{"uid":"cap_R1XjAqGnXuRGgAZu6w9ti","slug":"job-listing-inventories-record-quality-audit-string-normalisation-fe54515d","name":"Job Listing Inventories — Record Quality Audit & String Normalisation","description":"Job listing inventories — Record quality audit + String normalisation: Record quality audit + String normalisation for supplied job listing inventories records (listing_count, duplicate_listings). 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-13-001?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","listing_count","duplicate_listings"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_group":{"type":"string","default":"","maxLength":80},"listing_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"duplicate_listings":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","listing_count":10,"duplicate_listings":1},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","listing_count":20,"duplicate_listings":2},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","listing_count":15,"duplicate_listings":3},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","listing_count":30,"duplicate_listings":4}],"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_MjLKeEuvbVu0NR1b5xmT5","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 and normalises strings for up to 200 rows of job listing inventory data (listing_count, duplicate_listings), producing two independent analytical reports.","exampleAgentPrompt":"Can you audit the quality and normalise the strings in this job listing inventory dataset? I have 4 rows with fields row_id, company_group, date, listing_count, and duplicate_listings — for example row-1 is group-a on 2026-10-01 with 10 listings and 1 duplicate. Run both the record quality audit and string normalisation reports.","exampleUseCases":[{"title":"Pre-pipeline data quality gate","prompt":"Before I load this batch of job listing records into our data warehouse, can you run a record quality audit and string normalisation on these 150 rows? Each row has a row_id, company_group, date, listing_count, and duplicate_listings — flag anything that looks malformed or inconsistent."},{"title":"Duplicate listing rate investigation","prompt":"I've got 80 rows of job listing inventory data across several company groups and I'm seeing weirdly high duplicate_listings numbers. Can you audit the record quality and normalise the company_group strings so I can see where the duplication issues are concentrated?"},{"title":"Monthly recruiter data hygiene check","prompt":"At the end of each month I want to clean up our job listing inventory snapshot. Here are 200 rows with row_id, company_group, date, listing_count, and duplicate_listings — please run both the quality audit and the string normalisation report so I can spot any bad records before archiving."}],"resultDescription":"Two independent reports: (1) a record quality audit identifying issues such as missing values, out-of-range numbers, malformed dates, and anomalous listing counts or duplicate rates; (2) a string normalisation report showing standardised or corrected versions of string fields such as company_group. Both reports cover up to 200 supplied rows and are generated locally without external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, company_group, date, listing_count, duplicate_listings) on any row causes validation errors","Malformed date strings not matching YYYY-MM-DD pattern rejected by schema","Numeric values outside allowed range (-1e12 to 1e12) rejected","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you need a fast, low-cost, offline quality audit and string normalisation pass on job listing inventory records (up to 200 rows) without requiring live lookups, predictions, or external integrations. Ideal as a pre-processing or data hygiene step before analytics pipelines, database loads, or reporting.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T00:56:14.800Z","isFirstParty":false,"canonicalSlug":"job-listing-inventories-record-quality-audit-string-normalisation-fe54515d"}