{"uid":"cap__DImDnsLKIk63r2mQWNOm","slug":"data-validation-results-string-normalisation-25fb8c2b","name":"Data Validation Results – String Normalisation","description":"Data validation results - String normalisation: String normalisation for Data validation results. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded string normalisation report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-validation-results-normalise?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","rule","date","checked_records","failed_records"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"rule":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"failed_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"checked_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","rule":"group-a","row_id":"row-1","failed_records":1,"checked_records":10},{"date":"2026-10-02","rule":"group-b","row_id":"row-2","failed_records":2,"checked_records":20},{"date":"2026-10-03","rule":"group-a","row_id":"row-3","failed_records":3,"checked_records":15},{"date":"2026-10-04","rule":"group-b","row_id":"row-4","failed_records":4,"checked_records":30}],"maxItems":200,"minItems":1}}},"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_Dus6WXzxj_0BL2iiIe1Pw","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":"Normalises and standardises string fields across up to 200 data validation result records, producing a bounded descriptive analytics report.","exampleAgentPrompt":"Can you normalise the string fields in these 4 data validation records? The rows have rule names like 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, and checked/failed record counts — I need a clean normalisation report across all of them.","exampleUseCases":[{"title":"QA pipeline string cleanup","prompt":"I have 50 rows from our daily data validation pipeline with inconsistent rule names and date formats — can you run string normalisation on them and give me a descriptive report showing what was standardised?"},{"title":"Audit-ready validation log standardisation","prompt":"Our audit team needs clean, normalised string fields across 120 validation result records from last month — each row has a rule, a date, and counts of checked vs failed records. Can you normalise the strings and produce a summary report?"},{"title":"Spotting rule naming inconsistencies","prompt":"We have validation results from three teams using slightly different rule name conventions — can you normalise the strings across all 80 rows so we can compare failure rates across rules consistently?"}],"resultDescription":"A bounded string normalisation report covering up to 200 validation result records, including normalised rule names, standardised date strings, and row identifiers, with local descriptive analytics summarising the normalisation applied — no external enrichment or forecasting.","failureModes":["Fewer than 1 or more than 200 rows submitted — request rejected with validation error","Missing required fields (row_id, rule, date, checked_records, failed_records) on any row — schema validation failure","Date field not matching YYYY-MM-DD pattern — rejected with pattern validation error","Rule or row_id string exceeding 80 character limit — truncation or rejection","checked_records or failed_records outside the allowed numeric range — validation error","Payment of 0.01 USDC not provided via x402 protocol — payment required error"],"whenToPreferThis":"Choose this endpoint when you have structured data validation result records with string fields (rule names, row IDs, dates) that need normalisation and you want a lightweight, local descriptive analytics report for up to 200 records at very low cost. Prefer this over general-purpose string cleaning tools when your data specifically follows the validation results schema (row_id, rule, date, checked_records, failed_records) and you need a bounded, repeatable normalisation run without external enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T19:16:41.879Z","isFirstParty":false,"canonicalSlug":"data-validation-results-string-normalisation-25fb8c2b"}