{"uid":"cap_GezxdbNha0migo1qgtKVQ","slug":"price-quote-imports-numeric-type-check-a524a1b4","name":"Price Quote Imports — Numeric Type Check","description":"Price quote imports — Numeric type check: Numeric type check for Price quote 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-quotes-types?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"csv":{"type":"string","default":"quote_id,quoted_on,supplier_id,unit_price,minimum_quantity\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_sStQWpyKs2TMSR9fhQ5-0","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 numeric fields in a price quote CSV by checking that all declared numeric columns contain properly typed, in-range values.","exampleAgentPrompt":"Check my price quote import CSV for numeric type errors — here's the data with comma delimiter, and make sure unit_price and minimum_quantity are valid numbers between 0 and 1,000,000: quote_id,quoted_on,supplier_id,unit_price,minimum_quantity\\nrecord-a,2026-01-01,group-a,10,2\\nrecord-b,2026-01-02,group-b,20,3","exampleUseCases":[{"title":"Pre-import supplier quote validation","prompt":"Before I load this supplier quote CSV into our system, can you run a numeric type check on it to make sure unit_price and minimum_quantity columns only have valid numbers? The file uses commas as delimiters and prices should all be between 0 and 999999."},{"title":"Detecting corrupt cells in quote exports","prompt":"I exported 800 rows of price quotes from our ERP and I suspect some cells got corrupted — can you check the numeric columns for type errors and flag any rows where the values aren't proper numbers or fall outside the range of -1 to 1000000?"},{"title":"Automated quote file QA in procurement pipeline","prompt":"As part of our procurement pipeline, validate this incoming quote CSV with comma delimiter — allowed supplier categories are group-a and group-b — and tell me which rows have numeric type violations so we can reject bad records before processing."}],"resultDescription":"A CSV numeric type check report covering up to 1000 rows, identifying which cells or rows contain non-numeric values in declared numeric columns, values outside the specified min/max bounds, or type mismatches. The report indicates pass/fail status per row and details any offending cells.","failureModes":["CSV exceeds 100,000 character limit — request rejected","More than 1000 rows submitted — only first 1000 processed or error returned","Invalid delimiter value (not comma, semicolon, or tab) — validation error","Cell length exceeds max_cell_length — flagged or truncated","Malformed CSV that cannot be parsed — parsing error returned","Minimum value greater than maximum value — configuration error"],"whenToPreferThis":"Use this endpoint when you need to validate that numeric fields in a price quote CSV are properly typed and within acceptable bounds before importing into a procurement or ERP system. It is purpose-built for price quote schemas (quote_id, supplier_id, unit_price, minimum_quantity) and supports quoted cells, custom delimiters, and category allow-lists. Prefer it over generic CSV validators when your use case is specifically financial/pricing data with known numeric column contracts.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T18:47:34.957Z","isFirstParty":false,"canonicalSlug":"price-quote-imports-numeric-type-check-a524a1b4"}