Can you run a numeric distribution and adjacent row changes analysis on my coordinate quality check data? I have rows for station groups 'group-a' and 'group-b' from 2026-10-01 through 2026-10-04 with checked_points and flagged_points — analyze the checked_points field.","exampleUseCases":[{"title":"Weekly station quality drift detection","prompt":"I have 150 rows of daily coordinate quality checks across my weather stations from the past month. Can you analyze the checked_points field for its numeric distribution and also show me how the values change between adjacent rows, so I can spot any unusual shifts?"},{"title":"Flagged point anomaly review","prompt":"Run a distribution and adjacent-row-change report on my flagged_points data for these coordinate quality records — I want to see whether flagging counts are stable or spiking between consecutive dates across my station groups."},{"title":"QA audit on coordinate check batches","prompt":"I need to audit these 80 coordinate quality check records for station group 'north-cluster'. Give me the numeric distribution stats and row-to-row change breakdown for the checked_points field so I can confirm the data looks consistent."}],"resultDescription":"Two analytical reports: (1) a numeric distribution summary (e.g. min, max, mean, percentiles, histogram buckets) for the selected field across all supplied rows, and (2) an adjacent row changes report showing value differences between consecutive rows for the selected field — both computed locally without any external lookups or live data.","failureModes":["Fewer than 1 row supplied returns a validation error","More than 200 rows submitted exceeds the row limit and will be rejected","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Null values in checked_points or flagged_points may affect distribution completeness","Unknown field enum value (not 'checked_points' or 'flagged_points') causes rejection","Missing required fields (row_id, station_group, date) cause schema validation errors"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of coordinate quality check records and need both a numeric distribution summary and adjacent row change analysis in a single low-cost call ($0.01 USDC). It is ideal for offline/batch auditing of quality check data without needing live lookups, external APIs, or professional assessments. Prefer this over general analytics tools when the data fits the specific checked_points/flagged_points schema.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:37:57.448Z","isFirstParty":false,"canonicalSlug":"coordinate-quality-checks-numeric-distribution-adjacent-row-changes-6680e3a4"}