{"uid":"cap_6YvbEa1c9ZXTUGTRGzdgz","slug":"settlement-timing-string-normalisation-adjacent-row-changes-4a672875","name":"Settlement Timing — String Normalisation + Adjacent Row Changes","description":"Settlement timing — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied settlement timing records (settlement_minutes, payment_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-finance-18-029?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","instrument_group","date","settlement_minutes","payment_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"payment_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"instrument_group":{"type":"string","default":"","maxLength":80},"settlement_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","payment_count":1,"instrument_group":"group-a","settlement_minutes":10},{"date":"2026-10-02","row_id":"row-2","payment_count":2,"instrument_group":"group-b","settlement_minutes":20},{"date":"2026-10-03","row_id":"row-3","payment_count":3,"instrument_group":"group-a","settlement_minutes":15},{"date":"2026-10-04","row_id":"row-4","payment_count":4,"instrument_group":"group-b","settlement_minutes":30}],"maxItems":200,"minItems":1},"field":{"enum":["settlement_minutes","payment_count"],"type":"string","default":"settlement_minutes"}}},"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_Orhg48CR8B9jKAIa2znl1","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 string normalisation and adjacent-row change detection on settlement timing records (settlement_minutes, payment_count) for up to 200 rows, returning two analytical reports.","exampleAgentPrompt":"Can you run string normalisation and adjacent-row change detection on these settlement timing records? I have 4 rows with columns row_id, instrument_group, date, settlement_minutes, and payment_count — analyse the settlement_minutes field across rows row-1 through row-4 covering 2026-10-01 to 2026-10-04.","exampleUseCases":[{"title":"Audit settlement minute shifts across dates","prompt":"I have a batch of 50 settlement timing records by instrument group and date — can you run adjacent-row change detection on the settlement_minutes field so I can see where timing shifted between consecutive entries?"},{"title":"Normalise instrument group strings in payment data","prompt":"Some of my instrument group labels in these settlement records have inconsistent capitalisation and spacing — can you run string normalisation on all 120 rows so they're clean and consistent?"},{"title":"Track payment count changes row by row","prompt":"I need to know where payment_count jumps between consecutive rows in this settlement dataset — run the adjacent-row changes report on payment_count for these 80 records grouped by instrument group and date."}],"resultDescription":"Two analytical reports: (1) string normalisation results for the selected field across all supplied rows, standardising instrument_group and other string values; (2) adjacent row change detection showing value differences between consecutive rows for the chosen numeric field (settlement_minutes or payment_count). Covers up to 200 input rows with no external lookups.","failureModes":["More than 200 rows submitted — request exceeds maxItems limit","Missing required fields (row_id, instrument_group, date, settlement_minutes, payment_count) causes validation error","Invalid date format (not YYYY-MM-DD) rejected by pattern constraint","Numeric fields outside allowed range (-1000000000000 to 1000000000000) rejected","Invalid field enum value (must be 'settlement_minutes' or 'payment_count')","Empty rows array (minItems: 1) causes rejection"],"whenToPreferThis":"Choose this endpoint when you have tabular settlement timing data and need two specific local analytical operations — string normalisation and adjacent-row change detection — applied in a single call without any external data lookup or live market data. Ideal for data cleaning pipelines, sequential audit workflows, or QA checks on financial settlement records where you want both string hygiene and row-over-row delta detection at a low per-call cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:38:51.975Z","isFirstParty":false,"canonicalSlug":"settlement-timing-string-normalisation-adjacent-row-changes-4a672875"}