{"uid":"cap_xz9LFxcU2FnyooDWFDuHv","slug":"customer-segment-observations-record-quality-audit-string-cd9ff45f","name":"Customer Segment Observations — Record Quality Audit + String Normalisation + Numeric Interval Filter","description":"Customer segment observations — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter for supplied customer segment observations records (account_count, revenue_amount). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-company-16-197?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","account_count","revenue_amount"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"account_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"revenue_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","account_count":10,"company_group":"group-a","revenue_amount":1},{"date":"2026-10-02","row_id":"row-2","account_count":20,"company_group":"group-b","revenue_amount":2},{"date":"2026-10-03","row_id":"row-3","account_count":15,"company_group":"group-a","revenue_amount":3},{"date":"2026-10-04","row_id":"row-4","account_count":30,"company_group":"group-b","revenue_amount":4}],"maxItems":200,"minItems":1},"field":{"enum":["account_count","revenue_amount"],"type":"string","default":"account_count"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_tXbVVdZCi-Hc1mQp9b_sP","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":"Runs three local analytical reports on customer segment observation rows: a record quality audit, string normalisation, and numeric interval filter on account_count or revenue_amount fields.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and numeric interval filter on these customer segment rows — filter account_count between 0 and 100 — and give me all three reports? I have up to 50 rows with row_id, company_group, date, account_count, and revenue_amount.","exampleUseCases":[{"title":"Segment data hygiene before CRM import","prompt":"Before I import these customer segment observations into our CRM, can you audit the record quality, normalise the company_group strings, and filter account_count between 5 and 500? I have 80 rows with row_id, company_group, date, account_count, and revenue_amount fields."},{"title":"Revenue outlier detection for monthly reporting","prompt":"I need three reports on my monthly segment observations: a quality audit, string normalisation on company names, and a numeric interval filter on revenue_amount between 1000 and 9999999 — here are 120 rows, please flag anything outside that range."},{"title":"Quarterly data validation for analytics pipeline","prompt":"Can you validate these 60 customer segment observation records — run the record quality audit, normalise the string fields, and filter account_count to only rows between 10 and 50000 — so I can confirm the data is clean before passing it to our analytics pipeline?"}],"resultDescription":"Three independent analytical reports returned for the supplied rows: (1) a record quality audit flagging issues such as missing or malformed values, (2) a string normalisation report cleaning and standardising the company_group and date text fields, and (3) a numeric interval filter report identifying rows where the selected numeric field (account_count or revenue_amount) falls within or outside the specified minimum–maximum range. All processing is local with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows supplied — request rejected","Row missing required fields (row_id, company_group, date, account_count, revenue_amount) — validation error","Date field does not match YYYY-MM-DD pattern — schema validation failure","Numeric values outside the allowed range (±1,000,000,000,000) — schema rejection","Invalid field enum value (must be account_count or revenue_amount) — parameter error","minimum greater than maximum — may produce empty interval filter results"],"whenToPreferThis":"Choose this endpoint when you need three simultaneous local data-quality operations — quality audit, string normalisation, and numeric interval filtering — on customer segment observation data (account_count, revenue_amount) in a single low-cost call. Ideal for pre-processing pipelines, CRM import validation, or analytics hygiene checks on batches up to 200 rows. Not suitable if you need live data lookup, ML predictions, or more than 200 rows per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T06:58:32.335Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-record-quality-audit-string-cd9ff45f"}