{"uid":"cap_oOl2pezYdUDVaywAY6J28","slug":"brand-mention-inventories-string-normalisation-base-100-series-36732dcd","name":"Brand Mention Inventories — String Normalisation + Base-100 Series","description":"Brand mention inventories — String normalisation + Base-100 series: String normalisation + Base-100 series 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-18-030?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_CAuInK2b2i-kXHhU5gUyt","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 computes Base-100 indexed time series for brand mention inventory data (mention_count, source_count) across up to 200 rows in two independent analytical reports.","exampleAgentPrompt":"Can you normalize my brand mention data and produce a base-100 indexed series for mention_count starting at row index 0? I have records for company groups 'group-a' and 'group-b' with dates and mention counts I'll supply — up to 50 rows.","exampleUseCases":[{"title":"Benchmark brand mentions over time","prompt":"I have 60 rows of daily brand mention counts for three company groups spanning Q3. Can you normalize the strings and give me a base-100 index series for mention_count starting from the first row so I can compare their relative growth?"},{"title":"Source diversity indexing for PR report","prompt":"I want to track how our source_count for brand coverage has grown relative to a baseline. Can you run string normalization and produce a base-100 series on source_count for my 120-row inventory dataset starting at row index 0?"},{"title":"Multi-brand competitive mention analysis","prompt":"I've got mention_count data for four competitor brands across 90 daily rows. Please normalize the data and index it to base-100 from row 0 so I can see which brand's mentions grew the fastest relative to their starting point."}],"resultDescription":"Returns two independent analytical reports per call: (1) string-normalized versions of the supplied brand mention inventory records, and (2) a Base-100 indexed time series for the selected numeric field (mention_count or source_count), rebased from the specified row index. Both reports are computed locally with no external lookups.","failureModes":["More than 200 rows supplied — request will be rejected or truncated","Invalid date format (not YYYY-MM-DD) causes row validation failure","base_index out of range (>=number of rows) causes indexing error","Null values in numeric fields may produce gaps or errors in Base-100 series","Missing required fields (row_id, company_group, date) cause schema validation failure","Empty rows array returns error"],"whenToPreferThis":"Choose this endpoint when you have brand mention inventory data (mention_count, source_count) and need both string normalization and Base-100 indexed time series in a single cost-effective call. It handles up to 200 rows and delivers two reports for $0.01 USDC. Prefer this over generic analytics tools when your use case is specifically brand mention tracking across named company groups over time, and you need a rebased comparative index rather than raw aggregates.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T18:57:18.941Z","isFirstParty":false,"canonicalSlug":"brand-mention-inventories-string-normalisation-base-100-series-36732dcd"}