{"uid":"cap_v4PlAGxlBm5JsBBtM0CBO","slug":"duplicate-observations-analytics-record-quality-audit-string-ecbf791c","name":"Duplicate Observations Analytics — Record Quality Audit + String Normalisation + Grouped Numeric Summary","description":"Duplicate observations — Record quality audit + String normalisation + Grouped numeric summary: Record quality audit + String normalisation + Grouped numeric summary for supplied duplicate observations records (duplicate_rows, total_rows). 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-04-194?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","duplicate_rows","total_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"duplicate_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_rows":1,"dataset_group":"group-a","duplicate_rows":10},{"date":"2026-10-02","row_id":"row-2","total_rows":2,"dataset_group":"group-b","duplicate_rows":20},{"date":"2026-10-03","row_id":"row-3","total_rows":3,"dataset_group":"group-a","duplicate_rows":15},{"date":"2026-10-04","row_id":"row-4","total_rows":4,"dataset_group":"group-b","duplicate_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["duplicate_rows","total_rows"],"type":"string","default":"duplicate_rows"}}},"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_6ZhCwE1pkx0u6Q7iz27nq","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 grouped numeric summary) on up to 200 duplicate-observation records containing duplicate_rows and total_rows fields.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and grouped numeric summary on my duplicate observation data? I have rows like: row-1 on 2026-10-01, dataset_group 'group-a', duplicate_rows=10, total_rows=1 — up to 4 rows total — and I want to focus the numeric summary on the duplicate_rows field.","exampleUseCases":[{"title":"Data pipeline deduplication audit","prompt":"I have a table tracking duplicate records across my data pipelines — each row has a date, a dataset group name, duplicate_rows, and total_rows. Can you run a record quality audit, normalise the group name strings, and give me a grouped numeric summary focused on duplicate_rows for these 50 rows?"},{"title":"Monthly dataset group quality report","prompt":"I need a quality report on my dataset groups for October 2026. I have about 80 rows with fields: row_id, dataset_group, date, duplicate_rows, and total_rows. Please audit the record quality, normalise the dataset_group strings, and summarise total_rows grouped by dataset_group."},{"title":"Deduplication tracking sanity check","prompt":"Can you sanity-check my deduplication tracking data? I've got 20 rows — each has a row ID, a date, a group label, a count of duplicate rows, and total rows. Run the record quality audit, string normalisation, and a grouped numeric summary on duplicate_rows so I can spot any anomalies."}],"resultDescription":"Returns three independent analytical reports for the supplied rows: (1) a record quality audit flagging data issues, (2) a string normalisation report cleaning the dataset_group and other string fields, and (3) a grouped numeric summary of the selected field (duplicate_rows or total_rows) broken down by dataset_group. All analysis is performed locally with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) causes rejection","Invalid date format (non-YYYY-MM-DD) fails schema validation","Empty rows array is rejected (minItems: 1)","Numeric values outside ±1,000,000,000,000 are rejected","Invalid field enum value (not 'duplicate_rows' or 'total_rows') fails validation","Payment of 0.01 USDC not fulfilled causes 402 response"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical reports — record quality audit, string normalisation, and grouped numeric summary — on duplicate observation data in a single cost-efficient call ($0.01 USDC for all three). It is best suited for offline/batch analytical workflows where no live data lookup, prediction, or external action is required, and when your data fits within 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:32.338Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-analytics-record-quality-audit-string-ecbf791c"}