{"uid":"cap_FHn6nw6k9jywGAweK-XL1","slug":"refund-imports-csv-column-statistics-07b3607f","name":"Refund Imports CSV Column Statistics","description":"Refund imports — Column statistics: Column statistics for Refund imports. Validate a declared CSV table contract, up to 1000 rows. Quoted cells supported; no external enrichment. Specialised preset in a shared 50-profile, 20-operation engine. 0.01 USDC includes one CSV column statistics report.","url":"https://market.datapackvibe.com/x402/assistant-bx-csv-refunds-column-stats?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"csv":{"type":"string","default":"refund_id,refunded_on,order_id,refund_amount,refunded_units\nrecord-a,2026-01-01,group-a,10,2\nrecord-b,2026-01-02,group-b,20,3","maxLength":100000,"minLength":1},"maximum":{"type":"number","default":1000000000000,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":-1000000000000,"maximum":1000000000000,"minimum":-1000000000000},"delimiter":{"enum":[",",";","\t"],"type":"string","default":","},"max_cell_length":{"type":"integer","default":1000,"maximum":5000,"minimum":1},"allowed_categories":{"type":"array","items":{"type":"string","default":"","maxLength":100,"minLength":1},"default":["group-a","group-b"],"maxItems":100,"minItems":0}}},"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_KN-XNLsfs4jGWX9Tshbq_","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 per-column statistics for a refund-import CSV table, validating up to 1000 rows against a declared schema contract.","exampleAgentPrompt":"Can you run column statistics on this refund CSV — columns are refund_id, refunded_on, order_id, refund_amount, refunded_units — using a comma delimiter, with allowed categories group-a and group-b, and flag any numeric values outside -1000 to 1000000?","exampleUseCases":[{"title":"Pre-upload refund data quality check","prompt":"Before I import this refund CSV into our system, can you run column statistics on it? It's comma-delimited with columns refund_id, refunded_on, order_id, refund_amount, and refunded_units — allowed order groups are group-a, group-b, and group-c, and refund_amount should stay between 0 and 50000."},{"title":"Detect out-of-range refund amounts","prompt":"I have a CSV export of last month's refunds and I'm worried some refund_amount values got corrupted — can you profile the columns and flag anything outside the range of 0 to 10000? Delimiter is comma, and the only valid categories for order_id are tier-1 and tier-2."},{"title":"Validate refund category labels post-migration","prompt":"We just migrated our refund data and need to confirm that the refunded_units and order_id columns only contain expected categories. Can you run column stats on this CSV using a semicolon delimiter and check that categories are limited to alpha, beta, and gamma?"}],"resultDescription":"Returns a per-column statistics report covering data types, value distributions, min/max ranges for numeric columns, category membership validation against the allowed list, and cell length violations — all computed locally without external enrichment on up to 1000 rows of the submitted CSV.","failureModes":["CSV exceeds 100,000 character limit — request rejected","More than 1000 rows in CSV — rows beyond limit may be ignored or rejected","Cell exceeds max_cell_length — flagged as violation","Numeric value outside specified minimum/maximum range — flagged in report","Category value not in allowed_categories list — flagged as invalid","Malformed CSV (unbalanced quotes, wrong delimiter) — parse error returned","Empty CSV string — validation error"],"whenToPreferThis":"Choose this endpoint when you need fast, self-contained column-level profiling and validation for refund-specific CSV data — especially when you want to enforce allowed categories, numeric range bounds, and cell length constraints before importing refund records into a downstream system. It is purpose-built for the refund-import use case with a preset schema profile, making it more targeted than a generic CSV validator.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T18:47:49.201Z","isFirstParty":false,"canonicalSlug":"refund-imports-csv-column-statistics-07b3607f"}