{"uid":"cap_IOoAJo4w0VgTgQG_JqyHv","slug":"product-photography-analytics-string-normalisation-two-measure-376ac647","name":"Product Photography Analytics — String Normalisation + Two-Measure Correlation","description":"Product photography — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied product photography records (required_images, completed_images). 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-retail-09-033?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","required_images","completed_images"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"store_group":{"type":"string","default":"","maxLength":80},"required_images":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"completed_images":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","store_group":"group-a","required_images":10,"completed_images":1},{"date":"2026-10-02","row_id":"row-2","store_group":"group-b","required_images":20,"completed_images":2},{"date":"2026-10-03","row_id":"row-3","store_group":"group-a","required_images":15,"completed_images":3},{"date":"2026-10-04","row_id":"row-4","store_group":"group-b","required_images":30,"completed_images":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_VyZJJyKkzOv_k_JYnsD73","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 two-measure correlation analysis on product photography records (required_images vs completed_images) for up to 200 rows, returning two independent analytical reports.","exampleAgentPrompt":"Analyse the correlation between required and completed product images for these store groups — I have 4 rows of data: group-a on 2026-10-01 needed 10 images and completed 1, group-b on 2026-10-02 needed 20 and completed 2, group-a on 2026-10-03 needed 15 and completed 3, group-b on 2026-10-04 needed 30 and completed 4. Give me the string normalisation and two-measure correlation reports.","exampleUseCases":[{"title":"Retail photography completion audit","prompt":"I have weekly product photography data for our two store groups — can you run a string normalisation and correlation analysis on the required vs completed images? Here are 8 rows with row IDs, dates, store groups, and both image counts."},{"title":"Cross-store image gap correlation","prompt":"We track required_images and completed_images across group-a and group-b stores each day. Run the two-measure correlation report on my 50-row dataset to see how tightly completion tracks requirements."},{"title":"Photography backlog trend analysis","prompt":"Can you normalise and correlate our product photography backlog data? I'll send you up to 200 rows with dates, store group names, required image counts, and how many were actually completed — I need both analytical reports."}],"resultDescription":"Returns two independent analytical reports: (1) a string normalisation report covering the text fields (row_id, store_group, date), and (2) a two-measure correlation report quantifying the statistical relationship between required_images and completed_images across the submitted rows. No external lookups or predictions are performed; analysis is fully local on the supplied data.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, required_images, completed_images) causes row rejection","Malformed date strings not matching YYYY-MM-DD pattern fail schema validation","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array returns an error","Payment failure (insufficient USDC) blocks execution"],"whenToPreferThis":"Choose this endpoint when you have product photography tracking data (required vs completed image counts by store group and date) and need both string normalisation of text fields and a two-measure statistical correlation report in a single call, at low cost ($0.01 USDC for up to 200 rows). Prefer it over generic analytics tools when your dataset fits within 200 rows and you want two bundled reports without external data lookups or ML predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T19:12:00.339Z","isFirstParty":false,"canonicalSlug":"product-photography-analytics-string-normalisation-two-measure-376ac647"}