{"uid":"cap_pdT55QhZYEM2OX86oPcet","slug":"label-review-analytics-category-frequencies-trailing-mean-series-6e6be047","name":"Label Review Analytics: Category Frequencies + Trailing Mean Series","description":"Label review — Category frequencies + Trailing mean series: Category frequencies + Trailing mean series for supplied label review records (reviewed_records, changed_labels). 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-analytics-12-103?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","reviewed_records","changed_labels"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"changed_labels":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"reviewed_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","changed_labels":1,"reviewed_records":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","changed_labels":2,"reviewed_records":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","changed_labels":3,"reviewed_records":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","changed_labels":4,"reviewed_records":30}],"maxItems":200,"minItems":1},"field":{"enum":["reviewed_records","changed_labels"],"type":"string","default":"reviewed_records"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_u_RQccR49munxSwtSQrsn","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":"Generates two analytical reports for label review data: category frequency distributions and trailing mean series for reviewed_records or changed_labels metrics.","exampleAgentPrompt":"Run category frequency and trailing mean reports on my label review data — here are 50 rows with row_id, dataset_group, date, reviewed_records, and changed_labels fields. Use a window of 5 and compute the trailing mean for reviewed_records.","exampleUseCases":[{"title":"Annotation pipeline quality check","prompt":"I have 120 rows of label review records from our ML annotation pipeline, each with a date, dataset group, number of reviewed records, and changed labels. Can you compute the category frequencies by dataset_group and a trailing mean over a window of 7 for reviewed_records so I can see which groups are most active and spot any quality trends?"},{"title":"Label correction rate trend analysis","prompt":"Here are 80 label review rows across three dataset groups over the past quarter. Run the two analytics reports — category frequencies and a trailing mean with window 10 for changed_labels — so I can track which groups have the highest correction rates and see if they're improving over time."},{"title":"Daily review volume rolling average","prompt":"I've got 150 rows of daily label review data and I want to understand the rolling average of reviewed_records over a 5-day window. Can you also show me the frequency breakdown by dataset_group so I know where most of our review effort is concentrated?"}],"resultDescription":"Two reports: (1) a category frequency table showing how often each dataset_group value appears across the supplied rows, and (2) a trailing mean series showing the rolling average of the selected field (reviewed_records or changed_labels) computed over the specified window size, both derived entirely from the supplied data.","failureModes":["Input array is empty or missing — returns validation error","Row count exceeds 200 — request rejected","Window size greater than number of rows — trailing mean may produce null/partial values for early rows","Invalid date format (not YYYY-MM-DD) — schema validation failure","Missing required row fields (row_id, reviewed_records, changed_labels) — rejected","Field enum value not recognized — validation error"],"whenToPreferThis":"Choose this endpoint when you have label review tabular data (up to 200 rows) and need both a category frequency breakdown by dataset_group and a rolling/trailing mean series for a numeric metric in a single low-cost call. It's ideal for MLOps, annotation pipeline monitoring, or data quality review workflows where no external data, live lookup, or prediction is needed — just local analytical summaries of supplied records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:53:39.301Z","isFirstParty":false,"canonicalSlug":"label-review-analytics-category-frequencies-trailing-mean-series-6e6be047"}