{"uid":"cap_W2ErhOIu6Zhl06CDZbpFa","slug":"save-files-data-quality-audit-record-quality-string-normalisation-a5be0353","name":"Save Files Data Quality Audit — Record Quality, String Normalisation & Category Frequencies","description":"Save files — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies for supplied save files records (save_kb, write_ms). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-game-13-195?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}}},"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_ydIknJIXMXbUqIZjpT6k9","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":"Runs three analytical reports (record quality audit, string normalisation, and category frequencies) on up to 200 rows of game save-file data (save_kb, write_ms) using local engines with no external lookups.","exampleAgentPrompt":"Can you run a data quality audit, string normalisation, and category frequency report on my game save file records? Here are up to 200 rows with fields row_id, game_area (like 'zone-a', 'zone-b'), date, save_kb, and write_ms — I want all three reports in one call.","exampleUseCases":[{"title":"Game save log quality check","prompt":"I have a batch of game save events — each has a row ID, a game area name, a date, a save size in KB, and a write time in milliseconds. Can you audit the record quality, normalise any messy string fields, and give me a frequency breakdown by game area for all 200 rows?"},{"title":"Detecting bad values in save data","prompt":"Some of my save file records might have nulls or weird values in save_kb and write_ms. Can you run a quality audit on these rows and flag any issues, plus tell me how the game_area categories are distributed?"},{"title":"Profiling a new save dataset","prompt":"Before I use this dataset of game save logs, I want to profile it — can you check record completeness, standardise the game_area strings, and count how often each category shows up? I'll send you up to 150 rows with row_id, date, save_kb, write_ms, and game_area."}],"resultDescription":"Three structured reports returned for the submitted rows: (1) a record quality audit flagging missing, null, or out-of-range values in each row; (2) a string normalisation report standardising text fields like game_area; (3) a category frequency table counting occurrences of each unique game_area value across the supplied dataset. All computed locally with no external data.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, game_area, date, save_kb, write_ms) per row causes rejection","Invalid date format (non-YYYY-MM-DD) triggers schema validation failure","Numeric values outside allowed range cause rejection","Empty rows array returns an error","Payment of 0.01 USDC not included or declined results in 402 response"],"whenToPreferThis":"Choose this endpoint when you need a combined data quality audit, string normalisation, and category frequency analysis for game save file records in a single low-cost API call. It is best suited for datasets up to 200 rows where the fields are save_kb, write_ms, game_area, date, and row_id. Prefer this over generic data profiling tools when working specifically with game save metrics and wanting three distinct analytical outputs without any external lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:31:39.548Z","isFirstParty":false,"canonicalSlug":"save-files-data-quality-audit-record-quality-string-normalisation-a5be0353"}