{"uid":"cap_Z-hA5ezpwhtah9oZxN7Zv","slug":"travel-administration-numeric-distribution-iqr-outlier-flags-3b53ffcb","name":"Travel Administration — Numeric Distribution + IQR Outlier Flags","description":"Travel administration — Numeric distribution + IQR outlier flags: Numeric distribution + IQR outlier flags for supplied travel administration records (trip_count, recorded_cost). 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-operations-14-080?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","team_group","date","trip_count","recorded_cost"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"team_group":{"type":"string","default":"","maxLength":80},"trip_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"recorded_cost":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","team_group":"group-a","trip_count":10,"recorded_cost":1},{"date":"2026-10-02","row_id":"row-2","team_group":"group-b","trip_count":20,"recorded_cost":2},{"date":"2026-10-03","row_id":"row-3","team_group":"group-a","trip_count":15,"recorded_cost":3},{"date":"2026-10-04","row_id":"row-4","team_group":"group-b","trip_count":30,"recorded_cost":4}],"maxItems":200,"minItems":1},"field":{"enum":["trip_count","recorded_cost"],"type":"string","default":"trip_count"}}},"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_Xb00uDrnFfoOQToo6-e21","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 travel administration records (trip_count or recorded_cost) across up to 200 rows, returning two independent analytical reports.","exampleAgentPrompt":"Can you analyze the distribution of trip_count values in my travel records and flag any IQR outliers? Here are up to 200 rows with fields row_id, team_group, date, trip_count, and recorded_cost — I want the two-report breakdown.","exampleUseCases":[{"title":"Expense anomaly detection for finance team","prompt":"I have 150 travel expense records with trip counts and costs by team group — can you run IQR outlier detection on the recorded_cost field and tell me which rows are statistical anomalies?"},{"title":"Monthly travel distribution audit","prompt":"Here are this month's travel admin records across our regional groups. Can you compute the numeric distribution and flag outliers on trip_count so I can spot teams with unusually high or low trip volumes?"},{"title":"Data quality check before travel report submission","prompt":"Before I submit our quarterly travel report, can you check these 200 rows of travel data for IQR outliers on recorded_cost? I need to know which entries look statistically suspicious before sign-off."}],"resultDescription":"Two independent analytical reports per call: (1) a numeric distribution summary (e.g. min, max, mean, median, quartiles) and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range — all computed locally on the supplied data for either trip_count or recorded_cost.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, team_group, date, trip_count, recorded_cost) causes rejection","Invalid date format (non-YYYY-MM-DD) fails pattern validation","Null values in the selected numeric field may affect distribution computation","Insufficient data rows (fewer than 4) may produce unreliable IQR results","Payment failure or insufficient USDC balance prevents processing"],"whenToPreferThis":"Choose this endpoint when you need fast, local statistical analysis (distribution + IQR outlier detection) on travel administration data specifically structured with trip_count and recorded_cost fields, with no need for live lookups or external data enrichment. Ideal for data quality checks, expense audits, or pre-reporting anomaly detection on batches up to 200 rows at very low cost ($0.01 per call for two reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:34:15.886Z","isFirstParty":false,"canonicalSlug":"travel-administration-numeric-distribution-iqr-outlier-flags-3b53ffcb"}