{"uid":"cap_ZxoUqGB3UrC3VzFX7I7Uz","slug":"registry-snapshots-string-normalisation-date-by-category-pivot-b36bd3a7","name":"Registry Snapshots — String Normalisation + Date by Category Pivot","description":"Registry snapshots — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied registry snapshots records (registered_entities, changed_entities). 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-company-04-035?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","registered_entities","changed_entities"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_group":{"type":"string","default":"","maxLength":80},"changed_entities":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"registered_entities":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","changed_entities":1,"registered_entities":10},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","changed_entities":2,"registered_entities":20},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","changed_entities":3,"registered_entities":15},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","changed_entities":4,"registered_entities":30}],"maxItems":200,"minItems":1},"field":{"enum":["registered_entities","changed_entities"],"type":"string","default":"registered_entities"}}},"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_ZrtTpwNTI-lLydZpFdBua","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":"Performs string normalisation and date-by-category pivot analysis on up to 200 rows of registry snapshot records (registered_entities and changed_entities fields), returning two analytical reports per call.","exampleAgentPrompt":"Can you run string normalisation and a date-by-category pivot on these registry snapshot rows — I have data for company groups 'group-a' and 'group-b' with registered_entities counts across dates in October 2026, up to 50 rows, and I want the registered_entities field analysed?","exampleUseCases":[{"title":"Registry entity change tracking by group","prompt":"I have 80 rows of registry snapshot data with dates, company group names, and changed_entities counts — can you normalise the string fields and pivot the changed_entities values by company group and date so I can see how each group changed over time?"},{"title":"Quarterly registered entity summary","prompt":"I've got a set of registry records for Q4 2026 with registered_entities and company_group columns, about 150 rows — run string normalisation on the group names and give me a date-by-category pivot for the registered_entities field."},{"title":"Data quality cleanup for registry export","prompt":"Our registry export has messy company group labels and I need two reports: normalised string values and a pivot of registered entity counts by date and category — there are about 120 rows, can you process the registered_entities field?"}],"resultDescription":"Returns two independent analytical reports: (1) a string normalisation report cleaning and standardising company_group labels across the supplied rows, and (2) a date-by-category pivot report aggregating the selected numeric field (registered_entities or changed_entities) by date and company_group category. No external lookups are performed; all computation is local and analytical.","failureModes":["Exceeds 200-row limit — request rejected, caller must batch input","Invalid date format (not YYYY-MM-DD) — schema validation error","Missing required fields (row_id, company_group, date) — validation failure","Null numeric values in both registered_entities and changed_entities — sparse or empty pivot output","Invalid field enum value — schema rejection","Empty rows array — minItems:1 constraint violated"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of registry snapshot data with company group labels and entity counts, and you need both string normalisation and a date-by-category pivot in a single low-cost call ($0.01 USDC for both reports). It is ideal for offline/batch analytical use cases where no live lookup, prediction, or external data enrichment is required — all processing is local and deterministic.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T06:43:28.471Z","isFirstParty":false,"canonicalSlug":"registry-snapshots-string-normalisation-date-by-category-pivot-b36bd3a7"}