{"uid":"cap_REZI2F2WRzjI5VkuxS3F4","slug":"company-headcount-observations-record-quality-audit-iqr-outlier-flags-dc6ae0c6","name":"Company Headcount Observations — Record Quality Audit + IQR Outlier Flags","description":"Company headcount observations — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags 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-12-014?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"}}},"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_pLLXfzk43k-WFR-piXdIL","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 a record quality audit and IQR-based outlier detection on up to 200 rows of company headcount observation data (headcount or open_roles), returning two independent analytical reports.","exampleAgentPrompt":"Can you audit these company headcount records for data quality issues and flag any IQR outliers in the headcount field? I have about 50 rows across two company groups with dates and open_roles values included.","exampleUseCases":[{"title":"Pre-report headcount data cleanup","prompt":"Before I send our quarterly workforce report, run a quality audit and IQR outlier check on our headcount observations — I have 120 rows with company_group, date, headcount, and open_roles. Flag anything that looks statistically suspicious in the headcount field."},{"title":"Detecting anomalous open roles spikes","prompt":"I've got 80 rows of hiring data by company group and date. Can you run the record quality audit and IQR outlier detection on the open_roles field to see if any entries are way outside the normal range?"},{"title":"Validating imported HR data before pipeline ingestion","prompt":"We just imported headcount observations from an external system — about 150 rows with row IDs, company groups, dates, headcount, and open_roles. Run a quality audit and flag any IQR outliers on the headcount field so we can clean it up before loading it into our data warehouse."}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit identifying data issues such as missing values, invalid formats, or constraint violations across the supplied rows, and (2) IQR-based outlier flags identifying which rows contain statistically anomalous values for the selected field (headcount or open_roles), all computed locally without any external lookups or live data.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, company_group, date, headcount, open_roles) cause validation errors","Invalid date format (not YYYY-MM-DD) causes schema rejection","Field selector not one of 'headcount' or 'open_roles' causes enum validation failure","All-null values for the selected numeric field may produce empty or degenerate IQR results","Payment of 0.01 USDC not included or declined causes access failure"],"whenToPreferThis":"Choose this endpoint when you have a batch of up to 200 company headcount or open_roles rows and need both a record-level data quality audit and IQR-based statistical outlier detection in a single low-cost call. Prefer this over generic data validation tools when your domain is specifically workforce/headcount time series grouped by company. It is ideal for pre-pipeline data cleaning, QA before reporting, or anomaly triage — not for live HR system queries, predictions, or external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:47.861Z","isFirstParty":false,"canonicalSlug":"company-headcount-observations-record-quality-audit-iqr-outlier-flags-dc6ae0c6"}