{"uid":"cap_ZXEGJwA2VeqEEdgOIWvxE","slug":"schema-conformity-record-quality-audit-string-normalisation-adjacent-1f814ae7","name":"Schema Conformity — Record Quality Audit + String Normalisation + Adjacent Row Changes","description":"Schema conformity — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied schema conformity records (valid_records, checked_records). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-200?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_kYGK3XeVN8S0DZKIHXfxW","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 three local analytical reports (record quality audit, string normalisation, and adjacent row changes) on up to 200 rows of schema conformity data containing valid_records and checked_records fields.","exampleAgentPrompt":"Can you run the three-report schema conformity analysis on my rows — record quality audit, string normalisation, and adjacent row changes — for this batch of up to 200 entries with valid_records as the target field?","exampleUseCases":[{"title":"Daily conformity audit for pipeline data","prompt":"I have 150 rows of schema conformity logs from yesterday's pipeline with date, dataset_group, valid_records, and checked_records — run all three reports (record quality audit, string normalisation, adjacent row changes) against the valid_records field so I can see where quality dropped."},{"title":"Detect sudden shifts between consecutive records","prompt":"Here are 80 schema conformity records grouped by dataset group — can you run the adjacent row changes analysis on checked_records so I can spot any unusual jumps between consecutive rows?"},{"title":"Normalise dataset group strings across conformity logs","prompt":"I've got a batch of conformity records where the dataset_group names look inconsistent — run the string normalisation report on these rows so I can see the cleaned-up values before I reload them."}],"resultDescription":"Three independent analytical reports returned together: (1) a record quality audit summarising completeness and validity of the supplied rows, (2) a string normalisation report showing standardised versions of string fields, and (3) an adjacent row changes report highlighting differences between consecutive rows — all computed locally without any external lookups or predictions.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, valid_records, checked_records) causes rejection","Malformed date strings not matching YYYY-MM-DD pattern are rejected","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array (minItems:1 violated) returns an error"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical passes — quality audit, string normalisation, and adjacent row change detection — on schema conformity data in a single $0.01 call, without needing external data lookups, live predictions, or professional assessments. It is ideal for offline batch validation of ETL pipeline outputs or data quality monitoring workflows where the data is already in hand.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T07:23:46.730Z","isFirstParty":false,"canonicalSlug":"schema-conformity-record-quality-audit-string-normalisation-adjacent-1f814ae7"}