{"uid":"cap_T_IQiyhz6AJQkrjSwDwH1","slug":"structured-data-observations-numeric-interval-filter-daily-sum-series-a259176f","name":"Structured Data Observations — Numeric Interval Filter + Daily Sum Series","description":"Structured data observations — Numeric interval filter + Daily sum series: Numeric interval filter + Daily sum series for supplied structured data observations records (valid_items, total_items). 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-web-08-125?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","site_group","date","valid_items","total_items"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"site_group":{"type":"string","default":"","maxLength":80},"total_items":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"valid_items":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","site_group":"group-a","total_items":1,"valid_items":10},{"date":"2026-10-02","row_id":"row-2","site_group":"group-b","total_items":2,"valid_items":20},{"date":"2026-10-03","row_id":"row-3","site_group":"group-a","total_items":3,"valid_items":15},{"date":"2026-10-04","row_id":"row-4","site_group":"group-b","total_items":4,"valid_items":30}],"maxItems":200,"minItems":1},"field":{"enum":["valid_items","total_items"],"type":"string","default":"valid_items"},"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_T3sVgp6e1QsoWS_9AEVUM","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":"Applies a numeric interval filter and generates a daily sum time series for structured observation records with valid_items and total_items fields, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you run a numeric interval filter on the valid_items field — keeping only rows where valid_items is between 5 and 50 — and also generate a daily sum series from this dataset? I have about 150 rows with row_id, site_group, date, valid_items, and total_items columns.","exampleUseCases":[{"title":"Quality control observation filtering","prompt":"I have 200 rows of daily quality control observations with valid_items and total_items. Filter the valid_items field to only rows between 10 and 500, and also give me a daily sum series so I can see how totals trend over time."},{"title":"Site group performance daily rollup","prompt":"Here's my structured dataset of site group observations — can you filter out any rows where total_items falls outside the range of 0 to 1000, and also produce a daily sum series for total_items so I can see the day-by-day totals?"},{"title":"Data validation with temporal aggregation","prompt":"I need two reports on this batch of observation records: first, flag which valid_items values fall within the interval 20 to 200, and second, give me a daily sum series for valid_items across all dates in the dataset."}],"resultDescription":"Two analytical reports: (1) a numeric interval filter report identifying which rows have the specified field value within the given minimum–maximum range, and (2) a daily sum series aggregating the specified numeric field by date across all provided rows. Results are computed locally from supplied data with no external lookups.","failureModes":["Rows array empty or missing — API rejects with validation error","More than 200 rows submitted — exceeds maxItems limit","Invalid date format (not YYYY-MM-DD) — pattern validation failure","Field value outside allowed numeric bounds (±1 trillion) — schema rejection","Null values in numeric fields may affect aggregation results","Payment not included or insufficient — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 structured observation rows with date, site_group, valid_items, and total_items fields and need both a numeric range filter report and a daily sum time series in a single low-cost call ($0.01 USDC). It is ideal for batch offline analysis of pre-collected data rather than live lookups or real-time streaming. Prefer alternatives when you need more than 200 rows, live data fetching, prediction, or professional assessment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:33:31.939Z","isFirstParty":false,"canonicalSlug":"structured-data-observations-numeric-interval-filter-daily-sum-series-a259176f"}