{"uid":"cap_dJlQmkh1McSvDb2f9M8J1","slug":"page-extraction-coverage-string-normalisation-exact-row-deduplication-43b53221","name":"Page Extraction Coverage — String Normalisation + Exact Row Deduplication","description":"Page extraction coverage — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied page extraction coverage records (extracted_fields, expected_fields). 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-web-02-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","site_group","date","extracted_fields","expected_fields"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"site_group":{"type":"string","default":"","maxLength":80},"expected_fields":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"extracted_fields":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","site_group":"group-a","expected_fields":1,"extracted_fields":10},{"date":"2026-10-02","row_id":"row-2","site_group":"group-b","expected_fields":2,"extracted_fields":20},{"date":"2026-10-03","row_id":"row-3","site_group":"group-a","expected_fields":3,"extracted_fields":15},{"date":"2026-10-04","row_id":"row-4","site_group":"group-b","expected_fields":4,"extracted_fields":30}],"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_Y-YhzV-BpihpdhQOzieLY","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":"Normalises strings and deduplicates exact rows in page extraction coverage data (extracted_fields vs expected_fields), producing two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you run string normalisation and exact row deduplication on my page extraction coverage data? I have rows for site groups like 'group-a' and 'group-b' with dates from 2026-10-01 to 2026-10-04, and I need both reports — extracted_fields and expected_fields are included for each row.","exampleUseCases":[{"title":"Cleaning scraper coverage audit logs","prompt":"I have 150 rows of page extraction coverage records from last month — each row has a site_group, date, extracted_fields count, and expected_fields count. Can you normalise the strings and remove any exact duplicate rows, then give me the two reports?"},{"title":"Pre-pipeline deduplication for ETL","prompt":"Before I load my extraction coverage dataset into the pipeline, can you run exact row deduplication and string normalisation on it? I've got about 80 rows across three site groups dated between 2026-09-01 and 2026-09-30."},{"title":"Data quality check across site groups","prompt":"I want to check data quality across my site groups — can you normalise strings and deduplicate the exact rows in my coverage records? There are around 200 rows with extracted_fields and expected_fields values per site group and date."}],"resultDescription":"Two analytical reports: one covering string normalisation results and one covering exact row deduplication results, applied to the supplied page extraction coverage records (up to 200 rows). No external lookups or predictions are made; all analysis is performed locally on the submitted data.","failureModes":["Exceeding 200 rows in the input array returns a validation error","Missing required fields (row_id, site_group, date, extracted_fields, expected_fields) causes rejection","Malformed date strings not matching YYYY-MM-DD pattern cause validation failure","Numeric field values outside the allowed range (-1e12 to 1e12) are rejected","Empty rows array (minItems: 1 not met) returns an error"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and exact row deduplication applied together to page extraction coverage data in a single call, producing two independent reports. It is ideal for data quality pipelines where you want to clean and deduplicate web scraping coverage records (extracted_fields vs expected_fields) without making any external lookups or predictions, and where your dataset fits within 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:54:32.861Z","isFirstParty":false,"canonicalSlug":"page-extraction-coverage-string-normalisation-exact-row-deduplication-43b53221"}