{"uid":"cap_1wUbBX8-q-ixhOsfJ5KY3","slug":"brand-mention-inventories-category-frequencies-iqr-outlier-flags-ec2c864f","name":"Brand Mention Inventories — Category Frequencies + IQR Outlier Flags","description":"Brand mention inventories — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags 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-18-107?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_oMmpD91M6E62vK_T7OkLd","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":"Computes category frequencies and IQR-based outlier flags for brand mention inventory records (mention_count or source_count) across company groups, delivering two analytical reports for up to 200 rows.","exampleAgentPrompt":"Analyze these brand mention records for group-a and group-b across October 2026 — give me the category frequencies and flag any IQR outliers in the mention_count field. I have about 50 rows to run through.","exampleUseCases":[{"title":"Detecting spike days in brand mentions","prompt":"I have 120 rows of daily brand mention data for our top 5 company groups — can you run category frequencies and IQR outlier detection on the mention_count field so I can spot which days had abnormally high or low coverage?"},{"title":"Source diversity audit for PR campaign","prompt":"We tracked brand mentions across 80 records with source_count and mention_count — run the category frequency and IQR outlier reports on source_count so I can see which company groups had unusually narrow or broad source spread."},{"title":"Weekly brand monitoring data QA","prompt":"Before I finalize this week's brand mention inventory report (about 150 rows, grouped by company_group), can you compute the category frequencies and flag any IQR outliers in mention_count so I can catch data quality issues?"}],"resultDescription":"Two analytical reports: (1) category frequency counts for each company_group in the submitted rows, and (2) IQR-based outlier flags identifying which rows have mention_count or source_count values that fall outside the interquartile range. Results are derived entirely from the supplied data with no external lookups.","failureModes":["Fewer than 1 row submitted — minimum row requirement not met","More than 200 rows submitted — exceeds maximum batch size","Missing required fields (row_id, company_group, date, mention_count, source_count) on any row — validation error","Invalid date format (not YYYY-MM-DD) — pattern mismatch rejection","Field selector not one of 'mention_count' or 'source_count' — enum validation failure","Numeric values outside allowed range (±1,000,000,000,000) — schema rejection","Payment not provided or insufficient — x402 payment required"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of brand mention inventory data and need both a category frequency breakdown and IQR outlier detection in a single call. It is ideal for local, offline-style statistical analysis with no external data dependencies — suitable for QA passes, anomaly triage, or summarizing brand monitoring exports. Prefer it over general-purpose analytics tools when you want a structured two-report output (frequencies + outlier flags) specifically calibrated for mention_count and source_count fields.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T18:57:18.186Z","isFirstParty":false,"canonicalSlug":"brand-mention-inventories-category-frequencies-iqr-outlier-flags-ec2c864f"}