{"uid":"cap_vqrU1EnakCRpvxXAeb4Vi","slug":"save-files-daily-sum-series-iqr-outlier-flags-58ee65e5","name":"Save Files Daily Sum Series + IQR Outlier Flags","description":"Save files — Daily sum series + IQR outlier flags: Daily sum series + IQR outlier flags for supplied save files records (save_kb, write_ms). 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-game-13-140?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","game_area","date","save_kb","write_ms"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"save_kb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"write_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"game_area":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","save_kb":10,"write_ms":1,"game_area":"group-a"},{"date":"2026-10-02","row_id":"row-2","save_kb":20,"write_ms":2,"game_area":"group-b"},{"date":"2026-10-03","row_id":"row-3","save_kb":15,"write_ms":3,"game_area":"group-a"},{"date":"2026-10-04","row_id":"row-4","save_kb":30,"write_ms":4,"game_area":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["save_kb","write_ms"],"type":"string","default":"save_kb"}}},"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_JzibNObpyprRbaY6b9ZbJ","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 save file metrics (save_kb, write_ms) from supplied records","exampleAgentPrompt":"Analyze these game save file records for me — compute the daily sum series and flag any IQR outliers for save_kb across up to 200 rows covering game areas like 'group-a' and 'group-b', with dates from 2026-10-01 to 2026-10-04.","exampleUseCases":[{"title":"Detect bloated save files by date","prompt":"I have a list of game save records with dates, game areas, and save sizes in KB — can you compute the daily totals for save_kb and flag any days that look like outliers using IQR? Here are up to 200 rows of data."},{"title":"Flag slow write times in game logs","prompt":"Can you analyze these game save log entries and give me a daily sum series for write_ms plus flag any rows where write times are outliers based on IQR? I want to catch performance spikes across my game areas."},{"title":"Summarize save activity across game zones","prompt":"I've got save file records from different game areas over a few weeks — please compute the daily sum series for save_kb and highlight any IQR-flagged outlier days so I can see which zones had abnormal save activity."}],"resultDescription":"Returns two independent analytical reports: (1) a daily sum time series aggregating the selected metric (save_kb or write_ms) by date, and (2) IQR-based outlier flags identifying rows or days with anomalous values — all computed locally from the supplied data, up to 200 rows.","failureModes":["Fewer than 1 or more than 200 rows submitted — rejected by schema validation","Missing required fields (row_id, game_area, date, save_kb, write_ms) cause row-level errors","Invalid date format (not YYYY-MM-DD) fails pattern validation","Numeric values outside allowed range rejected","Invalid field enum value (must be save_kb or write_ms) causes error","Insufficient data variance may produce trivial or empty IQR outlier results"],"whenToPreferThis":"Choose this endpoint when you have raw game save file records (with dates, save sizes, and write times) and need both a daily aggregated time series and statistical outlier detection (IQR-based) in a single low-cost call. It is ideal for gaming analytics pipelines where you want to detect anomalous save behavior without external lookups or predictions — all computation is local and deterministic from your supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T12:44:47.735Z","isFirstParty":false,"canonicalSlug":"save-files-daily-sum-series-iqr-outlier-flags-58ee65e5"}