{"uid":"cap__aPpxE9yoZJcBchAJtEBI","slug":"save-files-analyzer-adjacent-row-changes-date-by-category-pivot-6e7f0042","name":"Save Files Analyzer — Adjacent Row Changes + Date by Category Pivot","description":"Save files — Adjacent row changes + Date by category pivot: Adjacent row changes + 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-13-160?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_qZ8aqHeRiResUA8WpnMh4","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 metrics (save size and write time) by computing adjacent row changes and a date-by-category pivot table for up to 200 rows.","exampleAgentPrompt":"Can you analyze my game save file records — I have up to 50 rows with fields row_id, game_area, date, save_kb, and write_ms — and give me both an adjacent row changes report and a date-by-category pivot table for the save_kb field?","exampleUseCases":[{"title":"Game save size trend analysis","prompt":"I have a list of 80 game save records with dates, game areas, save sizes in KB, and write times in milliseconds — can you run the adjacent row changes and date-by-category pivot reports on save_kb to see how save file sizes shift between rows and vary by game area over time?"},{"title":"Write performance comparison across areas","prompt":"Here are 120 rows of save file data with row IDs, game areas, dates, save_kb, and write_ms — please analyze write_ms using the adjacent row changes and date-category pivot reports so I can see how write times differ across game zones day by day."},{"title":"Spotting anomalies in save file metrics","prompt":"I've got 40 save file records from our QA session across different game areas — run the adjacent row changes and date-by-category pivot on save_kb so I can spot any unusual spikes or drops between consecutive saves and across categories."}],"resultDescription":"Returns two analytical reports: (1) an adjacent row changes report showing the difference in the selected metric (save_kb or write_ms) between each consecutive row, and (2) a date-by-category pivot table summarizing the selected metric grouped by date and game_area. Both reports cover the supplied rows (up to 200).","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, game_area, date, save_kb, write_ms) cause validation errors","Invalid date format (not YYYY-MM-DD) causes parsing failure","Field selector not one of 'save_kb' or 'write_ms' causes enum validation error","Empty rows array causes a minimum items error","Numeric values outside allowed range cause validation errors"],"whenToPreferThis":"Choose this endpoint when you have structured game save file records and need both a sequential row-change analysis and a date-by-category pivot in a single call, without requiring any external data lookup or live prediction. It is ideal for offline batch analysis of up to 200 rows of save metrics at minimal cost ($0.01 USDC for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-06T06:36:53.875Z","isFirstParty":false,"canonicalSlug":"save-files-analyzer-adjacent-row-changes-date-by-category-pivot-6e7f0042"}