{"uid":"cap_J8FC6ntrjlaMhh7JecC5u","slug":"registry-snapshots-string-normalisation-category-frequencies-4be236c7","name":"Registry Snapshots: String Normalisation + Category Frequencies","description":"Registry snapshots — String normalisation + Category frequencies: String normalisation + Category frequencies 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-04-024?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}}},"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_W1sF9I56HfvSlcFmM6zgh","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 category frequency analysis on up to 200 registry snapshot rows containing registered and changed entity counts, returning two analytical reports.","exampleAgentPrompt":"I have registry snapshot records for a few company groups — can you normalize the company group strings and give me category frequency counts for both the registered_entities and changed_entities fields? I have 4 rows: group-a on 2026-10-01 with 10 registered and 1 changed, group-b on 2026-10-02 with 20 registered and 2 changed, group-a on 2026-10-03 with 15 registered and 3 changed, and group-b on 2026-10-04 with 30 registered and 4 changed.","exampleUseCases":[{"title":"Registry audit data cleanup","prompt":"I've got a batch of registry snapshot records from our compliance team — around 50 rows with company_group names that are inconsistently formatted. Can you normalize the strings and give me frequency counts for registered_entities and changed_entities grouped by category?"},{"title":"Monthly entity change frequency report","prompt":"Here are 120 registry snapshot rows covering last quarter across our company groups. Run string normalization on the group names and produce a category frequency breakdown showing how often entities were registered versus changed for each group."},{"title":"Spot-check small registry dataset","prompt":"I just pulled 8 registry snapshot records with row IDs row-1 through row-8, dates in October 2026, and two company groups. Can you normalize the company group labels and tell me the category frequencies for both registered_entities and changed_entities columns?"}],"resultDescription":"Two independent analytical reports: (1) normalised string output for the company_group field across all supplied rows, and (2) category frequency tables for the registered_entities and changed_entities numeric columns — all computed locally without live lookup or external data enrichment, covering up to 200 rows per call.","failureModes":["Exceeding 200 rows causes rejection — keep batch size within limit","Missing required fields (row_id, date, company_group, registered_entities, changed_entities) will cause validation errors","Dates not matching YYYY-MM-DD pattern will fail schema validation","Numeric values outside ±1,000,000,000,000 range will be rejected","Empty rows array is not permitted (minItems: 1)"],"whenToPreferThis":"Choose this endpoint when you have tabular registry snapshot data with company groups and entity counts and need both string normalisation of categorical labels and frequency analysis of numeric entity fields in a single low-cost call. It is well-suited for offline batch processing of up to 200 rows without requiring live data lookups or external enrichment. At $0.01 USDC for two reports, it is cost-effective for routine data cleaning and descriptive analytics pipelines on registry data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:39:51.292Z","isFirstParty":false,"canonicalSlug":"registry-snapshots-string-normalisation-category-frequencies-4be236c7"}