{"uid":"cap_kFURfmE8IemEHur0rhZrv","slug":"partnership-pipeline-record-quality-audit-string-normalisation-25855e2c","name":"Partnership Pipeline — Record Quality Audit + String Normalisation + Explicit Missing-Value Fill","description":"Partnership pipeline — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill for supplied partnership pipeline records (qualified_partners, active_partners). 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-09-208?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","qualified_partners","active_partners"],"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},"active_partners":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"qualified_partners":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","active_partners":1,"qualified_partners":10},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","active_partners":2,"qualified_partners":20},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","active_partners":3,"qualified_partners":15},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","active_partners":4,"qualified_partners":30}],"maxItems":200,"minItems":1},"field":{"enum":["qualified_partners","active_partners"],"type":"string","default":"qualified_partners"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_YPLeqCLOEd6iGSl828_xv","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, normalises, and fills missing values in partnership pipeline records (qualified_partners, active_partners) for up to 200 rows, returning 3 independent analytical reports.","exampleAgentPrompt":"Can you audit the quality of my partnership pipeline records, normalise the company_group strings, and fill any missing qualified_partners values using median imputation? Here are my rows: [{\"row_id\":\"r1\",\"company_group\":\"Group A\",\"date\":\"2025-01-01\",\"qualified_partners\":10,\"active_partners\":null},{\"row_id\":\"r2\",\"company_group\":\"group-a\",\"date\":\"2025-01-02\",\"qualified_partners\":null,\"active_partners\":3}].","exampleUseCases":[{"title":"Pre-analysis partner data cleanup","prompt":"I have 150 rows of partnership pipeline data with inconsistent company names and some null values in active_partners — can you run a quality audit, normalise the strings, and fill those nulls using the mean across the dataset?"},{"title":"Monthly partner reporting data validation","prompt":"Before I generate my monthly partner report, please audit these 80 partnership records for quality issues, standardise the company_group field, and fill any missing qualified_partners entries with zero so nothing is left blank."},{"title":"CRM data migration quality check","prompt":"We're migrating partner records to a new CRM — run a record quality audit, string normalisation, and median-based missing-value fill on these 200 rows covering qualified_partners so I can catch problems before the import."}],"resultDescription":"Three independent reports: (1) a record quality audit flagging issues such as malformed dates, out-of-range values, or duplicate row IDs; (2) a string normalisation report detailing transformations applied to text fields like company_group; (3) an explicit missing-value fill report showing which cells in the chosen field (qualified_partners or active_partners) were imputed and with what value (zero, mean, or median). All reports are generated locally from the supplied data with no external lookups.","failureModes":["Rows array is empty or exceeds 200 items — request rejected with validation error","row_id is missing or blank — schema validation failure","date field does not match YYYY-MM-DD pattern — validation error","Numeric values outside ±1,000,000,000,000 range — schema rejection","Invalid method enum value (not zero/mean/median) — validation error","Invalid field enum value (not qualified_partners/active_partners) — validation error","Payment not confirmed via x402 protocol — request blocked"],"whenToPreferThis":"Choose this endpoint when you need a bundled, cost-effective ($0.01 USDC) trio of data quality operations — audit, string normalisation, and missing-value imputation — on partnership pipeline records in a single call. It is ideal for pre-analysis cleanup, CRM migration validation, or routine data hygiene on up to 200 partner rows. Prefer it over single-operation endpoints when all three operations are needed simultaneously on the same dataset.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:57.595Z","isFirstParty":false,"canonicalSlug":"partnership-pipeline-record-quality-audit-string-normalisation-25855e2c"}