{"uid":"cap_msBBWkQq-dd-UzgQtFnVy","slug":"dataset-storage-trailing-mean-series-iqr-outlier-flags-6f07e2d2","name":"Dataset Storage Trailing Mean Series + IQR Outlier Flags","description":"Dataset storage — Trailing mean series + IQR outlier flags: Trailing mean series + IQR outlier flags for supplied dataset storage records (used_mb, row_count). 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-18-149?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","used_mb","row_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"used_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","used_mb":10,"row_count":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","used_mb":20,"row_count":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","used_mb":15,"row_count":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","used_mb":30,"row_count":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["used_mb","row_count"],"type":"string","default":"used_mb"},"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_AKj8npqbLbnP7FXFBnGNY","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 trailing moving-average series and IQR-based outlier flags for dataset storage metrics (used_mb, row_count) across up to 200 supplied records.","exampleAgentPrompt":"Analyze my dataset storage records and give me the trailing mean series with a window of 3 for used_mb, plus flag any IQR outliers — here are 10 rows with date, row_id, dataset_group, used_mb, and row_count values.","exampleUseCases":[{"title":"Detect storage spikes in data pipeline","prompt":"I have 50 daily storage snapshots for my ETL pipeline partitions — can you compute the trailing mean with a window of 5 for used_mb and flag any IQR outliers so I can see which days had abnormal disk usage?"},{"title":"Monitor row count anomalies by group","prompt":"Here are 120 dataset storage records grouped by team, each with a date and row_count. Run a trailing mean with window 7 on row_count and flag anything that looks like an outlier using IQR — I want to catch any unexpected data drops or surges."},{"title":"Audit storage growth before capacity review","prompt":"Before our capacity planning meeting, can you take these 80 monthly dataset records and calculate the 4-period trailing mean for used_mb along with IQR outlier flags? I need to spot any months where storage ballooned unexpectedly."}],"resultDescription":"Returns two analytical reports: (1) a trailing mean series for the selected field (used_mb or row_count) computed over the specified rolling window, and (2) IQR-based outlier flags indicating which rows fall outside the interquartile range — all derived locally from the supplied data with no external lookups.","failureModes":["Fewer than 2 rows supplied — minimum input not met","window parameter exceeds number of rows — trailing mean cannot be computed","Invalid date format not matching YYYY-MM-DD pattern","More than 200 rows submitted — exceeds maximum item limit","Non-numeric or null values in selected field may reduce outlier detection accuracy","Payment not completed — x402 payment required before response is returned"],"whenToPreferThis":"Choose this endpoint when you need both a smoothed time-series view (trailing mean) and statistical anomaly detection (IQR outlier flags) on dataset storage metrics in a single call. It is ideal for monitoring storage growth trends and detecting usage spikes in pre-collected dataset records without requiring any external data sources or live database connections.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:57.429Z","isFirstParty":false,"canonicalSlug":"dataset-storage-trailing-mean-series-iqr-outlier-flags-6f07e2d2"}