{"uid":"cap_AHb7ZXDlIbDOQh2cC4T8v","slug":"label-review-daily-sum-series-iqr-outlier-flags-29e00878","name":"Label Review — Daily Sum Series + IQR Outlier Flags","description":"Label review — Daily sum series + IQR outlier flags: Daily sum series + IQR outlier flags 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-12-140?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"}}},"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_-8nlLi6pKNf6hXJFO28Yc","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 daily sum time series and IQR-based outlier flags for label review data (reviewed_records or changed_labels) across up to 200 rows, returning two independent analytical reports.","exampleAgentPrompt":"Can you analyze my label review data for the 'annotations' group — I have daily rows with reviewed_records and changed_labels counts from October 2026 — and give me a daily sum series plus IQR outlier flags on the reviewed_records field?","exampleUseCases":[{"title":"Spot anomalous annotation days","prompt":"I have 90 days of label review logs with reviewed_records and changed_labels per day across two dataset groups. Can you compute the daily sum series and flag any IQR outliers on the reviewed_records field so I can spot days where review volume was unusually high or low?"},{"title":"Audit changed-labels spikes in ML pipeline","prompt":"Run a daily sum series and IQR outlier analysis on my changed_labels data from the last quarter of label review records — I want to see which days had suspiciously large label correction counts."},{"title":"QA check for data labeling team output","prompt":"We have daily label review records split across group-a and group-b. Can you summarize them as daily totals and flag outlier days using IQR on the changed_labels field, so our QA team can investigate anomalies?"}],"resultDescription":"Returns two independent reports: (1) a daily sum time series aggregating the selected field (reviewed_records or changed_labels) by date, and (2) IQR-based outlier flags identifying rows where values fall outside the interquartile range bounds. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Input array exceeds 200 rows — request will be rejected","Missing required fields (row_id, date, dataset_group, reviewed_records, changed_labels) cause validation errors","Invalid date format (must match YYYY-MM-DD pattern) causes schema rejection","Null values in selected field may reduce outlier detection accuracy","Insufficient data variance may result in trivial IQR bounds (all rows flagged or none)","Field enum value not matching 'reviewed_records' or 'changed_labels' causes rejection"],"whenToPreferThis":"Choose this endpoint when you need both a daily aggregation time series and IQR-based statistical outlier detection on label review data in a single $0.01 call. It is ideal for data quality monitoring of annotation pipelines, ML labeling operations, or any workflow producing daily reviewed_records and changed_labels metrics. Prefer it over general-purpose analytics when your data fits the label review schema and you want two bundled reports without external data dependencies.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:11.169Z","isFirstParty":false,"canonicalSlug":"label-review-daily-sum-series-iqr-outlier-flags-29e00878"}