{"uid":"cap_C4mCp_fNnF-XPRnisme-l","slug":"account-research-coverage-record-quality-audit-iqr-outlier-flags-3f1a9c9f","name":"Account Research Coverage — Record Quality Audit + IQR Outlier Flags","description":"Account research coverage — Record quality audit + IQR outlier flags: Record quality audit + 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-08-014?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_xNvG327P0UPCVPl9adQAx","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":"Audits up to 200 account research coverage records for quality issues and flags IQR-based outliers across researched_accounts and target_accounts fields, producing two independent analytical reports.","exampleAgentPrompt":"Can you audit this batch of account research coverage records for data quality issues and flag any IQR outliers in the researched_accounts field? I have about 50 rows across groups like 'group-a' and 'group-b' with dates from 2025-01-01 to 2025-03-31.","exampleUseCases":[{"title":"Sales team coverage data health check","prompt":"We just pulled our Q1 account research coverage data — about 120 rows with researched_accounts and target_accounts across 5 company groups. Can you run a record quality audit on it and flag any IQR outliers in researched_accounts so we know which rows look suspicious before we report upward?"},{"title":"Target accounts anomaly detection before CRM import","prompt":"Before we import these 80 target_accounts rows into our CRM, can you audit them for record quality issues and use IQR outlier detection to flag any rows with unusual target_accounts values? The data spans multiple company groups from 2025-01-01 through 2025-06-30."},{"title":"Identifying dirty data in account research pipeline","prompt":"Our account research pipeline produced 200 rows of coverage data last week and I think there are some bad records mixed in. Can you do a full quality audit and IQR outlier check on the researched_accounts field so I can see which rows to investigate or drop?"}],"resultDescription":"Two independent reports: (1) a record quality audit identifying missing values, type errors, and other data integrity issues across the supplied rows; (2) an IQR-based outlier flag report identifying rows with statistically anomalous values in the selected field (researched_accounts or target_accounts). No external lookups or live data are used — all analysis runs on the supplied data only.","failureModes":["Submitting more than 200 rows returns an error — batch must be split","Missing required fields (row_id, date, company_group, researched_accounts, target_accounts) causes row-level validation failure","Malformed date strings not matching YYYY-MM-DD pattern are rejected","Null numeric values are accepted but may reduce outlier detection effectiveness","Fewer than 4-5 rows may produce unreliable IQR calculations"],"whenToPreferThis":"Use this endpoint when you need a low-cost ($0.01), offline quality audit of account research coverage data without any live lookups or external enrichment. Ideal for pre-import validation pipelines, periodic data health checks on CRM or research exports, and when you need both a general record quality report and IQR-based outlier detection in a single call on up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:33.241Z","isFirstParty":false,"canonicalSlug":"account-research-coverage-record-quality-audit-iqr-outlier-flags-3f1a9c9f"}