{"uid":"cap_a5T4Kldj8YFxV4niEO2Cg","slug":"transport-ridership-duplicate-key-report-numeric-interval-filter-b24617eb","name":"Transport Ridership Duplicate Key Report & Numeric Interval Filter","description":"Transport ridership — Duplicate key report + Numeric interval filter: Duplicate key report + Numeric interval filter for supplied transport ridership records (passenger_count, service_count). 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-economics-05-059?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","region","date","passenger_count","service_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"region":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"service_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"passenger_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","service_count":1,"passenger_count":10},{"date":"2026-10-02","region":"group-b","row_id":"row-2","service_count":2,"passenger_count":20},{"date":"2026-10-03","region":"group-a","row_id":"row-3","service_count":3,"passenger_count":15},{"date":"2026-10-04","region":"group-b","row_id":"row-4","service_count":4,"passenger_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["passenger_count","service_count"],"type":"string","default":"passenger_count"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_ZxFrZ1eCd6Q3oFfUZONf0","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 two local analytical reports on supplied transport ridership data: identifies duplicate row keys and filters rows by a numeric interval on passenger or service counts.","exampleAgentPrompt":"Can you check my transport ridership records for duplicate row IDs and also filter them to only show rows where passenger_count is between 50 and 500? Here are the rows: row-1 (2026-10-01, group-a, passenger_count=10, service_count=1), row-2 (2026-10-02, group-b, passenger_count=200, service_count=2), row-1 (2026-10-03, group-a, passenger_count=450, service_count=3).","exampleUseCases":[{"title":"Transit data ingestion quality check","prompt":"I just received a batch of 150 ridership records from our regional transit authority — can you scan them for any duplicate row IDs and also pull out only the rows where passenger_count falls between 100 and 2000?"},{"title":"Service count anomaly bounding","prompt":"We have daily service count data across multiple regions. Can you run two reports: one to flag any repeated row keys, and one to filter the records where service_count is between 5 and 50?"},{"title":"Ridership upload validation before database insert","prompt":"Before I insert these transit records into our database, can you check for any duplicate row IDs and show me which rows have a passenger_count between 0 and 300? I'll share the CSV data as rows."}],"resultDescription":"Returns two analytical reports: (1) a duplicate key report listing any row_ids that appear more than once in the supplied data, and (2) a numeric interval filter report listing all rows where the selected field (passenger_count or service_count) falls within the specified minimum and maximum bounds. Up to 200 rows processed per call.","failureModes":["Empty rows array returns validation error","More than 200 rows submitted causes rejection","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Minimum greater than maximum may return empty interval filter results","Missing required fields (row_id, region, date) causes item-level rejection","Non-numeric values in passenger_count or service_count when not null cause type errors"],"whenToPreferThis":"Choose this endpoint when you need lightweight, offline data quality checks on transport ridership datasets — specifically duplicate key detection and numeric range filtering — without requiring a live database, external lookup, or ML model. Ideal for pre-ingestion validation pipelines, batch data audits, or quick ad-hoc QA on transit data exports of up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T12:41:59.573Z","isFirstParty":false,"canonicalSlug":"transport-ridership-duplicate-key-report-numeric-interval-filter-b24617eb"}