{"uid":"cap_VgtJ6yCbTBiG3bjberaLp","slug":"schema-conformity-numeric-interval-filter-date-by-category-pivot-4a512787","name":"Schema Conformity — Numeric Interval Filter + Date by Category Pivot","description":"Schema conformity — Numeric interval filter + Date by category pivot: Numeric interval filter + Date by category pivot for supplied schema conformity records (valid_records, checked_records). 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-analytics-02-133?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","valid_records","checked_records"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"valid_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"checked_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","valid_records":10,"checked_records":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","valid_records":20,"checked_records":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","valid_records":15,"checked_records":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","valid_records":30,"checked_records":4}],"maxItems":200,"minItems":1},"field":{"enum":["valid_records","checked_records"],"type":"string","default":"valid_records"},"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_01IMSlpYe2FtTRf0x48Up","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":"Filters schema conformity rows by a numeric interval on valid_records or checked_records, then pivots dates by dataset_group category — two analytical reports in one call.","exampleAgentPrompt":"Run two reports on my schema conformity data: filter the rows where valid_records is between 10 and 500, and also pivot the dates by dataset_group category — here are my 50 rows with row_id, dataset_group, date, valid_records, and checked_records fields.","exampleUseCases":[{"title":"Audit passing records within quality threshold","prompt":"I have 120 schema conformity records with valid_records and checked_records columns — can you filter down to only the rows where valid_records is between 50 and 10000, and also show me a date-by-category pivot so I can see which dataset_group has activity on which dates?"},{"title":"Identify low checked_records groups by date","prompt":"For my data quality batch, run an interval filter on checked_records between 0 and 100 and then pivot the dates by dataset_group — I want to see both the filtered set and the category-date breakdown in one shot. I'll send you the rows with row_id, dataset_group, date, valid_records, and checked_records."},{"title":"Compare dataset groups across conformity window","prompt":"Take these 80 schema conformity rows and give me two reports: filter them to where valid_records falls between 200 and 5000, and cross-tabulate dates against each dataset_group so I can compare conformity activity across groups over time."}],"resultDescription":"Two independent analytical reports returned together: (1) a subset of the input rows where the chosen numeric field (valid_records or checked_records) falls within the specified [minimum, maximum] interval, and (2) a pivot table of dates cross-tabulated by dataset_group category — both computed locally from the supplied data with no external lookups.","failureModes":["Input rows array is empty or exceeds 200 items — request rejected","minimum value greater than maximum value — invalid interval, likely returns empty filter result or error","Required row fields (row_id, date, dataset_group, valid_records, checked_records) missing or malformed — validation error","Date strings not matching YYYY-MM-DD pattern — schema validation failure","numeric fields out of allowed range (±1 trillion) — rejected by schema","Payment of 0.01 USDC not completed via x402 protocol — 402 Payment Required response"],"whenToPreferThis":"Choose this endpoint when you need both a numeric range filter and a date-by-category pivot on schema conformity data (valid_records, checked_records) in a single cheap call. It is ideal for data quality pipelines where you want to isolate records within acceptable bounds and simultaneously see temporal category breakdowns. Prefer it over general-purpose analytics tools when your data is already structured with row_id, dataset_group, date, valid_records, and checked_records fields and you want two focused reports without external computation.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T07:07:23.908Z","isFirstParty":false,"canonicalSlug":"schema-conformity-numeric-interval-filter-date-by-category-pivot-4a512787"}