{"uid":"cap_ipdppp3BNPqRcnm4rS9NY","slug":"account-research-coverage-iqr-outlier-flags-date-by-category-pivot-8c5b9064","name":"Account Research Coverage IQR Outlier Flags + Date by Category Pivot","description":"Account research coverage — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot 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-08-178?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_mNd687x7ZCDjQMI5__9Tz","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 supplied account research coverage data (researched_accounts, target_accounts) to produce IQR-based outlier flags and a date-by-category pivot table, using local analytical engines on up to 200 rows.","exampleAgentPrompt":"Can you run IQR outlier detection and a date-by-category pivot on my account research coverage records? I have rows for company groups like 'group-a' and 'group-b' with dates and researched_accounts values — flag any outliers and pivot by date and group for up to 200 rows, analyzing the researched_accounts field.","exampleUseCases":[{"title":"Spot anomalous research coverage by team","prompt":"I have account research data across several company groups for the past quarter — can you flag any rows where researched_accounts looks like a statistical outlier using IQR, and also pivot the data by date and company group so I can see coverage patterns?"},{"title":"QA target account counts before pipeline review","prompt":"Before our pipeline meeting, can you run IQR outlier detection on our target_accounts data across all company groups and dates, and give me a date-by-category breakdown so I can spot any weird spikes or gaps?"},{"title":"Audit research effort distribution across segments","prompt":"I want to audit how research effort is distributed — can you take my 150 rows of account coverage records and produce both an IQR outlier flag report and a date-by-company-group pivot on the researched_accounts field?"}],"resultDescription":"Returns two analytical reports for the supplied dataset: (1) IQR outlier flags identifying which rows have statistically anomalous values for the selected field (researched_accounts or target_accounts), and (2) a date-by-category pivot table summarizing the selected metric broken down by date and company_group. No external data is fetched; all analysis is performed on the submitted rows.","failureModes":["Fewer than 1 row submitted — returns validation error","More than 200 rows submitted — request rejected or truncated","Invalid date format (not YYYY-MM-DD) — schema validation failure","Non-numeric values in researched_accounts or target_accounts — parse error","Missing required fields (row_id, company_group, date) — schema rejection","Too few distinct values for meaningful IQR computation — report may note insufficient data"],"whenToPreferThis":"Use this endpoint when you have account research coverage data with researched_accounts or target_accounts metrics and want both IQR-based statistical outlier detection and a date-by-category pivot in a single low-cost call. Prefer it over general BI tools when you need a quick, structured, no-setup analytical pass on up to 200 rows without requiring a live database connection or external data access.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:41.487Z","isFirstParty":false,"canonicalSlug":"account-research-coverage-iqr-outlier-flags-date-by-category-pivot-8c5b9064"}