{"uid":"cap_ARWPCry7WiiLQBE_cEIFo","slug":"image-exports-record-quality-audit-string-normalisation-two-measure-7be71fdd","name":"Image Exports — Record Quality Audit + String Normalisation + Two-Measure Correlation","description":"Image exports — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation for supplied image exports records (width_pixels, height_pixels). 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-creative-17-204?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","width_pixels","height_pixels"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"asset_group":{"type":"string","default":"","maxLength":80},"width_pixels":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"height_pixels":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","asset_group":"group-a","width_pixels":10,"height_pixels":1},{"date":"2026-10-02","row_id":"row-2","asset_group":"group-b","width_pixels":20,"height_pixels":2},{"date":"2026-10-03","row_id":"row-3","asset_group":"group-a","width_pixels":15,"height_pixels":3},{"date":"2026-10-04","row_id":"row-4","asset_group":"group-b","width_pixels":30,"height_pixels":4}],"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_iZdGxFN739D-RQY2N1f1Z","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 up to 200 image export records (width/height pixels) with three bundled reports: record quality audit, string normalization, and correlation between width and height measures.","exampleAgentPrompt":"Can you run a quality audit, string normalization, and width-height correlation report on my image export records? I have about 50 rows with fields like row_id, asset_group, date, width_pixels, and height_pixels that I need checked.","exampleUseCases":[{"title":"Pre-pipeline image data validation","prompt":"Before I send my image export data to the processing pipeline, can you audit the record quality, normalize the asset group strings, and check if there's a correlation between width_pixels and height_pixels? I have 120 rows covering Q3 exports."},{"title":"Asset library dimension consistency check","prompt":"I have a batch of 80 image asset records from our creative library — can you check for data quality issues, clean up the asset_group labels, and tell me how correlated the width and height dimensions are across the dataset?"},{"title":"Monthly image export QA report","prompt":"Run the three-report analysis on our monthly image exports: quality audit to catch bad rows, normalize the group name strings, and give me the correlation between image width and height for all 200 entries."}],"resultDescription":"Returns three independent analytical reports for the submitted image export rows: (1) a record quality audit flagging missing, null, or out-of-range values; (2) a string normalization report standardizing asset_group and other string fields; and (3) a two-measure correlation report quantifying the statistical relationship between width_pixels and height_pixels across all submitted rows.","failureModes":["Empty rows array or missing required fields (row_id) returns a validation error","More than 200 rows submitted exceeds the per-call limit and is rejected","Invalid date format (not YYYY-MM-DD) causes row-level rejection","All null values for width_pixels or height_pixels may prevent correlation computation","Non-numeric values passed for pixel dimensions cause schema validation failure"],"whenToPreferThis":"Choose this endpoint when you need a bundled, low-cost ($0.01 USDC) offline analysis of image export records covering data quality, string cleanliness, and dimensional correlation — all in a single call without any external lookups or live data dependencies. It is ideal for batch QA workflows on up to 200 image dimension records where you want three distinct analytical perspectives at once.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:41:00.017Z","isFirstParty":false,"canonicalSlug":"image-exports-record-quality-audit-string-normalisation-two-measure-7be71fdd"}