{"uid":"cap_qXltSCJUYQ-wN392u6gVT","slug":"tree-canopy-observations-record-quality-audit-string-normalisation-05d83336","name":"Tree Canopy Observations — Record Quality Audit + String Normalisation + Base-100 Series","description":"Tree canopy observations — Record quality audit + String normalisation + Base-100 series: Record quality audit + String normalisation + Base-100 series for supplied tree canopy observations records (canopy_m2, plot_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-17-201?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","canopy_m2","plot_m2"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"plot_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"canopy_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","plot_m2":1,"canopy_m2":10,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","plot_m2":2,"canopy_m2":20,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","plot_m2":3,"canopy_m2":15,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","plot_m2":4,"canopy_m2":30,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["canopy_m2","plot_m2"],"type":"string","default":"canopy_m2"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_VQP783FDpZSpGQH4k6vCZ","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":"Runs three analytical reports on tree canopy observation records: a record quality audit, string normalisation, and a base-100 indexed time series — all computed locally without external lookups.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and base-100 index series on my tree canopy observations? I have up to 50 rows with fields row_id, station_group, date, canopy_m2, and plot_m2 — index on canopy_m2 starting from row 0.","exampleUseCases":[{"title":"Urban forestry canopy data QA","prompt":"I have 120 rows of tree canopy observation records with canopy_m2 and plot_m2 measurements across several station groups — can you run all three reports: record quality audit, string normalisation, and a base-100 series for canopy_m2 starting at index 0, so I can spot bad data before analysis?"},{"title":"Baseline canopy trend indexing","prompt":"Please generate a base-100 indexed series for the plot_m2 field in my canopy dataset starting from row 5, along with a quality audit and string normalisation report — I want to track relative change in plot size across dates."},{"title":"Station label consistency check","prompt":"My tree canopy dataset has inconsistent station_group labels across 80 rows — can you run the string normalisation and record quality audit reports on it, plus the base-100 series for canopy_m2 from index 0, so I can clean it up before merging with another dataset?"}],"resultDescription":"Returns three reports for the supplied canopy observation rows: (1) a record quality audit flagging missing, null, or malformed values; (2) a string normalisation report for the station_group field; and (3) a base-100 indexed numeric series for the chosen field (canopy_m2 or plot_m2) anchored at the specified base row index.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, date, canopy_m2, plot_m2) cause row-level errors","Invalid date format (not YYYY-MM-DD) triggers pattern validation failure","base_index out of range (>= number of rows) causes index computation error","Payment not included or insufficient USDC causes 402 rejection","All null values in the selected field may produce an empty or degenerate base-100 series"],"whenToPreferThis":"Choose this endpoint when you have tree canopy observation records (canopy_m2, plot_m2) and need all three of: a data quality audit, string normalisation of categorical labels, and a base-100 time series — in a single call at low cost. It is ideal for pre-analysis data cleaning pipelines where the dataset is up to 200 rows and no external data enrichment or prediction is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:52:17.414Z","isFirstParty":false,"canonicalSlug":"tree-canopy-observations-record-quality-audit-string-normalisation-05d83336"}