{"uid":"cap_a7yfNKbZzE1qs27FjKjkz","slug":"company-headcount-observations-string-normalisation-numeric-row-2505f0b8","name":"Company Headcount Observations — String Normalisation + Numeric Row Ordering","description":"Company headcount observations — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering 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-12-025?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_-FMADoZd7DE2jhCgJmCMz","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 company group strings and orders rows numerically for up to 200 company headcount observation records across headcount and open_roles fields, returning 2 analytical reports per call.","exampleAgentPrompt":"Take these 4 company headcount observation rows — group-a on 2026-10-01 with 10 headcount and 1 open role, group-b on 2026-10-02 with 20 headcount and 2 open roles, group-a on 2026-10-03 with 15 headcount and 3 open roles, group-b on 2026-10-04 with 30 headcount and 4 open roles — and run string normalisation plus numeric row ordering on the headcount field, giving me both analytical reports.","exampleUseCases":[{"title":"Standardise workforce snapshot exports","prompt":"I have 50 rows of company headcount observations exported from our HRIS — the company_group names are inconsistently cased and I need them normalised and the rows ordered by headcount numerically. Can you run string normalisation and numeric ordering on the headcount field for me?"},{"title":"Rank open roles across business units","prompt":"Here are 120 headcount observation records for our business units across Q4. I need the company group strings cleaned up and all rows ranked by open_roles so I can see which units have the most vacancies at a glance — please run both reports."},{"title":"Prepare hiring data for dashboard ingestion","prompt":"Before I load these 80 company headcount rows into our analytics dashboard, can you normalise the company group labels and sort everything by headcount so the data is consistent and ordered? Use the headcount field for the numeric ordering."}],"resultDescription":"Returns 2 analytical reports: one applying string normalisation to the company_group field across all supplied rows, and one ordering rows numerically by the selected field (headcount or open_roles). Up to 200 rows processed per call. No external lookups or predictions are made — all processing uses local analytical engines.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, company_group, date, headcount, open_roles) on any row causes validation failure","Date field not matching YYYY-MM-DD pattern causes rejection","Payment of 0.01 USDC not provided — x402 payment required before processing","Invalid field enum value (not 'headcount' or 'open_roles') causes error","Empty rows array (minItems: 1 not met) causes rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 company headcount observation records and need both string normalisation of company group labels and numeric ordering of headcount or open_roles values in a single low-cost call. It is purpose-built for workforce/HR observation data with the specific schema (row_id, company_group, date, headcount, open_roles) and delivers two independent reports simultaneously. Prefer this over general-purpose data transformation tools when you are working specifically with headcount or open_roles timeseries rows and want a lightweight, offline (no live lookup) analytical pass at $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:52:18.514Z","isFirstParty":false,"canonicalSlug":"company-headcount-observations-string-normalisation-numeric-row-2505f0b8"}