{"uid":"cap_VDNeK-cAXfK7pzAPdamra","slug":"contact-record-quality-string-normalisation-numeric-row-ordering-37923483","name":"Contact Record Quality — String Normalisation + Numeric Row Ordering","description":"Contact record quality — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied contact record quality records (checked_records, duplicate_records). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-company-03-025?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","checked_records","duplicate_records"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_group":{"type":"string","default":"","maxLength":80},"checked_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"duplicate_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","checked_records":10,"duplicate_records":1},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","checked_records":20,"duplicate_records":2},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","checked_records":15,"duplicate_records":3},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","checked_records":30,"duplicate_records":4}],"maxItems":200,"minItems":1},"field":{"enum":["checked_records","duplicate_records"],"type":"string","default":"checked_records"}}},"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_TBVhavOCUMVKXAcgTwIK6","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 string fields and orders rows numerically for up to 200 contact record quality data rows, producing two independent reports on checked_records and duplicate_records.","exampleAgentPrompt":"Can you normalise and numerically rank these contact quality records for me? I have 4 rows — group-a on 2026-10-01 with 10 checked and 1 duplicate, group-b on 2026-10-02 with 20 checked and 2 duplicates, group-a on 2026-10-03 with 15 checked and 3 duplicates, and group-b on 2026-10-04 with 30 checked and 4 duplicates — run it on the checked_records field and give me both reports.","exampleUseCases":[{"title":"Weekly duplicate audit by company group","prompt":"I've got a week's worth of contact record quality data across two company groups — can you normalise the strings and rank all 7 rows by duplicate_records so I can see which group has the most duplicates?"},{"title":"Monthly checked-records trend ranking","prompt":"Here are 15 rows of contact quality data from last month across our different company groups, each with a date, checked_records count, and duplicate_records count — please normalise the strings and give me a numeric row ordering by checked_records so I can spot the outliers."},{"title":"CRM data hygiene report for two teams","prompt":"We're auditing our CRM quality for teams alpha and beta — I have 30 rows with dates, checked record counts, and duplicate counts. Can you run the string normalisation and numeric ordering reports on checked_records so I can see how they compare?"}],"resultDescription":"Two independent analytical reports: one performing string normalisation on the supplied contact record quality rows, and one providing numeric ordering of rows by the selected field (checked_records or duplicate_records). Covers up to 200 input rows grouped by company_group and date, with no external lookups or predictions.","failureModes":["Fewer than 1 row submitted — minimum row count not met","More than 200 rows submitted — maxItems exceeded, request rejected","Invalid date format (not YYYY-MM-DD) — schema validation error","checked_records or duplicate_records value outside allowed numeric range","Missing required field (row_id, company_group, date) — validation failure","Invalid field enum value (not 'checked_records' or 'duplicate_records') — rejected"],"whenToPreferThis":"Choose this endpoint when you need lightweight, offline string normalisation and numeric ordering for contact record quality data (checked_records, duplicate_records) without requiring any live data lookups, predictions, or external integrations. It is ideal for batch preprocessing up to 200 rows at very low cost ($0.01 USDC for two reports). Prefer it over heavier analytics pipelines when the goal is simply standardising and ranking contact quality metrics by company group and date.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:06.179Z","isFirstParty":false,"canonicalSlug":"contact-record-quality-string-normalisation-numeric-row-ordering-37923483"}