{"uid":"cap_ZV7wc5d0KXjgY7M5AONg_","slug":"knowledge-base-maintenance-numeric-distribution-two-measure-correlation-52c3629b","name":"Knowledge Base Maintenance — Numeric Distribution + Two-Measure Correlation","description":"Knowledge base maintenance — Numeric distribution + Two-measure correlation: Numeric distribution + Two-measure correlation for supplied knowledge base maintenance records (updated_articles, due_articles). 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-writing-16-081?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","document_group","date","updated_articles","due_articles"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"due_articles":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"document_group":{"type":"string","default":"","maxLength":80},"updated_articles":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","due_articles":1,"document_group":"group-a","updated_articles":10},{"date":"2026-10-02","row_id":"row-2","due_articles":2,"document_group":"group-b","updated_articles":20},{"date":"2026-10-03","row_id":"row-3","due_articles":3,"document_group":"group-a","updated_articles":15},{"date":"2026-10-04","row_id":"row-4","due_articles":4,"document_group":"group-b","updated_articles":30}],"maxItems":200,"minItems":1},"field":{"enum":["updated_articles","due_articles"],"type":"string","default":"updated_articles"}}},"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_It7nI2_s9FLvA1bw9oGZa","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":"Analyzes knowledge base maintenance records by generating a numeric distribution report and a two-measure correlation report for updated_articles and due_articles fields across up to 200 rows.","exampleAgentPrompt":"Can you run a numeric distribution and two-measure correlation analysis on my knowledge base maintenance records? Here's the data with row IDs, document groups, dates, updated_articles, and due_articles counts — I want both reports covering all 200 rows, analyzing the updated_articles field.","exampleUseCases":[{"title":"KB team weekly article backlog review","prompt":"I have 150 rows of knowledge base maintenance data with dates, document groups, updated article counts, and due article counts — can you run the numeric distribution and correlation analysis on updated_articles so I can see how our update workload is spread and how it relates to what's overdue?"},{"title":"Content ops correlation deep dive","prompt":"Can you analyze these 80 knowledge base maintenance records across our document groups and tell me the distribution of due_articles and also how due_articles and updated_articles correlate with each other?"},{"title":"Multi-team document maintenance benchmarking","prompt":"I've got maintenance records from three document groups over the past quarter — 200 rows total with updated_articles and due_articles fields. Run the numeric distribution and two-measure correlation reports on updated_articles for me so I can benchmark team performance."}],"resultDescription":"Returns two independent statistical reports: (1) a numeric distribution report showing spread, central tendency, and shape of the selected field (updated_articles or due_articles) across the supplied rows, and (2) a two-measure correlation report quantifying the relationship between updated_articles and due_articles across the dataset. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Empty or missing rows array returns a validation error","Rows exceeding 200 items are rejected with a limit error","Malformed date strings not matching YYYY-MM-DD pattern cause schema validation failure","Null values in both measure fields across all rows may produce degenerate or undefined correlation","Missing required fields (row_id, document_group, date) cause per-row validation errors","Invalid field enum value (not updated_articles or due_articles) returns an error"],"whenToPreferThis":"Choose this endpoint when you have tabular knowledge base maintenance records with updated_articles and due_articles numeric fields and need both a distribution summary and a correlation between those two measures in a single call. It is ideal for editorial teams, content ops managers, or KB administrators who want quick statistical insight without setting up their own analytics pipeline. Prefer this over generic stats services when your data fits the KB maintenance schema (document_group, date, row_id) and you need exactly these two report types bundled at low cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:53:26.610Z","isFirstParty":false,"canonicalSlug":"knowledge-base-maintenance-numeric-distribution-two-measure-correlation-52c3629b"}