{"uid":"cap_huvfJOvUhYpDhTKJI58sB","slug":"supplier-qualification-data-quality-suite-audit-normalise-deduplicate-ddb8423a","name":"Supplier Qualification Data Quality Suite — Audit, Normalise & Deduplicate","description":"Supplier qualification — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication for supplied supplier qualification records (checked_criteria, met_criteria). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-company-02-191?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}}},"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_JVlxfsxuLbg8Ys7r1xspI","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 three local analytical reports on supplier qualification row data: record quality audit, string normalisation, and exact row deduplication — no external lookups or predictions.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and exact deduplication check on my supplier qualification records? I have up to 50 rows with fields like row_id, company_group, date, checked_criteria, and met_criteria that I need cleaned up before importing into our procurement system.","exampleUseCases":[{"title":"Pre-import procurement data cleanse","prompt":"Before I load these 120 supplier qualification records into our ERP, can you check them for data quality issues, normalise any inconsistent company group names, and flag any exact duplicate rows? The records have row_id, company_group, date, checked_criteria, and met_criteria columns."},{"title":"Supplier audit trail validation","prompt":"I've got a batch of 80 supplier qualification audit records and I need to know if there are quality issues, any string formatting inconsistencies in the company_group field, and whether any rows are exact duplicates — can you run all three checks at once?"},{"title":"Procurement dataset deduplication check","prompt":"We're consolidating supplier qualification data from two teams — about 150 rows total — and need a deduplication report plus a quality audit and string normalisation pass on the checked_criteria and met_criteria fields before we merge them."}],"resultDescription":"Three independent analytical reports delivered together: (1) a record quality audit flagging missing, null, or out-of-range values in checked_criteria and met_criteria; (2) a string normalisation report identifying inconsistent or non-standard values in text fields like company_group; (3) an exact row deduplication report listing any fully duplicate rows across the supplied batch of up to 200 records.","failureModes":["Batch exceeds 200 rows — rejected with validation error","Missing required fields (row_id, date, checked_criteria, met_criteria) — row-level validation failure","Date field not matching YYYY-MM-DD pattern — schema rejection","Empty rows array — minItems constraint violation","Numeric fields outside allowed range (±1 trillion) — schema rejection"],"whenToPreferThis":"Choose this endpoint when you need to clean, audit, and deduplicate supplier qualification tabular data offline with no external API calls, predictions, or live lookups — ideal as a preprocessing step before loading qualification records into a procurement or ERP system. It processes up to 200 rows per call and delivers three reports for a flat $0.01 USDC, making it cost-effective for batch qualification data hygiene tasks.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:38:32.749Z","isFirstParty":false,"canonicalSlug":"supplier-qualification-data-quality-suite-audit-normalise-deduplicate-ddb8423a"}