{"uid":"cap_tY6pmk6nfY1mN21tF7p_1","slug":"null-coverage-analytics-record-quality-audit-string-normalisation-b888e1b4","name":"Null Coverage Analytics: Record Quality Audit + String Normalisation + Base-100 Series","description":"Null coverage — Record quality audit + String normalisation + Base-100 series: Record quality audit + String normalisation + Base-100 series for supplied null coverage records (missing_values, total_values). 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-03-201?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","missing_values","total_values"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"missing_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_values":1,"dataset_group":"group-a","missing_values":10},{"date":"2026-10-02","row_id":"row-2","total_values":2,"dataset_group":"group-b","missing_values":20},{"date":"2026-10-03","row_id":"row-3","total_values":3,"dataset_group":"group-a","missing_values":15},{"date":"2026-10-04","row_id":"row-4","total_values":4,"dataset_group":"group-b","missing_values":30}],"maxItems":200,"minItems":1},"field":{"enum":["missing_values","total_values"],"type":"string","default":"missing_values"},"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_D1IGjIj8cWy4UqkaicRBZ","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 base-100 index series) on supplied null-coverage data (missing_values and total_values) for up to 200 rows.","exampleAgentPrompt":"Can you run the three null-coverage analytics reports — record quality audit, string normalisation, and base-100 series — on my dataset? I have 4 rows: row-1 in group-a on 2026-10-01 with 10 missing out of 1 total, row-2 in group-b on 2026-10-02 with 20 missing out of 2 total, row-3 in group-a on 2026-10-03 with 15 missing out of 3 total, and row-4 in group-b on 2026-10-04 with 30 missing out of 4 total. Use 'missing_values' as the field and base index 0.","exampleUseCases":[{"title":"Monthly data completeness audit","prompt":"I need a record quality audit, string normalisation, and base-100 series for my October null-coverage data — 3 rows: row-1 in group-alpha on 2026-10-01 with 5 missing out of 100 total, row-2 in group-beta on 2026-10-02 with 12 missing out of 100 total, row-3 in group-alpha on 2026-10-03 with 0 missing out of 100 total. Analyse the missing_values field starting from base index 0."},{"title":"Cross-group null coverage comparison","prompt":"Run all three null coverage reports on my two dataset groups: row-A in group-sales on 2026-11-01 had 200 missing out of 1000 total, row-B in group-marketing on 2026-11-01 had 50 missing out of 800 total, row-C in group-ops on 2026-11-01 had 0 missing out of 600 total. Use total_values as the field and base index 0."},{"title":"Time-series completeness indexing","prompt":"Can you compute the base-100 index series, quality audit, and string normalisation for my weekly null-coverage readings? Five rows: row-w1 in group-main on 2026-09-01 with 8 missing of 200, row-w2 on 2026-09-08 with 15 missing of 200, row-w3 on 2026-09-15 with 3 missing of 200, row-w4 on 2026-09-22 with 22 missing of 200, row-w5 on 2026-09-29 with 10 missing of 200. Field is missing_values, base index 2."}],"resultDescription":"Three independent analytical reports for the supplied null-coverage records: (1) a record quality audit flagging anomalies in missing/total value fields, (2) a string normalisation report cleaning dataset_group and row_id labels, and (3) a base-100 indexed series for the chosen field relative to the specified base row — all computed locally without external lookups or predictions.","failureModes":["Validation error if rows array is empty or exceeds 200 items","Schema violation if row objects are missing required fields (row_id, dataset_group, date, missing_values, total_values)","Invalid date format if date strings do not match YYYY-MM-DD pattern","base_index out of range if it exceeds the number of submitted rows minus one","Numeric overflow if missing_values or total_values exceed the 1,000,000,000,000 limit","Payment failure if 0.01 USDC x402 payment is not attached"],"whenToPreferThis":"Choose this endpoint when you need a combined, low-cost bundle of three data-quality analytics (quality audit, string normalisation, base-100 series) on null-coverage records without needing external data lookups, predictions, or live integrations. It is best suited for offline or batch data quality checks on small-to-medium datasets (up to 200 rows) where all data is already available as missing_values and total_values pairs.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-14T00:34:27.684Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-record-quality-audit-string-normalisation-b888e1b4"}