{"uid":"cap_Xpp67C6FMRa4RLNhCUIkJ","slug":"copyediting-throughput-string-normalisation-numeric-row-ordering-1f82f582","name":"Copyediting Throughput — String Normalisation + Numeric Row Ordering","description":"Copyediting throughput — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied copyediting throughput records (edited_words, editing_hours). 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-writing-13-025?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","document_group","date","edited_words","editing_hours"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"edited_words":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"editing_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"document_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","edited_words":10,"editing_hours":1,"document_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","edited_words":20,"editing_hours":2,"document_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","edited_words":15,"editing_hours":3,"document_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","edited_words":30,"editing_hours":4,"document_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["edited_words","editing_hours"],"type":"string","default":"edited_words"}}},"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_NXDRVshX6QcQSRR41Q8aq","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 orders rows numerically for up to 200 copyediting throughput records (edited_words, editing_hours), producing 2 analytical reports per call.","exampleAgentPrompt":"Can you normalize the document group names and sort these copyediting records by edited_words for me? I have 4 rows: row-1 on 2026-10-01 with 10 edited words and 1 editing hour in group-a, row-2 on 2026-10-02 with 20 words and 2 hours in group-b, row-3 on 2026-10-03 with 15 words and 3 hours in group-a, and row-4 on 2026-10-04 with 30 words and 4 hours in group-b — I need both the string normalisation and numeric ordering reports.","exampleUseCases":[{"title":"Rank editors by word output","prompt":"I have a week's worth of copyediting logs — 8 rows each with a date, editor group, edited_words, and editing_hours. Can you normalize the group names and sort all rows by edited_words so I can see who processed the most words this week?"},{"title":"Clean editorial session records","prompt":"Our editorial team submitted throughput records for October with inconsistent document group labels. Can you run string normalisation on the document_group field and sort the 50 rows by editing_hours for me? I want both reports back."},{"title":"Prepare throughput data for dashboard","prompt":"Before I load these copyediting records into our dashboard, can you normalize the string fields and rank the 120 rows by edited_words? I need the two standard analytical reports — string normalisation and numeric row ordering — on this batch."}],"resultDescription":"Returns two analytical reports per call: (1) a string normalisation report standardising the document_group and related string fields across the submitted rows, and (2) a numeric row ordering report ranking rows by the selected field (edited_words or editing_hours). Covers up to 200 input rows with no external lookups or predictions.","failureModes":["More than 200 rows submitted — input rejected","Missing required fields (row_id, document_group, date, edited_words, editing_hours) cause validation errors","Invalid date format (not YYYY-MM-DD) triggers schema rejection","Null numeric values may affect ordering output","Empty rows array causes an error"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and numeric row ordering applied to copyediting throughput records (edited_words, editing_hours) in a single low-cost call. Ideal for editorial teams or publishing analytics pipelines that need lightweight, local data cleaning and ranking without any external API calls, ML predictions, or live lookups. Best for batches up to 200 rows at $0.01 USDC per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T00:39:09.637Z","isFirstParty":false,"canonicalSlug":"copyediting-throughput-string-normalisation-numeric-row-ordering-1f82f582"}