{"uid":"cap_a4-9RzxDITfW3MvTR0pGe","slug":"schema-conformity-record-quality-audit-and-string-normalisation-5a6252b0","name":"Schema Conformity Record Quality Audit and String Normalisation","description":"Schema conformity — Record quality audit + String normalisation: Record quality audit + String normalisation 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-02-001?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}}},"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_X_ZTaIir3Y3Fd_w2DZPkp","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":"Audits record quality and normalises strings for schema conformity data (valid_records, checked_records) across up to 200 rows, producing two independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit and string normalisation on my schema conformity data? Here are 4 rows: row-1 on 2026-10-01 in group-a with 10 valid_records and 1 checked_records, row-2 on 2026-10-02 in group-b with 20 valid and 2 checked, row-3 on 2026-10-03 in group-a with 15 valid and 3 checked, row-4 on 2026-10-04 in group-b with 30 valid and 4 checked.","exampleUseCases":[{"title":"Daily ETL pipeline conformity check","prompt":"I have my daily ETL run results — 50 rows with row IDs, dates, dataset groups, and valid_records vs checked_records counts. Can you audit the record quality and normalise the strings so I can see where my pipeline is dropping records?"},{"title":"Cross-group validity comparison","prompt":"I want to compare schema conformity across two dataset groups — group-alpha and group-beta — over the past month. I have 120 rows with dates, valid_records, and checked_records for each. Can you give me a quality audit and normalised string report for both?"},{"title":"Pre-release data quality review","prompt":"Before we ship this dataset, can you audit the record quality and run string normalisation on our conformity logs? We have about 80 rows covering group-prod entries from October, each with valid_records and checked_records counts."}],"resultDescription":"Two independent analytical reports: (1) a record quality audit summarising valid vs checked record statistics, anomalies, and conformity rates across rows and groups; (2) a string normalisation report cleaning and standardising string fields. Both reports are generated locally with no external lookups, predictions, or professional assessments.","failureModes":["Input array exceeds 200 rows — request will be rejected","Missing required fields (row_id, date, valid_records, checked_records) cause row-level validation errors","Date strings not matching YYYY-MM-DD pattern are rejected","Null values in valid_records or checked_records may produce incomplete audit entries","row_id or dataset_group exceeding 80 character maxLength will fail validation"],"whenToPreferThis":"Choose this endpoint when you need two simultaneous offline analytical reports — a record quality audit plus string normalisation — for schema conformity data with valid_records and checked_records fields, across up to 200 rows, without requiring live lookups, predictions, or external data enrichment. Ideal for batch data quality workflows where cost efficiency ($0.01 for two reports) and local analytical processing are priorities.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-13T00:42:06.797Z","isFirstParty":false,"canonicalSlug":"schema-conformity-record-quality-audit-and-string-normalisation-5a6252b0"}