{"uid":"cap_VZt4rKUgoyfUYpCVvKQ-L","slug":"save-files-analytics-numeric-row-ordering-date-by-category-pivot-978c3793","name":"Save Files Analytics — Numeric Row Ordering + Date by Category Pivot","description":"Save files — Numeric row ordering + Date by category pivot: Numeric row ordering + Date by category pivot 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-13-122?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_0VcQ4YQGIIg3At9k8rFRI","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) by producing two reports: a numeric row ordering and a date-by-category pivot table, for up to 200 rows.","exampleAgentPrompt":"Can you run the numeric row ordering and date-by-category pivot reports on these save file records — the field I want analyzed is save_kb, and here are my rows: row-1, 2026-10-01, game_area group-a, save_kb 10, write_ms 1; row-2, 2026-10-02, group-b, 20, 2; row-3, 2026-10-03, group-a, 15, 3?","exampleUseCases":[{"title":"Rank save files by size","prompt":"I have a list of game save records with dates, areas, and file sizes — can you sort them numerically by save_kb so I can see which saves are the largest? My rows are: row-1 (2026-10-01, group-a, save_kb 10, write_ms 1), row-2 (2026-10-02, group-b, save_kb 20, write_ms 2), row-3 (2026-10-03, group-a, save_kb 15, write_ms 3)."},{"title":"Pivot write times by game area and date","prompt":"Can you pivot my save file write times by game area and date? Use write_ms as the field. Here are my records: row-1 (2026-10-01, group-a, save_kb 10, write_ms 1), row-2 (2026-10-02, group-b, save_kb 20, write_ms 2), row-3 (2026-10-03, group-a, save_kb 15, write_ms 3), row-4 (2026-10-04, group-b, save_kb 30, write_ms 4)."},{"title":"Identify slow save areas across dates","prompt":"I want to see which game areas have the slowest write times on each date — can you run both a row ordering and a date-by-category pivot on these save records using write_ms? Rows: row-1 (2026-10-01, dungeon, save_kb 50, write_ms 120), row-2 (2026-10-02, world-map, save_kb 80, write_ms 45), row-3 (2026-10-03, dungeon, save_kb 55, write_ms 200), row-4 (2026-10-04, world-map, save_kb 90, write_ms 60)."}],"resultDescription":"Two analytical reports: (1) a numeric row ordering that ranks the supplied save-file records by the chosen metric (save_kb or write_ms), and (2) a date-by-category pivot table that cross-tabulates save file metrics by game_area and date. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Input rows array is empty or missing — validation error returned","row_id or game_area exceeds 80-character limit — schema validation failure","date field does not match YYYY-MM-DD pattern — rejected with format error","More than 200 rows submitted — request rejected due to row limit","field value is not 'save_kb' or 'write_ms' — enum validation failure","save_kb or write_ms values outside allowed numeric range — validation error","Payment not included or insufficient — x402 payment required response"],"whenToPreferThis":"Choose this endpoint when you have tabular game save-file data (with row IDs, game areas, dates, save sizes in KB, and write times in ms) and need both a ranked ordering by a numeric metric AND a cross-tabulated date-by-category pivot in a single call. Best for offline/local analytical reporting on supplied data up to 200 rows, with no need for live lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:31:45.341Z","isFirstParty":false,"canonicalSlug":"save-files-analytics-numeric-row-ordering-date-by-category-pivot-978c3793"}