{"uid":"cap_CCoXcv4jiJ15vmZFSLxOI","slug":"save-files-analytics-category-frequencies-iqr-outlier-flags-3485d464","name":"Save Files Analytics — Category Frequencies + IQR Outlier Flags","description":"Save files — Category frequencies + IQR outlier flags: Category frequencies + 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-13-107?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_ckrb4ubTEUbcEBl5-Uo33","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":"Analyzes save file records (save_kb, write_ms) to produce category frequency distributions and IQR-based outlier flags for up to 200 rows.","exampleAgentPrompt":"I have 4 game save records across group-a and group-b areas — can you analyze the save_kb field to show me how often each game area appears and flag any rows with outlier save sizes using IQR? Rows: row-1 (2026-10-01, group-a, 10 KB, 1 ms), row-2 (2026-10-02, group-b, 20 KB, 2 ms), row-3 (2026-10-03, group-a, 15 KB, 3 ms), row-4 (2026-10-04, group-b, 30 KB, 4 ms).","exampleUseCases":[{"title":"Detect outlier save sizes in game telemetry","prompt":"Here are 50 game save records from our telemetry system — can you analyze the save_kb field, show me how frequently each game_area appears, and flag any rows with save sizes that are outliers based on IQR?"},{"title":"Identify slow write operations by area","prompt":"I have game save logs across multiple areas and want to know: which areas appear most often, and are there any rows where write_ms is suspiciously high based on IQR outlier detection? Here are my 120 records."},{"title":"QA check on save file dataset","prompt":"Before I process this batch of 80 game save records, can you run a quick frequency count of game areas and flag any rows where save_kb looks like an outlier using IQR — I want to catch data quality issues early."}],"resultDescription":"Two analytical reports: (1) a category frequency table showing how often each game_area value appears across the supplied rows, and (2) IQR-based outlier flags for the selected numeric field (save_kb or write_ms), identifying which rows fall outside the interquartile range bounds. Both reports are generated locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 row supplied — minimum input requirement not met","More than 200 rows submitted — exceeds maximum row limit","Missing required fields (row_id, game_area, date, save_kb, write_ms) in any row","Invalid date format (must match YYYY-MM-DD pattern)","Numeric fields out of accepted range (±1 trillion)","Field enum value not one of 'save_kb' or 'write_ms'","Payment not completed via x402 protocol — endpoint requires 0.01 USDC per call"],"whenToPreferThis":"Choose this endpoint when you have game save file telemetry data (up to 200 rows) and need both a categorical frequency breakdown by game area AND IQR-based statistical outlier detection on numeric save metrics (save_kb or write_ms) in a single $0.01 call. Prefer this over generic analytics tools when you specifically need these two combined local reports without any external data enrichment or prediction.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:32:22.750Z","isFirstParty":false,"canonicalSlug":"save-files-analytics-category-frequencies-iqr-outlier-flags-3485d464"}