{"uid":"cap_Q3vBX9Uu_VFFLo2EDj37y","slug":"account-research-coverage-string-normalisation-numeric-row-ordering-4819085a","name":"Account Research Coverage — String Normalisation + Numeric Row Ordering","description":"Account research coverage — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering 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-08-025?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_mxiaIJSjoe8z0TB6cAeFv","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":"Normalises company group strings and orders rows numerically for account research coverage data (researched_accounts, target_accounts) across up to 200 rows, producing 2 analytical reports per call.","exampleAgentPrompt":"Can you clean up the company group names and sort these account research records numerically by researched_accounts? I have 4 rows: row-1 group-a 2026-10-01 with 10 researched and 1 target, row-2 group-b 2026-10-02 with 20 researched and 2 target, row-3 group-a 2026-10-03 with 15 researched and 3 target, row-4 group-b 2026-10-04 with 30 researched and 4 target — give me two reports covering both fields.","exampleUseCases":[{"title":"Clean sales territory coverage data","prompt":"I've got a messy list of account research records with inconsistent company group names — can you normalise the strings and sort everything by researched_accounts numerically? Here are the rows: row-1, group-A, 2026-11-01, 50 researched, 5 target; row-2, Group-B, 2026-11-02, 120 researched, 12 target; row-3, group-a, 2026-11-03, 75 researched, 8 target. Give me both the researched_accounts and target_accounts reports."},{"title":"Rank accounts by target count","prompt":"Please sort my account coverage rows by target_accounts and standardise the company group labels. I have: row-1 group-x 2026-09-01 researched=200 target=15, row-2 Group-X 2026-09-02 researched=180 target=22, row-3 group-y 2026-09-03 researched=95 target=9. I need the two-report output covering both metrics."},{"title":"Audit research coverage across company groups","prompt":"Can you normalise the company_group strings and produce numeric row ordering for these 5 account research records? row-1 alpha 2026-08-01 researched=300 target=30, row-2 Alpha 2026-08-02 researched=250 target=25, row-3 beta 2026-08-03 researched=400 target=40, row-4 Beta 2026-08-04 researched=350 target=35, row-5 alpha 2026-08-05 researched=500 target=50. Run both the researched_accounts and target_accounts reports."}],"resultDescription":"Two analytical reports per call: one for researched_accounts and one for target_accounts. Each report contains string-normalised company_group labels and rows ordered numerically by the selected metric. No live lookups, predictions, or external actions are performed — all analysis uses local analytical engines on the supplied data.","failureModes":["Missing required fields (row_id, company_group, date, researched_accounts, target_accounts) causes validation error","More than 200 rows submitted exceeds the maxItems limit and will be rejected","Invalid date format (not YYYY-MM-DD) triggers pattern validation failure","Numeric values outside ±1,000,000,000,000 are rejected by schema bounds","Empty rows array (minItems: 1 not met) returns error","Payment of 0.01 USDC not included or rejected blocks the request"],"whenToPreferThis":"Choose this endpoint when you have raw account research coverage records with inconsistent company group string formatting and need both string normalisation and numeric ordering applied in a single low-cost call. It is ideal for sales ops or B2B data quality workflows where you want structured reports on researched_accounts and target_accounts without requiring live data lookups, external enrichment, or predictive modelling. At $0.01 USDC for up to 200 rows and two reports, it is cost-effective for batch cleaning of coverage datasets.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:12.316Z","isFirstParty":false,"canonicalSlug":"account-research-coverage-string-normalisation-numeric-row-ordering-4819085a"}