{"uid":"cap_yxE9dGhSvPNtN3UznndFD","slug":"field-survey-coverage-string-normalisation-secondary-measure-weighted-e3b7ee75","name":"Field Survey Coverage — String Normalisation + Secondary-Measure Weighted Mean","description":"Field survey coverage — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied field survey coverage records (surveyed_m2, target_m2). 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-weather-22-034?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","surveyed_m2","target_m2"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"target_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"surveyed_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","target_m2":1,"surveyed_m2":10,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","target_m2":2,"surveyed_m2":20,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","target_m2":3,"surveyed_m2":15,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","target_m2":4,"surveyed_m2":30,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["surveyed_m2","target_m2"],"type":"string","default":"surveyed_m2"}}},"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_Kq5wDW0Mfk2SVEzNk69G3","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 a secondary-measure weighted mean for up to 200 field survey coverage records (surveyed_m2, target_m2), returning two analytical reports.","exampleAgentPrompt":"Can you normalise the station group strings and compute a surveyed_m2 weighted mean for these four survey records: row-1 on 2026-10-01 with surveyed_m2=10 and target_m2=1 for group-a, row-2 on 2026-10-02 with surveyed_m2=20 and target_m2=2 for group-b, row-3 on 2026-10-03 with surveyed_m2=15 and target_m2=3 for group-a, and row-4 on 2026-10-04 with surveyed_m2=30 and target_m2=4 for group-b?","exampleUseCases":[{"title":"Ecology plot coverage summary","prompt":"I have 50 ecology survey rows with station groups, dates, and surveyed_m2 and target_m2 values — can you normalise the group name strings and give me a surveyed_m2 weighted mean across all of them?"},{"title":"Target area compliance check","prompt":"Run string normalisation and a target_m2 weighted mean on my field coverage dataset — I have 120 rows with row IDs, dates, station groups, and both surveyed and target square metre readings, and I want to see whether we're hitting our targets on average."},{"title":"Multi-station survey aggregation","prompt":"I've collected 80 field survey records across three station groups over the past quarter. Can you normalise the station group labels and compute the weighted mean of surveyed_m2 weighted by target_m2 so I can compare coverage performance across groups?"}],"resultDescription":"Two analytical reports per call: (1) a string normalisation report cleaning the station_group and related text fields across all submitted rows, and (2) a secondary-measure weighted mean report computing the weighted average of the selected field (surveyed_m2 or target_m2) across up to 200 rows, using local analytical engines with no external lookups.","failureModes":["More than 200 rows submitted — request rejected with validation error","Missing required fields (row_id, date, surveyed_m2, target_m2) — row-level validation failure","Date field not matching YYYY-MM-DD pattern — schema validation error","Null values for both measures across all rows — weighted mean undefined or zero","Numeric values outside ±1 trillion range — rejected by schema bounds"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and a weighted mean statistic on field survey coverage data (surveyed_m2/target_m2) in a single cheap call. It is ideal for small-to-medium datasets (up to 200 rows) where no live data lookup, external enrichment, or prediction is required — purely local analytical processing on your supplied records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:33:30.877Z","isFirstParty":false,"canonicalSlug":"field-survey-coverage-string-normalisation-secondary-measure-weighted-e3b7ee75"}