{"uid":"cap_5D2Z_a8-j_eRAakSSKSqt","slug":"brand-mention-inventories-record-quality-audit-string-normalisation-cadcde81","name":"Brand Mention Inventories — Record Quality Audit, String Normalisation & Exact Row Deduplication","description":"Brand mention inventories — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication for supplied brand mention inventories records (mention_count, source_count). 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-18-191?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","mention_count","source_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"mention_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_count":1,"company_group":"group-a","mention_count":10},{"date":"2026-10-02","row_id":"row-2","source_count":2,"company_group":"group-b","mention_count":20},{"date":"2026-10-03","row_id":"row-3","source_count":3,"company_group":"group-a","mention_count":15},{"date":"2026-10-04","row_id":"row-4","source_count":4,"company_group":"group-b","mention_count":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_2_2JBiYnDtO6TjGksrjLu","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, normalises strings, and deduplicates up to 200 rows of brand mention inventory records (mention_count, source_count), producing 3 independent analytical reports.","exampleAgentPrompt":"Can you audit, normalise, and deduplicate my brand mention inventory data? I have rows like {row_id: 'row-1', company_group: 'group-a', date: '2026-10-01', mention_count: 10, source_count: 1} — up to 50 rows total — and I need all three reports: record quality audit, string normalisation, and exact row deduplication.","exampleUseCases":[{"title":"Pre-analysis brand mention data cleanup","prompt":"I have about 120 rows of brand mention inventory data with company_group names that may have inconsistent casing and some duplicate rows — can you run a full quality audit, normalise the strings, and flag exact duplicates before I load this into my dashboard?"},{"title":"Validating merged mention datasets","prompt":"I just merged two brand mention feeds into one dataset of around 80 rows with mention_count and source_count fields — can you check for record quality issues, normalise the company_group strings, and deduplicate any exact duplicate rows for me?"},{"title":"Routine weekly brand mention data hygiene","prompt":"Here are this week's 60 brand mention inventory rows across several company groups — please run the record quality audit, string normalisation, and exact row deduplication reports so I can spot any data issues before reporting."}],"resultDescription":"Three independent analytical reports covering: (1) a record quality audit highlighting data quality issues in the supplied rows, (2) a string normalisation report showing standardised versions of string fields such as company_group, and (3) an exact row deduplication report identifying and removing duplicate entries — all derived from the supplied brand mention inventory data without any external lookups or live data.","failureModes":["Submitting more than 200 rows returns an error due to the maxItems limit","Missing required fields (row_id, company_group, date, mention_count, source_count) cause validation failure","Invalid date format (not YYYY-MM-DD) triggers schema validation error","Empty rows array (minItems: 1 not met) returns an error","Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) may be rejected","Payment failure via x402 protocol prevents report generation"],"whenToPreferThis":"Choose this endpoint when you need a combined record quality audit, string normalisation, and exact row deduplication on brand mention inventory data (mention_count, source_count fields) in a single low-cost call. It is ideal for pre-processing brand monitoring datasets before dashboarding or analysis, and when you want three distinct analytical reports from one submission of up to 200 rows without relying on external lookups or live data sources.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T12:48:51.778Z","isFirstParty":false,"canonicalSlug":"brand-mention-inventories-record-quality-audit-string-normalisation-cadcde81"}