{"uid":"cap_QcwazQLgQNbPtzUZT3uDf","slug":"join-coverage-record-quality-audit-and-base-100-series-4700ce99","name":"Join Coverage Record Quality Audit and Base-100 Series","description":"Join coverage — Record quality audit + Base-100 series: Record quality audit + Base-100 series for supplied join coverage records (matched_rows, source_rows). 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-09-012?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","matched_rows","source_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"matched_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_rows":1,"matched_rows":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_rows":2,"matched_rows":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_rows":3,"matched_rows":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_rows":4,"matched_rows":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["matched_rows","source_rows"],"type":"string","default":"matched_rows"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_GV_i6H-DznWRrP_EElLFR","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 two analytical reports on join coverage data — a record quality audit and a Base-100 index series — for up to 200 rows of matched_rows/source_rows data.","exampleAgentPrompt":"Run a record quality audit and Base-100 series on my join coverage data — I have 4 rows with fields row_id, dataset_group, date, matched_rows, and source_rows; use matched_rows as the field and row index 0 as the base.","exampleUseCases":[{"title":"ETL join quality audit","prompt":"I have 50 rows of daily join coverage results across two dataset groups with matched_rows and source_rows counts — can you run a record quality audit and Base-100 series on them using matched_rows as the field and row 0 as the base?"},{"title":"Baseline indexing for coverage trends","prompt":"Run a Base-100 index series on my join coverage data for dataset group 'orders' across the last 30 days, using source_rows as the field and index 0 as the baseline, so I can see how coverage has shifted over time."},{"title":"Detecting anomalies in matched row counts","prompt":"I want to audit the data quality of my join coverage records — I've got 120 rows with matched_rows and source_rows values across groups A and B. Can you run both the record quality audit and Base-100 report, using matched_rows and base index 0?"}],"resultDescription":"Two independent analytical reports for the supplied join coverage rows: (1) a record quality audit flagging anomalies, nulls, or inconsistencies in the matched_rows/source_rows data; and (2) a Base-100 index series normalizing the selected field relative to the specified baseline row — all computed locally without external lookups.","failureModes":["More than 200 rows supplied — request will be rejected or truncated","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors","base_index out of range (must be 0–199 and within the supplied row count)","Null values in the selected field may affect Base-100 indexing","Invalid date format (must be YYYY-MM-DD) causes schema rejection"],"whenToPreferThis":"Choose this endpoint when you have join coverage data (matched_rows and source_rows) and need both a record-level quality audit and a Base-100 normalization series in a single $0.01 call, without requiring external data sources, live lookups, or predictions. Ideal for ETL validation workflows, data pipeline monitoring, and coverage trend analysis on batches up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:46.673Z","isFirstParty":false,"canonicalSlug":"join-coverage-record-quality-audit-and-base-100-series-4700ce99"}