{"uid":"cap_4fyF9NsU3W3UTuQ3dHB1Q","slug":"travel-administration-data-quality-audit-record-quality-string-f8ae6dd4","name":"Travel Administration Data Quality Audit: Record Quality, String Normalisation & IQR Outlier Flags","description":"Travel administration — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags for supplied travel administration records (trip_count, recorded_cost). 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-operations-14-203?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_s1eNCeVmr5YBgssimODBL","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":"Audits up to 200 travel administration records (trip_count, recorded_cost) producing three reports: record quality audit, string normalisation, and IQR-based outlier detection.","exampleAgentPrompt":"Can you audit these 150 travel administration records for data quality issues, normalise the team_group strings, and flag any IQR outliers in the trip_count field? Here are the rows with row_id, team_group, date, trip_count, and recorded_cost.","exampleUseCases":[{"title":"Corporate travel expense anomaly detection","prompt":"I have 180 rows of corporate travel data with trip counts and recorded costs per team group. Can you run an IQR outlier check on recorded_cost and also do a full record quality audit and string normalisation on the team_group column?"},{"title":"Monthly travel data cleansing before reporting","prompt":"Before I submit our monthly travel report, can you audit these 200 travel administration records for quality issues, normalise the team_group strings, and flag any outliers in trip_count using IQR? I need all three reports."},{"title":"Identifying bad data in multi-team travel dataset","prompt":"We've got travel records across about 12 team groups and I suspect there are some dodgy entries. Can you run a record quality audit, string normalisation, and IQR outlier detection on the trip_count field across these rows?"}],"resultDescription":"Three independent analytical reports: (1) a record quality audit identifying missing values, invalid formats, or constraint violations per row; (2) a string normalisation report showing standardised versions of string fields like team_group; (3) an IQR outlier flags report identifying rows where the chosen numeric field (trip_count or recorded_cost) falls outside the interquartile range bounds. All analysis is performed locally on the supplied data with no external lookups.","failureModes":["Exceeding 200 rows returns an error — batch must be split","Missing required fields (row_id, date, trip_count, recorded_cost) causes validation failure","Invalid date format (not YYYY-MM-DD) triggers schema rejection","Numeric values outside ±1,000,000,000,000 bounds rejected","Empty rows array not accepted (minItems: 1)","Invalid field enum value (must be 'trip_count' or 'recorded_cost') causes error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 travel administration records and need all three of: data quality auditing, string normalisation, and IQR outlier detection in a single $0.01 call. It is ideal for pre-reporting data cleansing pipelines, travel expense validation workflows, or ad-hoc data hygiene checks on team-level trip and cost data. Prefer this over general-purpose data tools when your data specifically contains trip_count and recorded_cost fields organised by team_group and date.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:51:42.769Z","isFirstParty":false,"canonicalSlug":"travel-administration-data-quality-audit-record-quality-string-f8ae6dd4"}