{"uid":"cap_dYnhUMmNtDBlmHYfheFRF","slug":"business-location-inventories-record-quality-audit-string-5d75e5ce","name":"Business Location Inventories — Record Quality Audit, String Normalisation & Missing-Value Fill","description":"Business location inventories — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill for supplied business location inventories records (location_count, verified_locations). 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-05-208?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","location_count","verified_locations"],"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},"location_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"verified_locations":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","location_count":10,"verified_locations":1},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","location_count":20,"verified_locations":2},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","location_count":15,"verified_locations":3},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","location_count":30,"verified_locations":4}],"maxItems":200,"minItems":1},"field":{"enum":["location_count","verified_locations"],"type":"string","default":"location_count"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_59m1pGI4majHFGl6JZ8Ly","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":"Audits record quality, normalises strings, and fills missing values in business location inventory data (location_count, verified_locations) for up to 200 rows, producing 3 independent analytical reports.","exampleAgentPrompt":"Can you audit and clean up my business location inventory records — I have up to 50 rows with location_count and verified_locations fields, grouped by company, and I want missing location_count values filled using the median method?","exampleUseCases":[{"title":"Retail chain location audit","prompt":"I've got a CSV of 120 rows tracking location_count and verified_locations across our retail company groups by date — can you run a record quality audit, normalise the strings, and fill any missing location_count values using the mean?"},{"title":"Multi-brand inventory data cleaning","prompt":"Before I import our brand location inventory into the dashboard, can you check data quality, fix string formatting, and fill missing verified_locations values with zeros for these 80 rows across our company groups?"},{"title":"Pre-analysis data validation","prompt":"I need to validate my business location dataset of 200 rows before running analysis — run a full quality audit, normalise any inconsistent strings in company_group, and use median imputation for any missing location_count entries."}],"resultDescription":"Three independent analytical reports covering: (1) a record quality audit identifying issues in the supplied rows, (2) a string normalisation summary for text fields like company_group, and (3) an explicit missing-value fill result for the specified numeric field (location_count or verified_locations) using the chosen method (zero, mean, or median). All processing is local with no external lookups or live data enrichment.","failureModes":["Rows array is empty or exceeds 200 items — rejected with validation error","row_id missing or blank — schema requires minLength 1","date field does not match YYYY-MM-DD pattern — rejected","Numeric fields outside allowed range (±1,000,000,000,000) — rejected","Invalid enum value for field or method parameters — rejected","Payment of 0.01 USDC not completed — request blocked"],"whenToPreferThis":"Choose this endpoint when you need a lightweight, low-cost batch data quality pass on business location inventory records (location_count, verified_locations) without external API calls, live lookups, or predictions. Ideal for pre-processing pipelines where you want three bundled analytical outputs — quality audit, string normalisation, and missing-value imputation — in a single call for up to 200 rows at $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:14.203Z","isFirstParty":false,"canonicalSlug":"business-location-inventories-record-quality-audit-string-5d75e5ce"}