{"uid":"cap_dfb7ymb6QDajc0oRqvpv2","slug":"export-validation-category-frequencies-numeric-row-ordering-972f12ef","name":"Export Validation — Category Frequencies + Numeric Row Ordering","description":"Export validation — Category frequencies + Numeric row ordering: Category frequencies + Numeric row ordering for supplied export validation records (valid_rows, exported_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-14-100?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","valid_rows","exported_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"valid_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"exported_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","valid_rows":10,"dataset_group":"group-a","exported_rows":1},{"date":"2026-10-02","row_id":"row-2","valid_rows":20,"dataset_group":"group-b","exported_rows":2},{"date":"2026-10-03","row_id":"row-3","valid_rows":15,"dataset_group":"group-a","exported_rows":3},{"date":"2026-10-04","row_id":"row-4","valid_rows":30,"dataset_group":"group-b","exported_rows":4}],"maxItems":200,"minItems":1},"field":{"enum":["valid_rows","exported_rows"],"type":"string","default":"valid_rows"}}},"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_UYJ8uxsMopDLYKe7axVnT","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":"Analyzes export validation records to produce two local reports: category frequency counts by dataset_group and numeric row ordering by valid_rows or exported_rows, for up to 200 rows.","exampleAgentPrompt":"Analyze my export validation records — I have rows with dataset_group, valid_rows, and exported_rows fields — and give me two reports: a frequency count of each category group and the rows sorted by valid_rows. Here are my rows: row-1 (group-a, 2026-10-01, valid=10, exported=1), row-2 (group-b, 2026-10-02, valid=20, exported=2), row-3 (group-a, 2026-10-03, valid=15, exported=3).","exampleUseCases":[{"title":"Audit export coverage by category","prompt":"I have 50 export validation records across several dataset groups and I want to know how many records fall into each group, plus a ranked list of rows by valid_rows. Can you run both reports for me? Groups include 'finance', 'ops', and 'hr'."},{"title":"Rank records by exported row count","prompt":"Take my export validation data — about 80 rows with valid_rows and exported_rows fields — and order them by exported_rows so I can see which entries had the most exports, and also tell me how frequently each dataset_group appears."},{"title":"Validate dataset export balance across groups","prompt":"I'm checking whether our data export is evenly distributed across groups. I have 120 validation records with dataset_group, valid_rows, and exported_rows. Give me a category frequency count for the groups and sort the records by valid_rows descending so I can spot imbalances."}],"resultDescription":"Returns two independent analytical reports: (1) a frequency count showing how many records belong to each dataset_group category, and (2) a numeric row ordering of the submitted records ranked by the selected field (valid_rows or exported_rows). All computation is performed locally on the supplied data — no external lookups or predictions.","failureModes":["Submitting more than 200 rows returns an error (maxItems exceeded)","Missing required fields (row_id, dataset_group, date, valid_rows, exported_rows) cause schema validation failure","Invalid date format (not YYYY-MM-DD) is rejected by the pattern constraint","Null values in valid_rows or exported_rows are allowed but may affect ordering output","Payment failure via x402 protocol results in no response"],"whenToPreferThis":"Choose this endpoint when you need two bundled analytical reports — category frequency counts and numeric row ordering — on export validation records in a single cost-efficient call ($0.01 USDC for both). Ideal when you already have the data locally and need fast, offline-style statistical summaries without live lookups, external data enrichment, or ML predictions. Prefer over general analytics tools when working within the x402 micropayment ecosystem and needing reproducible, deterministic outputs on small-to-medium datasets (up to 200 rows).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:16.230Z","isFirstParty":false,"canonicalSlug":"export-validation-category-frequencies-numeric-row-ordering-972f12ef"}