{"uid":"cap_3Ug3S1iW5UjGuVPcoBGmW","slug":"correction-logs-numeric-distribution-numeric-row-ordering-dac7566f","name":"Correction Logs — Numeric Distribution + Numeric Row Ordering","description":"Correction logs — Numeric distribution + Numeric row ordering: Numeric distribution + Numeric row ordering for supplied correction logs records (correction_count, published_items). 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-news-04-073?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","channel_group","date","correction_count","published_items"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"channel_group":{"type":"string","default":"","maxLength":80},"published_items":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"correction_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","channel_group":"group-a","published_items":1,"correction_count":10},{"date":"2026-10-02","row_id":"row-2","channel_group":"group-b","published_items":2,"correction_count":20},{"date":"2026-10-03","row_id":"row-3","channel_group":"group-a","published_items":3,"correction_count":15},{"date":"2026-10-04","row_id":"row-4","channel_group":"group-b","published_items":4,"correction_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["correction_count","published_items"],"type":"string","default":"correction_count"}}},"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_dNA-Hmhu0wGnxChybrU_4","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":"Computes numeric distribution statistics and numeric row ordering for correction log data (correction_count, published_items) on up to 200 supplied rows, returning 2 independent analytical reports.","exampleAgentPrompt":"Can you run a numeric distribution and row ordering analysis on my correction log data — I have rows with correction_count and published_items by channel_group and date — and give me both reports for the correction_count field?","exampleUseCases":[{"title":"Editorial team correction rate analysis","prompt":"I have correction log records from our news channels with correction_count and published_items per date and channel group. Can you analyze the numeric distribution and ordering of correction_count across these rows so I can see which groups have the most corrections?"},{"title":"Published items volume ranking","prompt":"Run a numeric distribution and row ordering report on my correction log data using the published_items field — I want to see how published item counts are distributed and which rows rank highest."},{"title":"Multi-channel correction audit","prompt":"I've got up to 150 correction log rows across several channel groups with dates ranging over the past quarter. Can you compute the numeric distribution and numeric row ordering for correction_count so I can spot outliers and rank the channels?"}],"resultDescription":"Returns 2 independent analytical reports: (1) a numeric distribution report showing how values of the selected field (correction_count or published_items) are spread across the supplied rows, and (2) a numeric row ordering report ranking the rows by the selected numeric field — all computed locally on the supplied data with no external lookups.","failureModes":["Fewer than 1 row supplied — minItems violation returns validation error","More than 200 rows supplied — maxItems exceeded, request rejected","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Missing required fields (row_id, channel_group, date, correction_count, published_items) causes row rejection","Field enum value not 'correction_count' or 'published_items' causes error","Null values in the selected numeric field may affect distribution and ordering results","Payment of 0.01 USDC not included causes x402 payment required response"],"whenToPreferThis":"Choose this endpoint when you have tabular correction log data (up to 200 rows) with numeric fields and need both a distribution breakdown and a row-level numeric ranking in a single low-cost call. It is purpose-built for editorial/news correction data with channel_group and date dimensions. Prefer it over generic analytics tools when you want a fast, offline (no external lookup) dual-report output for correction_count or published_items.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:38:02.025Z","isFirstParty":false,"canonicalSlug":"correction-logs-numeric-distribution-numeric-row-ordering-dac7566f"}