{"uid":"cap_38EHQKSxJfeU6U1R9ylr4","slug":"article-publication-string-normalisation-numeric-row-ordering-3c87ff78","name":"Article Publication — String Normalisation + Numeric Row Ordering","description":"Article publication — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied article publication records (published_articles, word_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-news-01-025?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","channel_group","date","published_articles","word_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"word_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"channel_group":{"type":"string","default":"","maxLength":80},"published_articles":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","word_count":1,"channel_group":"group-a","published_articles":10},{"date":"2026-10-02","row_id":"row-2","word_count":2,"channel_group":"group-b","published_articles":20},{"date":"2026-10-03","row_id":"row-3","word_count":3,"channel_group":"group-a","published_articles":15},{"date":"2026-10-04","row_id":"row-4","word_count":4,"channel_group":"group-b","published_articles":30}],"maxItems":200,"minItems":1},"field":{"enum":["published_articles","word_count"],"type":"string","default":"published_articles"}}},"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_YG_HNKIg81Wzs80kxqf6A","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 string fields and applies numeric row ordering to up to 200 article publication records, producing two analytical reports on published_articles or word_count data.","exampleAgentPrompt":"I have up to 200 rows of article publication data with row IDs, dates, channel groups, and published article counts — can you run string normalisation on the channel group field and apply numeric row ordering on published_articles, then give me both reports?","exampleUseCases":[{"title":"Standardise news channel article counts","prompt":"I've got 150 rows of daily article publication records across different channel groups — can you normalise the channel group strings and rank them by published_articles count so I can see which channels are most active?"},{"title":"Order word count data across dates","prompt":"Here are 80 rows of article data with dates, channel groups, and word counts — please run string normalisation on the channel names and give me numeric row ordering based on word_count so I can spot patterns."},{"title":"Audit multi-channel publication records","prompt":"I need to clean up 60 rows of publication records from several news channels — can you normalise the channel_group text field and order all rows numerically by published_articles, then produce both reports?"}],"resultDescription":"Two independent analytical reports covering: (1) string-normalised channel_group values across the submitted rows, and (2) numeric row ordering applied to the selected field (published_articles or word_count), all computed locally against the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request rejected","Missing required fields (row_id, channel_group, date, published_articles, or word_count) — validation error","Invalid date format (must match YYYY-MM-DD pattern) — schema rejection","Numeric values outside allowed range — validation error","Empty rows array — minimum item constraint violation"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local string normalisation and numeric row ordering specifically on article publication datasets (published_articles, word_count) without any live data lookup, external enrichment, or predictive modelling — ideal for quick batch cleaning of up to 200 publication records at minimal cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:37:05.683Z","isFirstParty":false,"canonicalSlug":"article-publication-string-normalisation-numeric-row-ordering-3c87ff78"}