{"uid":"cap_DDywD7DdmiF0UGa6uqP3U","slug":"export-validation-string-normalisation-date-by-category-pivot-fe9173d5","name":"Export Validation — String Normalisation + Date by Category Pivot","description":"Export validation — String normalisation + Date by category pivot: String normalisation + Date by category pivot 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-14-035?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_YCg4jF3Fn4NHuGhWDxpAU","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 two local analytical reports on export validation data: string normalisation of a chosen metric field and a date-by-category pivot, for up to 200 rows.","exampleAgentPrompt":"I have 150 export validation records with columns row_id, dataset_group, date, valid_rows, and exported_rows — can you run the string normalisation and date-by-category pivot reports on the valid_rows field?","exampleUseCases":[{"title":"Daily export pipeline quality check","prompt":"Here are my export validation records for October — each row has a dataset_group, date, valid_rows, and exported_rows. Can you run the string normalisation and date-by-category pivot on the exported_rows field so I can see how exports are distributed across groups over time?"},{"title":"Comparing valid vs exported row trends","prompt":"I've got 120 export validation rows from our ETL pipeline. Run both the string normalisation and date-by-category pivot reports on the valid_rows field so I can spot which dataset groups are underperforming on which dates."},{"title":"Auditing export dataset consistency","prompt":"Can you analyze these 80 export validation records — each has a row_id, dataset_group, date, valid_rows, and exported_rows — and give me the string normalisation plus date-by-category pivot for valid_rows so I can audit consistency across groups?"}],"resultDescription":"Returns two independent analytical reports: (1) a string normalisation report for the selected metric field (valid_rows or exported_rows) and (2) a date-by-category pivot table showing the chosen metric broken down by date and dataset_group, computed locally from the supplied rows with no external lookups.","failureModes":["More than 200 rows submitted — exceeds maximum batch size","Missing required fields (row_id, dataset_group, date, valid_rows, or exported_rows) on any row","Date field not matching YYYY-MM-DD pattern — validation error","Invalid field enum value — must be 'valid_rows' or 'exported_rows'","Numeric values outside allowed range (±1,000,000,000,000)","Empty rows array — minItems:1 not satisfied","Payment failure via x402 protocol — endpoint returns 402"],"whenToPreferThis":"Choose this endpoint when you need two simultaneous local analytics reports — string normalisation and date-by-category pivot — on export validation data (valid_rows/exported_rows) without requiring external lookups, live data, or predictions. It is cost-effective at $0.01 USDC for both reports on up to 200 rows. Prefer it over general analytics tools when your data is already structured as export validation records with date, group, and row-count fields.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:36.577Z","isFirstParty":false,"canonicalSlug":"export-validation-string-normalisation-date-by-category-pivot-fe9173d5"}