{"uid":"cap_TXj2RjY7QC7bGQwEF1Noo","slug":"account-research-coverage-adjacent-row-changes-iqr-outlier-flags-61c1e494","name":"Account Research Coverage — Adjacent Row Changes + IQR Outlier Flags","description":"Account research coverage — Adjacent row changes + IQR outlier flags: Adjacent row changes + IQR outlier flags for supplied account research coverage records (researched_accounts, target_accounts). 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-08-157?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","researched_accounts","target_accounts"],"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},"target_accounts":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"researched_accounts":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","target_accounts":1,"researched_accounts":10},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","target_accounts":2,"researched_accounts":20},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","target_accounts":3,"researched_accounts":15},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","target_accounts":4,"researched_accounts":30}],"maxItems":200,"minItems":1},"field":{"enum":["researched_accounts","target_accounts"],"type":"string","default":"researched_accounts"}}},"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_NSa-jW3GTXYi0t2vj5p4p","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":"Analyzes up to 200 account research coverage records by computing adjacent row changes and flagging IQR-based outliers for researched_accounts or target_accounts metrics.","exampleAgentPrompt":"I have a list of up to 200 account coverage records with dates, company groups, and researched_accounts counts — can you run adjacent row change analysis and IQR outlier flagging on the researched_accounts field for me?","exampleUseCases":[{"title":"Spot anomalies in weekly account research","prompt":"I have 90 rows of weekly account research coverage data across two company groups — can you check the researched_accounts field for sudden row-over-row jumps and flag any IQR outliers?"},{"title":"Audit target account counts for data quality","prompt":"Before I finalize my quarterly report, can you run adjacent row change detection and IQR outlier flags on our target_accounts field across these 150 records grouped by company?"},{"title":"Identify coverage spikes by group","prompt":"We've got about 60 rows of account coverage data broken out by company group and date — can you analyze target_accounts for unusual adjacent changes and statistical outliers using IQR?"}],"resultDescription":"Returns two independent analytical reports: (1) adjacent row change analysis showing delta values between consecutive rows for the selected field, and (2) IQR-based outlier flags identifying rows where the metric falls outside the interquartile range boundaries — all computed locally on the supplied data with no external lookups.","failureModes":["Missing required fields (row_id, date, company_group, researched_accounts, target_accounts) cause validation errors","Submitting more than 200 rows exceeds the row limit and will be rejected","Invalid date format (non YYYY-MM-DD) triggers schema validation failure","Selecting an invalid field value outside the enum causes a request error","Null values in the selected numeric field may affect IQR and delta calculations"],"whenToPreferThis":"Choose this endpoint when you need lightweight, self-contained statistical anomaly detection on account research coverage data without any external API calls or live data enrichment. It is ideal for data quality audits, pre-reporting checks, or pipeline validation steps where you supply the rows and need both row-over-row change signals and IQR outlier flags in a single low-cost call. Prefer alternatives if you need live CRM data fetching, predictive modeling, or analysis on more than 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:49.723Z","isFirstParty":false,"canonicalSlug":"account-research-coverage-adjacent-row-changes-iqr-outlier-flags-61c1e494"}