{"uid":"cap_2Jg9y804Itsqqwmq7bKxH","slug":"legal-document-inventories-string-normalisation-two-measure-correlation-e607ce07","name":"Legal Document Inventories — String Normalisation + Two-Measure Correlation","description":"Legal document inventories — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied legal document inventories records (document_count, reviewed_count). 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-writing-10-033?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","document_group","date","document_count","reviewed_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"document_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"document_group":{"type":"string","default":"","maxLength":80},"reviewed_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","document_count":10,"document_group":"group-a","reviewed_count":1},{"date":"2026-10-02","row_id":"row-2","document_count":20,"document_group":"group-b","reviewed_count":2},{"date":"2026-10-03","row_id":"row-3","document_count":15,"document_group":"group-a","reviewed_count":3},{"date":"2026-10-04","row_id":"row-4","document_count":30,"document_group":"group-b","reviewed_count":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_NzvTpIEwxkdTSUBxDjxQu","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":"Normalises string fields and computes two-measure correlation analysis on legal document inventory records (document_count, reviewed_count) for up to 200 rows, returning two analytical reports.","exampleAgentPrompt":"I have a legal document inventory with 4 rows — row-1 on 2026-10-01 in group-a with 10 documents and 1 reviewed, row-2 on 2026-10-02 in group-b with 20 documents and 2 reviewed, row-3 on 2026-10-03 in group-a with 15 documents and 3 reviewed, and row-4 on 2026-10-04 in group-b with 30 documents and 4 reviewed — can you normalise the string fields and run a two-measure correlation between document_count and reviewed_count?","exampleUseCases":[{"title":"Review rate correlation across legal groups","prompt":"I have 50 rows of legal document inventory data across groups alpha, beta, and gamma from 2026, with document_count and reviewed_count per day — normalise the group name strings and tell me how correlated the document counts are with the review counts across all rows."},{"title":"Audit preparation string clean-up","prompt":"Before our compliance audit, can you normalise the document_group labels in these 120 legal inventory records and compute the correlation between document_count and reviewed_count so we can see if our review pace tracks our filing volume?"},{"title":"Monthly legal inventory statistical report","prompt":"Here are 80 rows of our monthly legal document inventory records with dates in October 2026, document groups A through D, and both document_count and reviewed_count columns — please normalise the strings and generate two correlation reports for these measures."}],"resultDescription":"Two analytical reports per call: (1) normalised string fields for document_group and other text columns, and (2) a two-measure correlation analysis between document_count and reviewed_count, computed locally without any external lookup or prediction, covering up to 200 input rows.","failureModes":["More than 200 rows submitted — request rejected due to maxItems constraint","Missing required fields (row_id, document_group, date, document_count, reviewed_count) — validation error","Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure","Null values for both numeric measures on all rows — correlation cannot be computed","row_id exceeds 80 characters — schema validation error","Payment not included or insufficient — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you have legal document inventory data with both a string field (document_group) needing normalisation and two numeric measures (document_count, reviewed_count) you want to correlate statistically, with up to 200 rows, and you need two independent reports in a single low-cost call without any external data lookup or professional legal assessment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:38:55.292Z","isFirstParty":false,"canonicalSlug":"legal-document-inventories-string-normalisation-two-measure-correlation-e607ce07"}