{"uid":"cap_FieVniVDmBhWYf5cA_G_7","slug":"returns-handling-data-quality-suite-audit-normalise-deduplicate-268b1d9d","name":"Returns Handling Data Quality Suite — Audit, Normalise & Deduplicate","description":"Returns handling — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication for supplied returns handling records (returned_units, processing_minutes). 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-retail-04-191?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","returned_units","processing_minutes"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"store_group":{"type":"string","default":"","maxLength":80},"returned_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"processing_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","store_group":"group-a","returned_units":10,"processing_minutes":1},{"date":"2026-10-02","row_id":"row-2","store_group":"group-b","returned_units":20,"processing_minutes":2},{"date":"2026-10-03","row_id":"row-3","store_group":"group-a","returned_units":15,"processing_minutes":3},{"date":"2026-10-04","row_id":"row-4","store_group":"group-b","returned_units":30,"processing_minutes":4}],"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_WrCGE-vn9fdP6jKREXI_O","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 returns handling records: a record quality audit, string normalisation, and exact row deduplication — for up to 200 rows of returned_units and processing_minutes data.","exampleAgentPrompt":"Can you run a data quality audit, string normalisation, and exact row deduplication on these returns handling records — I have about 50 rows with store_group, date, returned_units, and processing_minutes fields and want three separate reports back?","exampleUseCases":[{"title":"Pre-analysis returns data cleanup","prompt":"I've got 120 rows of store returns data with returned_units and processing_minutes per store group and date — can you run a quality audit plus deduplicate any exact duplicate rows before I load it into my dashboard?"},{"title":"Detecting dirty strings in returns records","prompt":"Our returns processing pipeline has inconsistent store group names — things like extra spaces and mixed casing — can you normalise the strings in these 80 returns records and also flag any quality issues in the returned_units column?"},{"title":"Monthly returns reconciliation hygiene","prompt":"Before I send the monthly returns report to finance, can you check these 200 rows for duplicate records, run a full quality audit, and normalise any string fields — the data has returned_units and processing_minutes by store group and date?"}],"resultDescription":"Three independent analytical reports covering: (1) a record quality audit flagging missing, null, or out-of-range values in returned_units and processing_minutes; (2) a string normalisation report identifying and correcting inconsistent string formatting in fields like store_group; and (3) an exact row deduplication report identifying perfectly duplicated rows across all fields. All processing is performed locally with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Malformed date strings not matching YYYY-MM-DD pattern — validation error","Missing required fields (row_id, store_group, date, returned_units, processing_minutes) — schema validation failure","Empty rows array — minimum 1 item required","Numeric values outside allowed range (-1e12 to 1e12) — schema rejection","Payment not included or insufficient USDC — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you need three simultaneous data hygiene operations — quality auditing, string normalisation, and exact deduplication — on retail returns handling records in a single low-cost call. It is ideal for pre-processing pipelines where returned_units and processing_minutes data needs to be cleaned before analysis or reporting. Prefer this over general-purpose data tools when your dataset is under 200 rows and you want bundled reports without external data lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:38:51.941Z","isFirstParty":false,"canonicalSlug":"returns-handling-data-quality-suite-audit-normalise-deduplicate-268b1d9d"}