{"uid":"cap_V53IbHrIVz9MguHts_H4W","slug":"schema-conformity-exact-row-deduplication-adjacent-row-changes-88330b30","name":"Schema Conformity — Exact Row Deduplication + Adjacent Row Changes","description":"Schema conformity — Exact row deduplication + Adjacent row changes: Exact row deduplication + Adjacent row changes 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-02-046?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"}}},"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_r_huDjM-RHYrBkaXlY6tt","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 up to 200 schema conformity records to produce two reports: one identifying exact duplicate rows and one detecting adjacent row changes in valid_records or checked_records fields.","exampleAgentPrompt":"Can you run deduplication and adjacent row change detection on my schema conformity data? I have rows with row_id, dataset_group, date, valid_records, and checked_records — I want both reports on the valid_records field for up to 200 rows.","exampleUseCases":[{"title":"Daily conformity pipeline dedup check","prompt":"I have a batch of up to 150 schema conformity records from my daily pipeline — each has a row_id, dataset_group, date, valid_records, and checked_records. Can you find all exact duplicate rows and also flag where valid_records changed between adjacent rows?"},{"title":"Spot data entry errors in checked_records","prompt":"Here's my dataset conformity log with 80 rows. I need you to deduplicate it and then show me where checked_records shifted between consecutive entries — I'm trying to catch manual data entry mistakes."},{"title":"Validate conformity report before submission","prompt":"Before I submit this schema conformity report, can you run exact row deduplication and adjacent row change analysis on the checked_records field? I have about 60 rows with row_id, dataset_group, date, valid_records, and checked_records."}],"resultDescription":"Returns two independent analytical reports: (1) an exact row deduplication report identifying which rows are perfect duplicates, and (2) an adjacent row changes report showing where the selected field (valid_records or checked_records) changed between consecutive rows — all computed locally with no external lookups.","failureModes":["Empty rows array or missing required row fields (row_id, date, valid_records, checked_records) causes validation error","More than 200 rows submitted exceeds the maxItems limit and will be rejected","Invalid date format (not YYYY-MM-DD) fails pattern validation","Field value outside the allowed numeric range (±1,000,000,000,000) is rejected","Invalid field enum value (not 'valid_records' or 'checked_records') causes error"],"whenToPreferThis":"Choose this endpoint when you need both exact duplicate detection and consecutive-row change analysis on schema conformity data in a single low-cost call. It is ideal for data quality workflows where you want to audit valid_records or checked_records for redundancy and drift without any external lookups or predictions — all processing is local and deterministic.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:26.178Z","isFirstParty":false,"canonicalSlug":"schema-conformity-exact-row-deduplication-adjacent-row-changes-88330b30"}