{"uid":"cap_T75MGFuFlv0UrIM4JICA6","slug":"test-run-imports-numeric-type-check-6e877129","name":"Test Run Imports — Numeric Type Check","description":"Test run imports — Numeric type check: Numeric type check for Test run 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-test-runs-types?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"csv":{"type":"string","default":"run_id,executed_on,suite_id,passed_tests,failed_tests\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_hMp6Zz4HFE8IDBuHnZse8","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 CSV test-run import file contain values within specified bounds and belong to allowed categories, returning a type-check report.","exampleAgentPrompt":"Can you run a numeric type check on this test-run CSV to make sure columns like passed_tests and failed_tests are valid numbers between 0 and 10000, using a comma delimiter, and that suite_id values are only 'group-a' or 'group-b'?","exampleUseCases":[{"title":"CI pipeline CSV import gate","prompt":"Before we import these test run results into the dashboard, run a numeric type check on this CSV — comma-delimited, numbers should be between 0 and 500, and only suite IDs 'regression' and 'smoke' are allowed. Flag any rows that fail."},{"title":"QA data integrity audit","prompt":"I have a CSV export of test runs from last sprint. Can you validate that the passed_tests and failed_tests columns are all proper numbers with no stray text, values between 0 and 1000, and delimiter is a semicolon?"},{"title":"Automated test result validation before DB load","prompt":"We're about to bulk-load a test results CSV into our database. Check that all numeric fields are valid numbers, nothing below 0 or above 50000, using tab as the delimiter, and allowed suite categories are 'unit', 'integration', and 'e2e'."}],"resultDescription":"A CSV numeric type check report indicating which rows and cells pass or fail numeric type validation, including whether values fall within the specified minimum/maximum bounds and whether categorical cells match the allowed values list. Up to 1000 rows are checked per call.","failureModes":["CSV exceeds 100,000 character limit — request rejected","CSV has fewer than 1 character — request rejected","Delimiter mismatch causes all cells to be read as single column","minimum value greater than maximum value causes invalid range","Cell length exceeds max_cell_length — cells flagged or truncated","Malformed CSV quoting leads to parse errors","Non-numeric values in numeric columns reported as type violations"],"whenToPreferThis":"Choose this endpoint when you need a lightweight, low-cost ($0.01 USDC) automated check specifically for numeric type conformance in CSV files representing test run data, especially when you want to enforce value ranges and categorical constraints before importing into a test results system. Prefer it over general-purpose CSV validators when your schema includes numeric columns that must stay within defined bounds.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T18:48:52.304Z","isFirstParty":false,"canonicalSlug":"test-run-imports-numeric-type-check-6e877129"}