{"uid":"cap__HGiaSiqNPoMqw1J-WYc3","slug":"schema-conformity-analytics-record-quality-audit-exact-row-342505f5","name":"Schema Conformity Analytics — Record Quality Audit, Exact Row Deduplication & Category Frequencies","description":"Schema conformity — Record quality audit + Exact row deduplication + Category frequencies: Record quality audit + Exact row deduplication + Category frequencies 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-02-212?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_voQjWsq-ecsdEt7Zg-hv8","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 on schema conformity data (valid_records, checked_records): a record quality audit, exact row deduplication, and category frequency breakdown — all for up to 200 rows in a single call.","exampleAgentPrompt":"Can you run a record quality audit, exact duplicate check, and category frequency breakdown on my schema conformity data? Here are my rows — each has a row_id, dataset_group, date, valid_records, and checked_records — I have about 150 rows across groups like 'group-a' and 'group-b' from October 2026.","exampleUseCases":[{"title":"Pipeline data quality audit","prompt":"I have 120 rows of schema conformity data from our ETL pipeline — each row has a row_id, dataset_group, date, valid_records, and checked_records. Can you audit the record quality, flag any exact duplicate rows, and show me frequency counts per dataset_group?"},{"title":"Deduplication check before reporting","prompt":"Before I send this conformity report to my team, can you check these 80 rows for exact duplicates and also give me a quality audit? The rows have fields for row_id, dataset_group, date, valid_records, and checked_records."},{"title":"Category frequency analysis for schema groups","prompt":"I want to understand how my schema validation records are distributed across dataset groups. Can you take these 200 rows — with row_id, dataset_group, date, valid_records, and checked_records — and give me the category frequencies along with a quality audit and duplicate check?"}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit summarizing completeness and validity of each row's fields, (2) an exact row deduplication report identifying identical rows, and (3) category frequency counts broken down by dataset_group — all computed locally without external lookups.","failureModes":["Exceeding 200 rows returns an error — input must be trimmed to the limit","Missing required fields (row_id, dataset_group, date, valid_records, checked_records) on any row may cause validation failure","Malformed date strings not matching YYYY-MM-DD pattern will be flagged or rejected","Null numeric values are accepted but may affect quality audit scoring","Empty row array (minItems: 1 violated) will return an error"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical reports — quality audit, deduplication, and frequency analysis — on schema conformity tracking data (valid_records and checked_records fields) in a single low-cost call. It is ideal for data pipeline QA workflows, pre-report data hygiene checks, and governance dashboards where you want offline, deterministic analysis with no external data access. Prefer it over separate single-report endpoints when all three report types are needed simultaneously to save cost and latency.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-14T00:37:23.781Z","isFirstParty":false,"canonicalSlug":"schema-conformity-analytics-record-quality-audit-exact-row-342505f5"}