{"uid":"cap_5jCHDd3JrZj2eEP7TnXC3","slug":"dataset-storage-analytics-record-quality-audit-string-normalisation-2ca5d609","name":"Dataset Storage Analytics — Record Quality Audit, String Normalisation & Secondary-Measure Weighted Mean","description":"Dataset storage — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean for supplied dataset storage records (used_mb, row_count). 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-18-205?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","used_mb","row_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"used_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_count":{"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","used_mb":10,"row_count":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","used_mb":20,"row_count":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","used_mb":15,"row_count":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","used_mb":30,"row_count":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["used_mb","row_count"],"type":"string","default":"used_mb"}}},"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__kgKtLdg1LRN1lYHp2Rng","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 bundled analytical reports on up to 200 dataset storage records: record quality audit, string normalisation, and secondary-measure weighted mean for used_mb or row_count fields.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and weighted mean analysis on my dataset storage records — here are up to 200 rows with fields row_id, dataset_group, date, used_mb, and row_count — and use used_mb as the primary field?","exampleUseCases":[{"title":"Storage usage quality audit","prompt":"I have a batch of dataset storage records with fields like dataset_group, date, used_mb, and row_count — can you audit them for quality issues, normalise the group name strings, and give me a weighted mean of used_mb across all 150 rows?"},{"title":"Row count analytics across groups","prompt":"Run the three analytics reports on my dataset storage data — quality audit, string normalisation, and weighted mean — but use row_count as the measure field instead of used_mb. I'll paste in about 80 rows with row_id, dataset_group, date, used_mb, and row_count."},{"title":"Detecting dirty group labels in storage data","prompt":"I suspect some of my dataset_group labels are inconsistently formatted across my storage records. Can you run a string normalisation report along with the quality audit and weighted mean on these 60 rows so I can see what needs cleaning?"}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging missing, out-of-range, or malformed values; (2) a string normalisation report on dataset_group and other string fields; and (3) a weighted mean of the selected numeric measure (used_mb or row_count) using the secondary measure as weights — all computed locally without external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, dataset_group, date, used_mb, row_count) causes rejection","Date values not matching YYYY-MM-DD pattern fail schema validation","Numeric values outside allowed range trigger validation errors","Invalid field enum value (not 'used_mb' or 'row_count') causes parameter error"],"whenToPreferThis":"Choose this endpoint when you need three bundled data quality and statistical reports on dataset storage records in a single low-cost call — specifically when you want record quality auditing, string normalisation, and a weighted mean computation together without making external API calls or requiring live data lookup. Ideal for batch analytical pipelines processing up to 200 storage usage rows at a time.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T17:26:33.156Z","isFirstParty":false,"canonicalSlug":"dataset-storage-analytics-record-quality-audit-string-normalisation-2ca5d609"}