{"uid":"cap_LsneP6xgFPWZQc6hLkn2A","slug":"commerce-intent-exact-normalised-duplicate-audit-2c563c0f","name":"Commerce Intent Exact Normalised Duplicate Audit","description":"Commerce intent - Exact normalised duplicate audit: Exact normalised duplicate audit for Commerce intent. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded exact normalised duplicate audit deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-commerce-intent-duplicates?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"records":{"type":"array","items":{"type":"object","required":["id","text","actual"],"properties":{"id":{"type":"string","default":"","maxLength":80,"minLength":1},"text":{"type":"string","default":"","maxLength":1000},"actual":{"enum":["browse","purchase","return","other"],"type":"string"}},"additionalProperties":false},"default":[{"id":"example-0-0","text":"browse sample document number 0 for this supplied dataset.","actual":"browse"},{"id":"example-0-1","text":"browse sample document number 1 for this supplied dataset.","actual":"browse"},{"id":"example-0-2","text":"browse sample document number 2 for this supplied dataset.","actual":"browse"},{"id":"example-1-0","text":"purchase sample document number 0 for this supplied dataset.","actual":"purchase"},{"id":"example-1-1","text":"purchase sample document number 1 for this supplied dataset.","actual":"purchase"},{"id":"example-1-2","text":"purchase sample document number 2 for this supplied dataset.","actual":"purchase"},{"id":"example-2-0","text":"return sample document number 0 for this supplied dataset.","actual":"return"},{"id":"example-2-1","text":"return sample document number 1 for this supplied dataset.","actual":"return"},{"id":"example-2-2","text":"return sample document number 2 for this supplied dataset.","actual":"return"},{"id":"example-3-0","text":"other sample document number 0 for this supplied dataset.","actual":"other"},{"id":"example-3-1","text":"other sample document number 1 for this supplied dataset.","actual":"other"},{"id":"example-3-2","text":"other sample document number 2 for this supplied dataset.","actual":"other"}],"maxItems":200,"minItems":2}}},"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_9pMLIsyLNHMNnCoWD9sdM","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":"Audits up to 200 labelled commerce-intent text records to identify exact normalised duplicates across browse, purchase, return, and other categories.","exampleAgentPrompt":"Can you run an exact normalised duplicate audit on my commerce intent dataset? I have 150 labelled records with browse, purchase, return, and other categories — here they are — and I want to know which ones are exact duplicates after normalisation.","exampleUseCases":[{"title":"Pre-training data quality check","prompt":"Before I fine-tune my commerce intent classifier, can you audit these 180 labelled records — tagged as browse, purchase, return, or other — and flag any exact normalised duplicates so I'm not training on redundant data?"},{"title":"Dataset deduplication for ML benchmark","prompt":"I'm building a benchmark for commerce intent classification. Can you check my 120 labelled text samples for exact normalised duplicates across all four categories: browse, purchase, return, and other?"},{"title":"Crowdsourced label audit","prompt":"We collected 200 commerce intent labels from crowdworkers and I suspect some annotators submitted identical texts. Can you run a normalised duplicate audit on these records and tell me which ones are repeated?"}],"resultDescription":"A structured duplicate audit report identifying which of the supplied labelled text records are exact matches after normalisation, covering records labelled across browse, purchase, return, and other commerce intent categories. The deliverable is bounded to one audit per call for up to 200 records.","failureModes":["Fewer than 2 records supplied — minimum input requirement not met","More than 200 records supplied — exceeds maximum batch size","Record ID missing or exceeds 80 characters — schema validation failure","Text field exceeds 1000 characters per record — rejected","Invalid intent label provided outside browse/purchase/return/other enum — validation error","Payment of 0.01 USDC not completed — request blocked"],"whenToPreferThis":"Choose this endpoint when you need a cheap, fast, and deterministic exact-match duplicate check on a small labelled commerce-intent dataset (up to 200 records) before training or benchmarking a classifier. It is not a semantic similarity tool or a hosted model — it uses local normalisation logic to find verbatim or near-verbatim duplicates. Prefer it over general deduplication tools when your data is specifically structured around browse, purchase, return, and other commerce intent labels and you want an audit deliverable rather than transformed data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:54:51.447Z","isFirstParty":false,"canonicalSlug":"commerce-intent-exact-normalised-duplicate-audit-2c563c0f"}