{"uid":"cap_vVCBhH5RpYG2LjHQ9oRMX","slug":"image-exports-string-normalisation-two-measure-correlation-560f44e5","name":"Image Exports — String Normalisation + Two-Measure Correlation","description":"Image exports — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied image exports records (width_pixels, height_pixels). 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-creative-17-033?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_ueBCwCz9bayuZqQkCwJhQ","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 string normalisation and a two-measure Pearson/rank correlation analysis on up to 200 image export records (width_pixels, height_pixels), returning two analytical reports.","exampleAgentPrompt":"Can you run a string normalisation and two-measure correlation analysis on my image export data? I have 4 rows: row-1 on 2026-10-01 in group-a with width 1920 and height 1080, row-2 on 2026-10-02 in group-b with width 1280 and height 720, row-3 on 2026-10-03 in group-a with width 3840 and height 2160, row-4 on 2026-10-04 in group-b with width 2560 and height 1440.","exampleUseCases":[{"title":"Checking dimension consistency across asset groups","prompt":"I have 50 image exports from two asset groups — can you normalize the group names and tell me how strongly width_pixels and height_pixels are correlated across all of them?"},{"title":"QA audit of exported image dimensions","prompt":"Our render pipeline exported a batch of images; can you run string normalisation and a two-measure correlation on the width and height pixel values so I can see if there are any unusual relationships or inconsistencies?"},{"title":"Analytics report for creative team deliverables","prompt":"I need two statistical reports on our creative deliverables — please normalize the asset group strings and compute the correlation between width_pixels and height_pixels for these 150 image export records."}],"resultDescription":"Returns two structured analytical reports: (1) a string normalisation report cleaning and standardising text fields such as asset_group, and (2) a two-measure correlation report quantifying the statistical relationship between width_pixels and height_pixels across the submitted rows. No external data is fetched; analysis is performed locally on the supplied dataset.","failureModes":["Fewer than 1 row or more than 200 rows submitted — request rejected","Missing required fields (row_id, date, width_pixels, height_pixels) — validation error","Malformed date format (not YYYY-MM-DD) — schema validation failure","All width_pixels or height_pixels values are null — correlation cannot be computed","row_id exceeds 80 characters — schema rejection","Payment not attached or insufficient USDC — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you have a batch of image export records (up to 200 rows) with pixel dimension fields and need both string normalisation on categorical text fields and a statistical correlation between two numeric measures in a single paid call. It is ideal for offline/local analytical use cases where no external lookup, live data, or predictive model is needed — just clean stats on your supplied data at low cost ($0.01 USDC for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:31:34.569Z","isFirstParty":false,"canonicalSlug":"image-exports-string-normalisation-two-measure-correlation-560f44e5"}