{"uid":"cap_nyl1N4kTF5BBSYIsn9_js","slug":"company-headcount-observations-string-normalisation-category-e7cf1ca7","name":"Company Headcount Observations — String Normalisation + Category Frequencies","description":"Company headcount observations — String normalisation + Category frequencies: String normalisation + Category frequencies 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-12-024?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_jnWnQpo1ydXLGY3eeYBTp","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":"Normalises string fields and computes category frequency distributions for up to 200 company headcount observation records (headcount, open_roles).","exampleAgentPrompt":"Can you normalize the string fields and compute category frequencies for these company headcount records? I have 4 rows: row-1 for group-a on 2026-10-01 with headcount 10 and 1 open role, row-2 for group-b on 2026-10-02 with headcount 20 and 2 open roles, row-3 for group-a on 2026-10-03 with headcount 15 and 3 open roles, and row-4 for group-b on 2026-10-04 with headcount 30 and 4 open roles.","exampleUseCases":[{"title":"HR data cleaning before reporting","prompt":"I have a batch of 50 company headcount records with messy string values in the company_group field — can you normalize those strings and tell me how frequently each group appears? Here are the rows with row IDs, dates, headcount counts, and open role counts."},{"title":"Workforce distribution audit by company group","prompt":"We collected headcount and open_roles observations across 3 company groups over the last quarter — can you run string normalization and category frequency analysis on these 120 rows so I can see which groups dominate the dataset?"},{"title":"Recruiting data quality check","prompt":"Before we import this recruiting dataset into our dashboard, can you normalize the company group labels and calculate how often each category shows up across these 80 headcount observation rows with their open_roles values?"}],"resultDescription":"Two analytical reports for the supplied rows: (1) a string normalisation report for the headcount and open_roles observation records (standardising company_group and other string fields), and (2) category frequency counts showing how often each distinct company_group value appears across the submitted rows. Results are computed locally with no external lookups.","failureModes":["Rows array exceeds 200 items — request rejected","Missing required fields (row_id, company_group, date, headcount, or open_roles) — validation error","Date field does not match YYYY-MM-DD pattern — schema validation failure","Numeric fields (headcount, open_roles) out of allowed range — validation error","Empty rows array — minimum 1 item required","Payment of 0.01 USDC not fulfilled — 402 response"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and category frequency analysis on company headcount observations in a single low-cost call. It is ideal for preprocessing HR or workforce datasets before importing into dashboards, detecting inconsistent company_group labels, or auditing the distribution of headcount and open_roles records across groups. Not suitable for live lookups, predictions, or datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:31.341Z","isFirstParty":false,"canonicalSlug":"company-headcount-observations-string-normalisation-category-e7cf1ca7"}