{"uid":"cap_RjktENfFmbU1kStZykr6y","slug":"dataset-storage-record-quality-audit-string-normalisation-numeric-f16d7bf0","name":"Dataset Storage Record Quality Audit, String Normalisation & Numeric Distribution","description":"Dataset storage — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution 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-18-193?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_xKJNnftQ2NFYTmNTIy12s","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 dataset storage records: a record quality audit, string normalisation check, and numeric distribution analysis for the used_mb and row_count fields.","exampleAgentPrompt":"Can you run a quality audit, string normalisation check, and numeric distribution analysis on my dataset storage records — here are up to 200 rows with row_id, dataset_group, date, used_mb, and row_count fields — and report on the used_mb field?","exampleUseCases":[{"title":"Pre-ingestion data quality check","prompt":"Before I load these dataset storage records into our warehouse, can you audit them for quality issues, check the string fields are well-formed, and show me the numeric distribution of used_mb? I have about 80 rows with row_id, dataset_group, date, used_mb, and row_count."},{"title":"Storage anomaly detection by group","prompt":"I've got 150 rows of storage tracking data across multiple dataset groups and I want to know if there are any outliers or weird distributions in the row_count field — can you run the quality audit and numeric distribution report on them?"},{"title":"Monthly dataset health report","prompt":"Here are this month's 200 storage records with used_mb and row_count per dataset group — run the full three-report analysis including string normalisation and numeric distribution on used_mb so I can include it in our monthly data health summary."}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging nulls, missing values, and data completeness issues; (2) a string normalisation report checking and cleaning string fields like row_id and dataset_group; (3) a numeric distribution summary (e.g. min, max, mean, percentiles, outlier flags) for the selected numeric field (used_mb or row_count). All computed locally with no external lookups. Covers up to 200 input rows.","failureModes":["Input array is empty or missing — minItems:1 not satisfied","More than 200 rows submitted — maxItems exceeded","row_id missing or empty — minLength:1 violation","date field does not match YYYY-MM-DD pattern — pattern validation failure","used_mb or row_count values outside allowed numeric range","Invalid field enum value provided — must be 'used_mb' or 'row_count'","Payment not completed — x402 payment required before response"],"whenToPreferThis":"Choose this endpoint when you have up to 200 dataset storage records (with used_mb and row_count fields) and need three combined analytical outputs — quality audit, string normalisation, and numeric distribution — in a single low-cost call. Ideal for lightweight pre-ingestion validation or periodic data health checks where no external data enrichment or predictive modelling is required. Not suitable for large datasets over 200 rows, real-time monitoring, or tasks requiring live lookups or ML-based predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:53.852Z","isFirstParty":false,"canonicalSlug":"dataset-storage-record-quality-audit-string-normalisation-numeric-f16d7bf0"}