{"uid":"cap_20lj6XASajYPS7V3h4-Mz","slug":"save-files-string-normalisation-explicit-missing-value-fill-e60bc4fb","name":"Save Files — String Normalisation + Explicit Missing-Value Fill","description":"Save files — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill 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-13-037?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_twC1f5Az7OKDkLB238-SG","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":"Normalises string fields and fills missing numeric values (save_kb or write_ms) in up to 200 save-file records, returning two analytical reports.","exampleAgentPrompt":"I have 150 save file records with some missing save_kb values — can you normalise the strings and fill those nulls using the median method, with fields like row_id, game_area, date, save_kb, and write_ms?","exampleUseCases":[{"title":"Impute missing save sizes for game analytics","prompt":"I've got a batch of 80 save file rows where some save_kb values are null — can you fill those missing sizes using the median and also normalise any inconsistent string fields? The rows have row_id, game_area, date, save_kb, and write_ms columns."},{"title":"Clean write latency data before reporting","prompt":"My save file dataset has about 50 rows with several write_ms values missing — please fill them in using the mean and run string normalisation on the text fields so I can use this for reporting."},{"title":"Zero-fill absent save sizes for two game areas","prompt":"Can you process these 120 save file records for group-a and group-b, fill any missing save_kb values with zero, and normalise the string columns? I need both the normalisation report and the missing-value fill report back."}],"resultDescription":"Two analytical reports covering (1) string normalisation results for text fields and (2) explicit missing-value fill results for the chosen numeric field (save_kb or write_ms), applied to up to 200 submitted save-file rows using local engines — no external lookups or predictions.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, game_area, date) causes row rejection","Numeric values outside allowed range (±1,000,000,000,000) are rejected","Invalid date format (non-YYYY-MM-DD) causes schema validation failure","Specifying an unsupported fill method or field enum value returns an error","Empty rows array is rejected (minItems: 1)"],"whenToPreferThis":"Choose this endpoint when you have up to 200 save-file records with mixed string inconsistencies and null numeric values (save_kb or write_ms) and need both normalisation and imputation in a single low-cost call. It is ideal for offline batch data-quality workflows on game save data where no live lookup or external enrichment is required.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:48:19.594Z","isFirstParty":false,"canonicalSlug":"save-files-string-normalisation-explicit-missing-value-fill-e60bc4fb"}