{"uid":"cap_HxoNAMvJVp_Oty0wCNfNN","slug":"company-headcount-observations-record-quality-audit-string-a64992f5","name":"Company Headcount Observations — Record Quality Audit, String Normalisation & Missing-Value Fill","description":"Company headcount observations — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill for supplied company headcount observations records (headcount, open_roles). 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-12-208?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","headcount","open_roles"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"headcount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"open_roles":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","headcount":10,"open_roles":1,"company_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","headcount":20,"open_roles":2,"company_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","headcount":15,"open_roles":3,"company_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","headcount":30,"open_roles":4,"company_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["headcount","open_roles"],"type":"string","default":"headcount"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_ulqiSR-ocEamIBSyghMy1","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 record quality, normalises strings, and fills missing values in company headcount observation data (headcount, open_roles) for up to 200 rows, returning three independent analytical reports.","exampleAgentPrompt":"Can you audit and clean my company headcount dataset? I have about 150 rows with fields like company_group, date, headcount, and open_roles — please run a record quality audit, normalise the company_group strings, and fill any missing headcount values using median imputation.","exampleUseCases":[{"title":"Pre-analysis headcount data cleanup","prompt":"I have 120 rows of quarterly headcount observations across several company groups and I need to clean them up before analysis — can you audit the record quality, fix any inconsistent company_group labels, and fill missing headcount values using median imputation?"},{"title":"Open roles data gap filling","prompt":"My open_roles data has a bunch of nulls scattered across dates and company groups — can you run a missing-value fill using mean substitution on the open_roles field and also give me a record quality report on the whole dataset?"},{"title":"HR reporting pipeline data validation","prompt":"Before I send this headcount dataset to our reporting team, can you do a full quality audit, normalise the company name strings, and fill any missing headcount entries with zero so the downstream system doesn't break?"}],"resultDescription":"Three independent analytical reports covering: (1) a record quality audit flagging issues such as nulls, out-of-range values, and malformed records; (2) a string normalisation report identifying and correcting inconsistencies in company_group labels; and (3) an explicit missing-value fill report showing which headcount or open_roles values were imputed and with what value (zero, mean, or median).","failureModes":["Empty rows array or rows exceeding 200 items returns a validation error","Invalid date format (not YYYY-MM-DD) causes row rejection","Missing required fields (row_id, company_group, date) results in row-level errors","Invalid enum values for field or method parameters return a schema validation error","Payment not completed via x402 protocol results in 402 Payment Required response"],"whenToPreferThis":"Choose this endpoint when you need a combined data quality audit, string normalisation, and missing-value imputation in a single call for company headcount datasets of up to 200 rows. It is ideal as a preprocessing step before downstream analytics or reporting, when you want three distinct reports from one $0.01 payment without any external lookups or live data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:59.738Z","isFirstParty":false,"canonicalSlug":"company-headcount-observations-record-quality-audit-string-a64992f5"}