{"uid":"cap_QxBpE6LFOIqvd6rFwnmEG","slug":"vendor-evaluation-exact-row-deduplication-iqr-outlier-flags-f69f0a16","name":"Vendor Evaluation — Exact Row Deduplication + IQR Outlier Flags","description":"Vendor evaluation — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags for supplied vendor evaluation records (supplied_score, maximum_score). 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-10-049?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","supplied_score","maximum_score"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_group":{"type":"string","default":"","maxLength":80},"maximum_score":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"supplied_score":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","maximum_score":1,"supplied_score":10},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","maximum_score":2,"supplied_score":20},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","maximum_score":3,"supplied_score":15},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","maximum_score":4,"supplied_score":30}],"maxItems":200,"minItems":1},"field":{"enum":["supplied_score","maximum_score"],"type":"string","default":"supplied_score"}}},"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_sPsnbWd23YOcCls0nuyg1","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":"Deduplicates vendor evaluation records by exact row matching and flags statistical outliers using IQR analysis on supplied_score or maximum_score fields.","exampleAgentPrompt":"Can you deduplicate this vendor evaluation dataset and flag any IQR outliers in the supplied_score column? I have up to 150 rows with fields: row_id, company_group, date, supplied_score, and maximum_score.","exampleUseCases":[{"title":"Procurement data quality audit","prompt":"I have a vendor evaluation spreadsheet with about 80 rows — each row has a row_id, company group, date, supplied_score, and maximum_score. Can you remove any exact duplicate rows and flag which supplied_score values look like statistical outliers using IQR?"},{"title":"Vendor scoring anomaly detection","prompt":"We just collected vendor assessment scores across 120 entries and I think there are some duplicates and weird outlier scores sneaking in. Can you run exact deduplication and IQR outlier flagging on the maximum_score field for me?"},{"title":"Pre-report vendor data cleanup","prompt":"Before I finalize my vendor performance report, can you clean up this dataset of 60 evaluation records by deduplicating exact rows and using IQR to flag any suspicious supplied_score outliers I should investigate?"}],"resultDescription":"Returns two independent analytical reports: (1) an exact row deduplication report identifying and removing duplicate vendor evaluation records, and (2) an IQR outlier flagging report marking rows whose selected numeric field (supplied_score or maximum_score) falls outside the interquartile range bounds. Up to 200 input rows are supported per call.","failureModes":["Input exceeds 200 rows — request rejected","Missing required fields (row_id, date, supplied_score, maximum_score) causes validation error","Invalid date format (not YYYY-MM-DD) causes schema rejection","Too few rows to compute meaningful IQR statistics (e.g. 1-3 rows)","Null values in selected numeric field may reduce IQR analysis coverage"],"whenToPreferThis":"Choose this endpoint when you need both exact row deduplication and IQR-based outlier detection on vendor evaluation records (supplied_score, maximum_score) in a single low-cost call. Ideal for batch data quality checks on datasets up to 200 rows before reporting or further analysis. Not suitable if you need live data lookup, predictions, external enrichment, or more than 200 rows processed at once.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:52:07.184Z","isFirstParty":false,"canonicalSlug":"vendor-evaluation-exact-row-deduplication-iqr-outlier-flags-f69f0a16"}