{"uid":"cap_rR9VvoVgYYex89o20uYcd","slug":"receivables-collections-string-normalisation-and-exact-row-2605a452","name":"Receivables Collections String Normalisation and Exact Row Deduplication","description":"Receivables collections — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied receivables collections records (invoiced_amount, collected_amount). 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-finance-20-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","instrument_group","date","invoiced_amount","collected_amount"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"invoiced_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"collected_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"instrument_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","invoiced_amount":10,"collected_amount":1,"instrument_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","invoiced_amount":20,"collected_amount":2,"instrument_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","invoiced_amount":15,"collected_amount":3,"instrument_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","invoiced_amount":30,"collected_amount":4,"instrument_group":"group-b"}],"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_7Jv0VkOe0KrP-fk5kgBnc","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 receivables collections records (invoiced_amount, collected_amount) for up to 200 rows, producing 2 analytical reports.","exampleAgentPrompt":"Can you clean up my receivables collections data by normalizing string fields and removing exact duplicate rows? I have 4 records with row IDs row-1 through row-4, dated 2026-10-01 to 2026-10-04, with instrument groups group-a and group-b, invoiced amounts of 10, 20, 15, and 30, and collected amounts of 1, 2, 3, and 4.","exampleUseCases":[{"title":"Deduplicating month-end receivables export","prompt":"I exported our month-end receivables data and I think there are duplicate rows. Can you run string normalization and exact deduplication on these 50 records? Each has a row ID, instrument group, date, invoiced amount, and collected amount — I want two clean analytical reports back."},{"title":"Standardizing instrument group names before reporting","prompt":"Our collections team uses inconsistent capitalization and spacing in the instrument_group field across our receivables records. Can you normalize those strings and deduplicate any exact duplicate rows across our 120 receivables entries so the data is clean for our finance report?"},{"title":"Pre-processing receivables for reconciliation","prompt":"Before I reconcile our accounts receivable ledger, I need to clean the source data — normalize all the string fields and strip out any exact duplicate rows from these 80 receivables records covering invoiced and collected amounts by date and instrument group."}],"resultDescription":"Returns 2 independent analytical reports covering the submitted receivables collection rows after applying string normalisation (standardising whitespace, casing, and formatting in text fields) and exact row deduplication (removing rows that are byte-for-byte identical). Reports are generated locally with no external lookups or predictions.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, instrument_group, date, invoiced_amount, collected_amount) causes schema rejection","Invalid date format (not YYYY-MM-DD) triggers pattern validation failure","Amounts outside the ±1,000,000,000,000 range are rejected","Empty rows array returns a minItems validation error","Payment not completed via x402 results in 402 Payment Required"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local string normalisation and exact-duplicate removal on up to 200 receivables records (invoiced_amount and collected_amount fields) at very low cost ($0.01 USDC for 2 reports). Ideal for pre-processing finance data before reconciliation or reporting, without requiring live lookups, predictions, or external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T19:09:04.747Z","isFirstParty":false,"canonicalSlug":"receivables-collections-string-normalisation-and-exact-row-2605a452"}