{"uid":"cap_rxoswQfgikAGDfrMAsXRn","slug":"study-recruitment-string-normalisation-numeric-interval-filter-ef73dc5b","name":"Study Recruitment String Normalisation + Numeric Interval Filter","description":"Study recruitment — String normalisation + Numeric interval filter: String normalisation + Numeric interval filter for supplied study recruitment records (eligible_candidates, enrolled_candidates). 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-education-09-026?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","course_group","date","eligible_candidates","enrolled_candidates"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"course_group":{"type":"string","default":"","maxLength":80},"eligible_candidates":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"enrolled_candidates":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","course_group":"group-a","eligible_candidates":10,"enrolled_candidates":1},{"date":"2026-10-02","row_id":"row-2","course_group":"group-b","eligible_candidates":20,"enrolled_candidates":2},{"date":"2026-10-03","row_id":"row-3","course_group":"group-a","eligible_candidates":15,"enrolled_candidates":3},{"date":"2026-10-04","row_id":"row-4","course_group":"group-b","eligible_candidates":30,"enrolled_candidates":4}],"maxItems":200,"minItems":1},"field":{"enum":["eligible_candidates","enrolled_candidates"],"type":"string","default":"eligible_candidates"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_5ynNwy-Z5tePKsKNQBCzt","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 filters study recruitment rows by a numeric interval (min/max) on eligible or enrolled candidates, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Normalise the course group strings and filter my study recruitment records to only those where eligible_candidates is between 5 and 50 — here are my rows: [{\"row_id\":\"r1\",\"course_group\":\"Group A\",\"date\":\"2026-10-01\",\"eligible_candidates\":10,\"enrolled_candidates\":3}]. Give me both analytical reports.","exampleUseCases":[{"title":"Filter recruitment by eligible candidate count","prompt":"I have 120 rows of study recruitment data and I want to keep only the records where eligible_candidates is between 20 and 200. Can you also normalise the course_group strings and give me both reports? Here's the data as a JSON array with row_id, course_group, date, eligible_candidates, and enrolled_candidates."},{"title":"Audit enrolled candidate thresholds","prompt":"For my clinical study records, filter on the enrolled_candidates field and flag any rows where the value falls between 1 and 15 — normalise the course group names too and return the two analytical reports. I have about 80 rows to process."},{"title":"Clean recruitment data for course groups","prompt":"I need to normalise the course_group strings across my 50 study recruitment rows and then filter eligible_candidates to only show values from 0 to 100. Run both reports and send back the results."}],"resultDescription":"Returns two independent analytical reports covering: (1) normalised string values for the course_group field across all submitted rows, and (2) rows filtered to those where the selected numeric field (eligible_candidates or enrolled_candidates) falls within the specified minimum–maximum interval. Up to 200 input rows processed per call.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, eligible_candidates, enrolled_candidates) causes row rejection","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Minimum value greater than maximum value may return empty filter results","Null numeric values for the selected field may be excluded from interval filter output"],"whenToPreferThis":"Choose this endpoint when you need to both clean/normalise string fields and apply a numeric range filter to study recruitment or course enrollment records in a single low-cost call. It is ideal for small-to-medium datasets (up to 200 rows) where you want two co-generated reports without external lookups or live data sources. Not suitable for real-time data enrichment, predictive analytics, or datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:52:44.835Z","isFirstParty":false,"canonicalSlug":"study-recruitment-string-normalisation-numeric-interval-filter-ef73dc5b"}