{"uid":"cap_f6xCqsm0pSA94VETKLhsp","slug":"coordinate-quality-checks-numeric-interval-filter-adjacent-row-changes-4472421d","name":"Coordinate Quality Checks — Numeric Interval Filter + Adjacent Row Changes","description":"Coordinate quality checks — Numeric interval filter + Adjacent row changes: Numeric interval filter + 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-23-127?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_J-Ng1pl2OkvQREpZ5-X-p","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":"Runs two local analytical reports on coordinate quality check data: filters rows by a numeric interval on checked_points or flagged_points, and detects adjacent row changes across up to 200 rows.","exampleAgentPrompt":"Analyze my coordinate quality check records — I have 150 rows with station_group, date, checked_points, and flagged_points — filter on checked_points between 5 and 50, and also show me adjacent row changes for that field.","exampleUseCases":[{"title":"QC anomaly detection for weather stations","prompt":"I have 120 rows of coordinate quality check data for my weather stations with checked_points and flagged_points per day. Can you filter to only rows where checked_points falls between 10 and 100, and also flag any adjacent row changes in that field?"},{"title":"Flagged points trend monitoring","prompt":"Here are 80 daily QC records across two station groups — run an interval filter on flagged_points between 0 and 5, and tell me where adjacent rows show changes in flagged_points."},{"title":"Multi-group station QC batch review","prompt":"I need to review 200 rows of coordinate quality checks across multiple station groups. Filter checked_points to the range 0 to 200 and give me a report on adjacent row changes for checked_points as well."}],"resultDescription":"Two analytical reports: (1) a numeric interval filter report listing rows where the selected field (checked_points or flagged_points) falls within the specified minimum/maximum range, and (2) an adjacent row changes report highlighting where consecutive rows differ in the selected field — both computed locally on the supplied data without any external lookup.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, date, checked_points, flagged_points) cause validation errors","Invalid date format (not YYYY-MM-DD) fails schema validation","Numeric values outside allowed range (-1e12 to 1e12) rejected","Minimum greater than maximum produces empty interval filter result","Null values in checked_points/flagged_points may affect change detection output"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of coordinate quality check records (with checked_points and flagged_points fields) and need both a numeric range filter and adjacent row change detection in a single low-cost call. It is ideal for offline/local analytical processing of QC tabular data without needing live weather data, predictions, or external enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:34:57.153Z","isFirstParty":false,"canonicalSlug":"coordinate-quality-checks-numeric-interval-filter-adjacent-row-changes-4472421d"}