{"uid":"cap_P3nJVJlAJgpOERRpZay-A","slug":"company-headcount-observations-record-quality-audit-string-c2dffe9f","name":"Company Headcount Observations — Record Quality Audit & String Normalisation","description":"Company headcount observations — Record quality audit + String normalisation: Record quality audit + String normalisation for supplied company headcount observations records (headcount, open_roles). 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-12-001?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}}},"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_1AadaXJCSaGSFTe9LmDAb","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 and normalises up to 200 company headcount observation records (headcount, open_roles) producing two independent quality and string normalisation reports using local analytical engines.","exampleAgentPrompt":"Can you audit and normalise my company headcount observation records? I have a batch of up to 200 rows with fields like row_id, company_group, date, headcount, and open_roles — I want a record quality audit and string normalisation report for all of them.","exampleUseCases":[{"title":"HR data pipeline quality gate","prompt":"I'm loading headcount and open_roles observations into our data warehouse. Can you run a record quality audit and string normalisation check on these 150 rows before ingestion, so I can catch bad dates, nulls, or inconsistent company_group strings?"},{"title":"Monthly workforce snapshot validation","prompt":"We pulled our monthly company headcount snapshot — 80 rows with company_group, date, headcount, and open_roles. Please audit the record quality and normalise any messy string fields so the data is clean for our BI dashboard."},{"title":"Open roles data cleansing for reporting","prompt":"Our open_roles and headcount data has come in from three different sources and the company group names are inconsistent. Can you run a string normalisation and quality audit on these 200 rows and tell me what needs fixing?"}],"resultDescription":"Returns two independent reports: (1) a record quality audit flagging issues such as missing values, out-of-range numbers, malformed dates, and duplicate row IDs across the supplied headcount/open_roles rows; (2) a string normalisation report detailing transformations applied to text fields like company_group. Both reports cover up to 200 input rows and are generated locally without external lookups.","failureModes":["Input array is empty or exceeds 200 rows — rejected with validation error","Missing required fields (row_id, company_group, date, headcount, open_roles) in any row — row-level error reported","date field does not match YYYY-MM-DD pattern — flagged as malformed in quality audit","Payment not provided or insufficient USDC — request rejected before processing","headcount or open_roles values outside ±1,000,000,000,000 range — validation error"],"whenToPreferThis":"Choose this endpoint when you need a combined record quality audit and string normalisation pass on company headcount observation data (headcount, open_roles) in a single cost-effective call. It is ideal for data pipeline validation gates, pre-ingestion cleansing, or periodic data health checks where no external lookups or predictive models are needed — just local analytical engines on up to 200 rows for $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:59.152Z","isFirstParty":false,"canonicalSlug":"company-headcount-observations-record-quality-audit-string-c2dffe9f"}