{"uid":"cap_SJE7NjERK8tB_B2_0uUIk","slug":"partnership-pipeline-record-quality-audit-string-normalisation-two-e1d10bfb","name":"Partnership Pipeline — Record Quality Audit + String Normalisation + Two-Measure Correlation","description":"Partnership pipeline — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation 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-09-204?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}}},"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_Io3H39UnRhejSuS73_gzM","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":"Runs three analytical reports on partnership pipeline data: record quality audit, string normalisation, and correlation between qualified_partners and active_partners metrics, for up to 200 rows.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and correlation analysis on my partnership pipeline data? I have 4 rows: row-1 on 2026-10-01 for group-a with 10 qualified_partners and 1 active_partners, row-2 on 2026-10-02 for group-b with 20 qualified and 2 active, row-3 on 2026-10-03 for group-a with 15 qualified and 3 active, and row-4 on 2026-10-04 for group-b with 30 qualified and 4 active.","exampleUseCases":[{"title":"Partner data quality check before quarterly review","prompt":"Before our quarterly review, can you audit these 50 partnership pipeline records for quality issues, normalise the company group names, and tell me how correlated our qualified_partners and active_partners numbers are? Here are the rows with dates, row IDs, group names, and both metrics."},{"title":"Detecting string inconsistencies in CRM export","prompt":"I just exported our partner CRM data and I think the company_group field has a lot of inconsistent naming — can you run a string normalisation report and a quality audit on these 120 rows so I can see what needs cleaning? Also include the correlation between qualified and active partners."},{"title":"Validating pipeline data before dashboard load","prompt":"Before we load this partnership pipeline data into our dashboard, can you run a quality audit and check the correlation between qualified_partners and active_partners for these 80 rows? Also normalise the string fields so we catch any formatting issues."}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit flagging missing values, out-of-range numbers, malformed dates, or structural issues per row; (2) a string normalisation report showing standardised versions of text fields like company_group; and (3) a two-measure correlation report quantifying the statistical relationship between qualified_partners and active_partners across all supplied rows. No external data or live lookups are used — all analysis is performed on the supplied rows only.","failureModes":["Empty rows array or missing required fields (row_id, date, company_group) returns validation error","More than 200 rows submitted — exceeds maxItems limit, request rejected","Malformed date strings not matching YYYY-MM-DD pattern cause schema validation failure","All null values in qualified_partners or active_partners may prevent meaningful correlation computation","Numeric values outside ±1,000,000,000,000 range rejected by schema","Payment of 0.01 USDC not included or declined causes x402 payment-required error"],"whenToPreferThis":"Choose this endpoint when you need to run three complementary data-quality and analytical operations on partnership pipeline data in a single low-cost API call, rather than calling separate endpoints for each report. It is ideal for batch pre-processing of CRM exports, pipeline snapshots, or periodic data validation workflows involving up to 200 rows with qualified_partners and active_partners fields. Prefer it over manual inspection or generic ETL tools when you want structured reports on string normalisation, record quality, and metric correlation without involving external data sources or prediction models.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:39:40.522Z","isFirstParty":false,"canonicalSlug":"partnership-pipeline-record-quality-audit-string-normalisation-two-e1d10bfb"}