{"uid":"cap_XaCrJLYt9Jcd4hewKubPj","slug":"brand-mention-inventories-string-normalisation-secondary-measure-fddb1d6d","name":"Brand Mention Inventories — String Normalisation + Secondary-Measure Weighted Mean","description":"Brand mention inventories — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied brand mention inventories records (mention_count, source_count). 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-18-034?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},"field":{"enum":["mention_count","source_count"],"type":"string","default":"mention_count"}}},"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_FllMMLpDffnoVKq7rDZm4","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 brand mention inventory strings and computes a source-count-weighted mean for mention_count or source_count across up to 200 rows, producing 2 independent analytical reports.","exampleAgentPrompt":"I have brand mention inventory records for two company groups over the past week — can you normalize the strings and calculate the source-count weighted mean for mention_count? Here are up to 50 rows with row_id, company_group, date, mention_count, and source_count fields.","exampleUseCases":[{"title":"Weekly brand mention summary by group","prompt":"I've got 80 rows of brand mention data for three company groups over the last month — each row has a row_id, company_group, date, mention_count, and source_count. Can you normalize the strings and give me the source-count weighted mean for mention_count across all of them?"},{"title":"Comparing source reach across brand groups","prompt":"I want to understand how source_count is distributed across my brand monitoring data — here are 120 rows covering group-a and group-b. Please normalize the entries and compute the weighted mean using mention_count as the weight, targeting source_count as the field."},{"title":"Data quality pass before brand reporting","prompt":"Before I put together our monthly brand report, can you run a string normalisation and weighted mean calculation on these 60 brand mention inventory rows? Use mention_count as the field and source_count as the secondary measure weight — I need the two reports this endpoint provides."}],"resultDescription":"Returns 2 independent analytical reports: one covering string normalisation of company_group and date fields, and one providing a secondary-measure weighted mean (e.g. mention_count weighted by source_count or vice versa) aggregated across the supplied rows. No external data is fetched; all computation is local to the supplied dataset of up to 200 rows.","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, company_group, date, mention_count, source_count) cause validation errors","Null values in the weight field (source_count) may cause division-by-zero or skewed weighted mean","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Empty rows array rejected (minItems: 1)","Numeric values outside ±1,000,000,000,000 boundary cause schema rejection"],"whenToPreferThis":"Choose this endpoint when you have brand mention inventory tabular data (up to 200 rows) and need both string normalisation of group/date fields and a secondary-measure weighted mean statistic in a single low-cost call ($0.01 USDC for 2 reports). Prefer it over generic analytics tools when working specifically with mention_count and source_count brand monitoring fields and you want local analytical computation without any live lookup or external data dependency.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T12:44:27.460Z","isFirstParty":false,"canonicalSlug":"brand-mention-inventories-string-normalisation-secondary-measure-fddb1d6d"}