{"uid":"cap_dPTmvVzLmlP2hz7auj_oi","slug":"company-filing-inventories-record-quality-audit-string-normalisation-51d74480","name":"Company Filing Inventories — Record Quality Audit, String Normalisation & Category Frequencies","description":"Company filing inventories — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies for supplied company filing inventories records (available_filings, expected_filings). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-company-17-195?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","available_filings","expected_filings"],"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},"expected_filings":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"available_filings":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","expected_filings":1,"available_filings":10},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","expected_filings":2,"available_filings":20},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","expected_filings":3,"available_filings":15},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","expected_filings":4,"available_filings":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_to7sxLs1a-MovLjQMecdd","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 three analytical reports (record quality audit, string normalisation, and category frequency analysis) on supplied company filing inventory data (available_filings, expected_filings) for up to 200 rows.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and category frequency analysis on my company filing inventory data? I have up to 50 rows with fields like row_id, company_group, date, available_filings, and expected_filings — here's the data.","exampleUseCases":[{"title":"Filing completeness audit for compliance team","prompt":"I need to audit the quality of our company filing inventory records before our compliance review. Can you run a record quality audit, string normalisation, and category frequency report on these 120 rows of available and expected filing counts by company group?"},{"title":"Normalising messy company group labels","prompt":"Our filing inventory dataset has inconsistent company group names — things like 'Group A', 'group-a', 'GROUP A' all meaning the same thing. Can you run the string normalisation report on these 80 rows so we can see what needs cleaning?"},{"title":"Category frequency breakdown across filing groups","prompt":"I want to understand how our filings are distributed across different company groups. Can you run the category frequency analysis on my 200 rows of filing inventory data and show me how often each company group appears?"}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging missing values, invalid dates, out-of-range numbers, and other data issues; (2) a string normalisation report identifying inconsistent or malformed string values in fields like company_group; and (3) a category frequency report showing the distribution and counts of values across categorical fields — all computed locally without any external lookups.","failureModes":["Input array exceeds 200 rows — request will be rejected","Missing required fields (row_id, company_group, date, available_filings, expected_filings) in any row causes validation failure","Malformed date strings not matching YYYY-MM-DD pattern are flagged or rejected","Numeric values outside the allowed range (-1e12 to 1e12) are rejected","Empty input array (minItems: 1 not met) causes rejection","Payment not included or insufficient USDC causes 402 response"],"whenToPreferThis":"Choose this endpoint when you have a batch of up to 200 company filing inventory records and need three simultaneous analytical views — data quality, string normalisation, and category frequencies — in a single cheap call ($0.01 USDC). It is ideal for pre-processing or auditing filing data pipelines before downstream analysis, without needing a live data connection or external service.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T12:48:31.039Z","isFirstParty":false,"canonicalSlug":"company-filing-inventories-record-quality-audit-string-normalisation-51d74480"}