{"uid":"cap_O7xkRq4AQVSIqUtx-3yg4","slug":"csv-calendar-date-validation-for-training-data-ce7776b1","name":"CSV Calendar Date Validation for Training Data","description":"Training example metadata — Calendar date check: Calendar date check for Training example metadata. 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 calendar date check report.","url":"https://market.datapackvibe.com/x402/assistant-bx-csv-training-data-dates?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"csv":{"type":"string","default":"example_id,created_on,label,text_length,sample_weight\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_SJ-6wV5lcY33XyFQPbOkK","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 date columns in a CSV dataset (up to 1000 rows) against configurable min/max bounds and allowed category values, returning a calendar date check report.","exampleAgentPrompt":"Can you check the date columns in this CSV training dataset to make sure all dates fall between 2024-01-01 and 2026-12-31, using comma as the delimiter? The categories should only be group-a or group-b.","exampleUseCases":[{"title":"Pre-training data quality gate","prompt":"Before I train my model, can you validate the date fields in this CSV to make sure every date is between 2023-01-01 and 2025-12-31 and all label values are either group-a or group-b? The file uses commas as delimiters."},{"title":"Detecting out-of-range dates in exports","prompt":"I just exported a dataset from our pipeline and I need to check that the created_on column only has dates from 2025-01-01 to 2025-12-31 — can you run a calendar date validation on this CSV and flag any rows that fall outside that window?"},{"title":"Category and date audit for annotated dataset","prompt":"We have an annotated CSV with a date column and a label column — can you verify that all dates are within 2024-06-01 and 2024-09-30, and that the only allowed categories are alpha, beta, and gamma? Delimiter is a semicolon."}],"resultDescription":"A calendar date check report indicating which rows or cells contain dates outside the specified min/max bounds, malformed date values, or category values not in the allowed list. The report covers up to 1000 rows of the submitted CSV.","failureModes":["CSV exceeds 1000 rows — only the first 1000 may be processed","CSV string exceeds 100,000 character limit — request rejected","Invalid delimiter specified — only comma, semicolon, or tab are accepted","Cell exceeds max_cell_length — flagged or truncated","Malformed CSV with unmatched quotes — parse error returned","Min/max bounds are equal or inverted — may yield unexpected results","Empty CSV body — validation fails with input error"],"whenToPreferThis":"Use this endpoint when you need a lightweight, pay-per-call date column validation on a CSV dataset without setting up your own data pipeline. It is ideal for ML training data quality checks where you need to confirm date fields fall within a known range and categorical labels match a whitelist, all without sending data to an external enrichment service. Prefer it over general-purpose CSV validators when calendar date semantics and category allow-listing are the primary concern.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:54:31.461Z","isFirstParty":false,"canonicalSlug":"csv-calendar-date-validation-for-training-data-ce7776b1"}