{"uid":"cap_gWIACrIuQjiNfawJAz_Rd","slug":"field-survey-coverage-data-quality-suite-70f469a6","name":"Field Survey Coverage Data Quality Suite","description":"Field survey coverage — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication for supplied field survey coverage records (surveyed_m2, target_m2). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-weather-22-191?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}}},"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_hI1fTcFsuUWTRUsd6OCnH","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, normalises, and deduplicates up to 200 field survey coverage records (surveyed_m2, target_m2) across three independent analytical reports.","exampleAgentPrompt":"Can you run a full data quality check on my field survey coverage data — I need record quality audit, string normalisation, and exact row deduplication reports for these rows with surveyed_m2 and target_m2 values across different station groups and dates?","exampleUseCases":[{"title":"Pre-analysis survey dataset cleanup","prompt":"I have 150 rows of field survey coverage records with station_group names, dates, surveyed_m2 and target_m2 values — can you audit the record quality, normalise the station group strings, and flag any exact duplicate rows before I hand this off to the analysis team?"},{"title":"Ecological survey QA before reporting","prompt":"Before I submit this ecological survey dataset to our compliance team, can you run the three quality checks — record audit, string normalisation, and deduplication — on these 80 survey coverage rows so I can catch any issues first?"},{"title":"Automated pipeline data validation step","prompt":"As part of our weekly survey pipeline, run a record quality audit, string normalisation, and exact row deduplication on this batch of up to 200 field survey coverage records with surveyed_m2 and target_m2 columns and give me all three reports."}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging issues such as missing or invalid values in the survey rows, (2) a string normalisation report for fields like station_group, and (3) an exact row deduplication report identifying fully duplicate rows. All reports are derived from the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — endpoint rejects with row count exceeded error","Missing required fields (row_id, station_group, date, surveyed_m2, target_m2) cause validation failure","Malformed date strings not matching YYYY-MM-DD pattern are rejected","Empty rows array returns an error","Numeric values outside allowed range (±1,000,000,000,000) may be flagged or rejected"],"whenToPreferThis":"Choose this endpoint when you have structured field survey coverage tabular data (with surveyed_m2 and target_m2 columns) and need three bundled data quality operations — record audit, string normalisation, and exact deduplication — in a single low-cost call without requiring external data sources or live lookups. It is well-suited for pre-analysis data cleaning pipelines handling up to 200 rows of environmental or area-coverage survey records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T00:39:01.449Z","isFirstParty":false,"canonicalSlug":"field-survey-coverage-data-quality-suite-70f469a6"}