{"uid":"cap_lQ_uNwy1OjOmUL-52E1lM","slug":"supplier-qualification-string-normalisation-adjacent-row-changes-a5608a34","name":"Supplier Qualification — String Normalisation + Adjacent Row Changes","description":"Supplier qualification — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied supplier qualification records (checked_criteria, met_criteria). 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-company-02-029?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","checked_criteria","met_criteria"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"met_criteria":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"checked_criteria":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","met_criteria":1,"company_group":"group-a","checked_criteria":10},{"date":"2026-10-02","row_id":"row-2","met_criteria":2,"company_group":"group-b","checked_criteria":20},{"date":"2026-10-03","row_id":"row-3","met_criteria":3,"company_group":"group-a","checked_criteria":15},{"date":"2026-10-04","row_id":"row-4","met_criteria":4,"company_group":"group-b","checked_criteria":30}],"maxItems":200,"minItems":1},"field":{"enum":["checked_criteria","met_criteria"],"type":"string","default":"checked_criteria"}}},"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_s3N9yeBufciqI50Mvi4Z8","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":"Analyzes up to 200 supplier qualification rows by performing string normalization and detecting adjacent row changes on checked_criteria or met_criteria fields, returning two analytical reports.","exampleAgentPrompt":"Can you run string normalization and adjacent row change detection on my supplier qualification records — I have 4 rows with checked_criteria values (10, 20, 15, 30) for groups group-a and group-b from October 2026, and I want to analyze the checked_criteria field?","exampleUseCases":[{"title":"Audit supplier criteria changes over time","prompt":"I have 50 rows of supplier qualification data with dates from January to March 2025, each with a company_group, checked_criteria, and met_criteria — can you normalize the strings and flag where adjacent rows show changes in the met_criteria field?"},{"title":"Standardize procurement qualification records","prompt":"Run string normalization and adjacent row change detection on these 120 supplier qualification records grouped by vendor — I want to analyze the checked_criteria field to spot inconsistencies between consecutive entries."},{"title":"Detect qualification drift across supplier groups","prompt":"I've got quarterly supplier qualification records for 6 company groups, up to 200 rows total, and I need you to normalize the data and identify adjacent row changes in the checked_criteria column to flag any drift."}],"resultDescription":"Returns two independent analytical reports for the supplied rows: (1) a string normalization report for the selected field (checked_criteria or met_criteria), and (2) an adjacent row changes report highlighting where consecutive rows differ — both computed locally without external lookups or predictions.","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, company_group, date, checked_criteria, met_criteria) — validation error","Invalid date format (must be YYYY-MM-DD) — schema validation failure","Values outside numeric range (-1,000,000,000,000 to 1,000,000,000,000) — rejection","Invalid field enum value (must be checked_criteria or met_criteria) — error","Empty rows array — minimum 1 item required"],"whenToPreferThis":"Choose this endpoint when you need to batch-process supplier qualification records (up to 200 rows) and require both string normalization and adjacent row change detection in a single low-cost call. Ideal for procurement or supply chain analysts who want to clean and audit qualification data without external lookups or live data sources. Best suited when data is already collected and needs offline analytical processing across two report types simultaneously.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T06:44:40.970Z","isFirstParty":false,"canonicalSlug":"supplier-qualification-string-normalisation-adjacent-row-changes-a5608a34"}