{"uid":"cap_lud319DsicJCqVF0gDOvN","slug":"refund-imports-csv-numeric-type-check-8ac2c00d","name":"Refund Imports CSV Numeric Type Check","description":"Refund imports — Numeric type check: Numeric type check 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 numeric type check report.","url":"https://market.datapackvibe.com/x402/assistant-bx-csv-refunds-types?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_RnP90-sUX9RZHjGxEWiFP","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":"Validates that numeric columns in a refund imports CSV table contain properly typed numeric values, flagging any type violations across up to 1000 rows.","exampleAgentPrompt":"Can you run a numeric type check on this refund imports CSV — it uses comma delimiters, and I need to make sure columns like refund_amount and refunded_units only contain valid numbers between -1000000000000 and 1000000000000?","exampleUseCases":[{"title":"Pre-upload refund batch validation","prompt":"Before I import this month's refund CSV into the accounting system, can you check that all the numeric fields like refund_amount and refunded_units are actually valid numbers and nothing got corrupted? The file uses comma delimiters."},{"title":"Automated pipeline data quality gate","prompt":"I'm building a refund processing pipeline and need to validate incoming CSV files for numeric type correctness before they hit the database. Can you check this refund CSV and flag any cells that aren't valid numbers?"},{"title":"Debugging malformed refund export","prompt":"Our refund export from the old system looks broken — some amount fields might have text or symbols in them. Can you run a numeric type check on this CSV with comma delimiters to find which rows and columns have bad values?"}],"resultDescription":"A numeric type check report identifying which cells or rows in the refund imports CSV contain values that violate expected numeric types, including out-of-range values or non-numeric content in numeric columns, covering up to 1000 rows.","failureModes":["CSV exceeds 100,000 character limit — request rejected","CSV has fewer than 1 character — empty input error","More than 1000 rows submitted — may be truncated or rejected","Cell length exceeds max_cell_length setting — cell flagged or error","Invalid delimiter specified — must be comma, semicolon, or tab","Malformed CSV structure causing parse failure"],"whenToPreferThis":"Choose this endpoint when you specifically need to validate numeric data types in a refund-domain CSV file (with columns like refund_id, refunded_on, order_id, refund_amount, refunded_units) before importing into a system. It is purpose-built for the refund imports context with configurable numeric bounds and category allowlists, 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":"2026-10-12T00:57:34.885Z","isFirstParty":false,"canonicalSlug":"refund-imports-csv-numeric-type-check-8ac2c00d"}