{"uid":"cap_y78b4L8yVBtb-LgdtVcfx","slug":"account-research-coverage-record-quality-audit-string-normalisation-9e345cc4","name":"Account Research Coverage — Record Quality Audit + String Normalisation","description":"Account research coverage — Record quality audit + String normalisation: Record quality audit + String normalisation 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-08-001?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}}},"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_flUNFrDIQ9Cf9JbciRGMg","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 and normalises strings for account research coverage data (researched_accounts, target_accounts) across up to 200 rows, producing two independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit and string normalisation on my account research coverage data? I have rows with fields like row_id, company_group, date, researched_accounts, and target_accounts — here are my 4 rows: row-1 for group-a on 2026-10-01 with 10 researched and 1 target, row-2 for group-b on 2026-10-02 with 20 researched and 2 target, row-3 for group-a on 2026-10-03 with 15 researched and 3 target, and row-4 for group-b on 2026-10-04 with 30 researched and 4 target.","exampleUseCases":[{"title":"Pre-reporting data quality check","prompt":"Before I send my weekly account research report to the team, can you audit these 50 rows of researched_accounts and target_accounts data for quality issues and normalise the company_group strings? I want to catch any nulls, bad formats, or inconsistencies first."},{"title":"CRM export validation","prompt":"I just exported 120 rows of account coverage records from our CRM with columns for row_id, company_group, date, researched_accounts, and target_accounts — can you run a record quality audit and string normalisation on all of them so I know what needs fixing before we import it into our new system?"},{"title":"Research pipeline audit","prompt":"Our research team tracks target and researched accounts across multiple company groups by date — I have 80 rows I'd like you to audit for record quality issues and normalise the company group name strings so everything is consistent."}],"resultDescription":"Returns two independent analytical reports for the supplied rows: (1) a record quality audit identifying issues such as nulls, out-of-range values, duplicate row_ids, or malformed dates across researched_accounts and target_accounts fields; and (2) a string normalisation report standardising company_group and other string fields. No external lookups or predictions are made — all analysis uses local engines.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, company_group, date, researched_accounts, target_accounts) cause row-level rejection","Invalid date format (not YYYY-MM-DD) triggers a schema error","Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) are rejected","Empty rows array (minItems:1 not met) returns an input error","Payment failure (insufficient USDC balance) blocks processing"],"whenToPreferThis":"Choose this endpoint when you need a combined record quality audit AND string normalisation for account research coverage data specifically (researched_accounts, target_accounts fields) on up to 200 rows, at a fixed low cost of $0.01 USDC for both reports. Prefer this over generic data quality tools when your data already conforms to the expected schema (row_id, company_group, date, researched_accounts, target_accounts) and you want two complementary analytical reports in one call without live lookups or external enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:17.049Z","isFirstParty":false,"canonicalSlug":"account-research-coverage-record-quality-audit-string-normalisation-9e345cc4"}