{"uid":"cap_8rAoeW4R0uClaGolb5v4N","slug":"dataset-storage-record-quality-audit-and-category-frequencies-65ea27e1","name":"Dataset Storage Record Quality Audit and Category Frequencies","description":"Dataset storage — Record quality audit + Category frequencies: Record quality audit + Category frequencies for supplied dataset storage records (used_mb, row_count). 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-18-006?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}}},"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_3vGvUyJxLyUQsHl96_IUI","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 a record quality audit and category frequency analysis on up to 200 dataset storage records (used_mb, row_count) and returns two independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit and category frequency analysis on these 50 dataset storage records I have, each with row_id, dataset_group, date, used_mb, and row_count fields? I want to know which records have nulls or quality issues and how often each dataset_group appears.","exampleUseCases":[{"title":"Storage log data quality check","prompt":"I have 120 storage records from our data warehouse, each with a row_id, dataset_group, date, used_mb, and row_count. Can you audit them for data quality issues like nulls or bad values, and also tell me how many records fall into each dataset_group category?"},{"title":"Monthly dataset group frequency report","prompt":"Here are 80 rows from our monthly dataset storage report with fields row_id, dataset_group, date, used_mb, and row_count — can you give me a frequency breakdown of how many records are in each group, along with a quality audit flagging any missing or suspicious values?"},{"title":"Pre-pipeline data validation for storage metrics","prompt":"Before we load these 200 storage metric records into our pipeline, can you run a quality audit to spot any null used_mb or row_count values, and also show me the category frequencies for dataset_group so we know the distribution?"}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit identifying null, missing, or anomalous values across the used_mb and row_count fields for each row, and (2) a category frequency summary showing how many records belong to each dataset_group. Covers up to 200 input rows with no external lookups or predictions.","failureModes":["More than 200 rows submitted — endpoint enforces a 200-row maximum and will reject the request","Missing required fields (row_id, dataset_group, date, used_mb, or row_count) on any row causes validation failure","Invalid date format (not YYYY-MM-DD) triggers schema rejection","Numeric fields outside the allowed range (-1000000000000 to 1000000000000) will fail validation","Empty rows array (minItems: 1 not met) returns an error"],"whenToPreferThis":"Choose this endpoint when you need fast, local analytical profiling of dataset storage records — specifically record quality auditing (null/anomaly detection) and category frequency counting across dataset groups — without any external data lookups, predictions, or professional assessments. It is ideal for pre-pipeline data validation or exploratory data profiling on batches up to 200 rows at very low cost ($0.01 for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:56.156Z","isFirstParty":false,"canonicalSlug":"dataset-storage-record-quality-audit-and-category-frequencies-65ea27e1"}