{"uid":"cap_SNaPNDRUBjqU62IShn8w3","slug":"supplier-qualification-numeric-distribution-iqr-outlier-flags-65195dd0","name":"Supplier Qualification — Numeric Distribution + IQR Outlier Flags","description":"Supplier qualification — Numeric distribution + IQR outlier flags: Numeric distribution + IQR outlier flags 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-02-080?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_iJKJvTcVM9f8ENlmew0sf","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":"Computes numeric distribution statistics and IQR-based outlier flags for supplier qualification records (checked_criteria, met_criteria) across up to 200 supplied rows, returning two independent analytical reports.","exampleAgentPrompt":"Can you analyze the distribution of the checked_criteria field in my supplier qualification records and flag any IQR outliers? I have these rows: row-1 group-a 2026-10-01 checked_criteria=10 met_criteria=1, row-2 group-b 2026-10-02 checked_criteria=20 met_criteria=2, row-3 group-a 2026-10-03 checked_criteria=15 met_criteria=3, row-4 group-b 2026-10-04 checked_criteria=30 met_criteria=4.","exampleUseCases":[{"title":"Outlier detection in supplier scoring","prompt":"I have 150 supplier qualification records with checked_criteria and met_criteria scores — can you run IQR outlier detection on the checked_criteria field and show me which rows are flagged as anomalous?"},{"title":"Distribution audit before vendor selection","prompt":"Before we finalize our vendor shortlist, can you give me a numeric distribution summary and IQR outlier flags for the met_criteria values across these supplier qualification rows I'm uploading?"},{"title":"Spot-check supplier data quality by group","prompt":"Can you analyze the distribution of checked_criteria in my supplier qualification data grouped by company_group, and flag any outliers using IQR so I can spot data quality issues before the quarterly review?"}],"resultDescription":"Returns two independent analytical reports: (1) a numeric distribution summary (e.g. min, max, mean, quartiles, spread metrics) for the selected field (checked_criteria or met_criteria), and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range bounds — all computed locally against the supplied data rows, with no external lookups or predictions.","failureModes":["Fewer than 1 row provided — request rejected","More than 200 rows submitted — exceeds maxItems limit","Invalid date format (not YYYY-MM-DD) — schema validation error","Missing required fields (row_id, company_group, date, checked_criteria, met_criteria) — validation failure","Invalid field selector (not 'checked_criteria' or 'met_criteria') — enum error","All numeric values are null — distribution computation may be undefined or empty","Payment of 0.01 USDC not completed — request blocked by x402 paywall"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local statistical analysis (numeric distribution + IQR outlier detection) on a small-to-medium batch of supplier qualification records (up to 200 rows) without requiring any external data enrichment, live lookups, or ML predictions. It is ideal for data quality checks before procurement decisions or vendor onboarding workflows where you want to flag anomalous checked_criteria or met_criteria values quickly and cheaply.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:39:39.890Z","isFirstParty":false,"canonicalSlug":"supplier-qualification-numeric-distribution-iqr-outlier-flags-65195dd0"}