{"uid":"cap_JxRvKzfrUXRurHftZqT5j","slug":"account-research-coverage-record-quality-audit-string-normalisation-529fadbd","name":"Account Research Coverage — Record Quality Audit, String Normalisation & IQR Outlier Flags","description":"Account research coverage — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags for supplied account research coverage records (researched_accounts, target_accounts). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-company-08-203?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_NiuEnIntP4LpdmBTqu4Nh","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 record quality, normalises strings, and flags IQR-based outliers for account research coverage data (researched_accounts, target_accounts) across up to 200 rows, producing 3 independent analytical reports.","exampleAgentPrompt":"Can you audit my account research coverage data for quality issues, normalise the company group names, and flag any IQR outliers in the researched_accounts field? Here are my rows: row-1, 2024-01-15, group-a, researched_accounts=120, target_accounts=150; row-2, 2024-01-16, group-b, researched_accounts=5, target_accounts=200.","exampleUseCases":[{"title":"Sales pipeline coverage data quality check","prompt":"I have a spreadsheet of researched vs target accounts per company group over the last month — can you run a full quality audit on it, normalise the company group names, and flag any rows where the researched_accounts numbers look like statistical outliers?"},{"title":"CRM account data cleanup before reporting","prompt":"Before I send my quarterly account coverage report, can you check these 150 rows of researched_accounts and target_accounts data for record quality issues and string inconsistencies in the company_group field, and highlight anything that looks out of range using IQR outlier detection?"},{"title":"Anomaly detection in account research metrics","prompt":"Something looks off in our target_accounts numbers this week — can you run an IQR outlier analysis on the target_accounts field across these records grouped by company group and date, and also give me the record quality and string normalisation reports while you're at it?"}],"resultDescription":"Three independent reports: (1) a record quality audit identifying missing, malformed, or incomplete fields; (2) a string normalisation report standardising company_group and other string fields; and (3) IQR-based outlier flags identifying statistically anomalous values in the selected numeric field (researched_accounts or target_accounts), all computed locally without any external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, company_group) causes row-level rejection","Invalid date format (non-YYYY-MM-DD) triggers schema validation failure","Numeric values outside ±1,000,000,000,000 boundary are rejected","Empty rows array returns an error","Unsupported field enum value causes request failure"],"whenToPreferThis":"Choose this endpoint when you need a low-cost, self-contained, three-in-one data quality pass on account research coverage records — specifically combining record auditing, string normalisation, and IQR outlier detection in a single call. Ideal for sales ops, RevOps, or BI teams preparing account coverage data for reporting or CRM ingestion. Prefer this over general-purpose data tools when your data involves researched_accounts and target_accounts fields grouped by company and date, and you want no external data lookups or predictions — just local analytical computation.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:05.169Z","isFirstParty":false,"canonicalSlug":"account-research-coverage-record-quality-audit-string-normalisation-529fadbd"}