{"uid":"cap_FzW3QlopzAuFzXXBviaAg","slug":"air-quality-observations-adjacent-row-changes-2e0f28d9","name":"Air Quality Observations – Adjacent Row Changes","description":"Air quality observations - Adjacent row changes: Adjacent row changes for Air quality observations. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded adjacent row changes report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-air-quality-observations-period-change?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station","date","pm25","humidity_percent"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"pm25":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"station":{"type":"string","default":"","maxLength":80},"humidity_percent":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","pm25":10,"row_id":"row-1","station":"group-a","humidity_percent":1},{"date":"2026-10-02","pm25":20,"row_id":"row-2","station":"group-b","humidity_percent":2},{"date":"2026-10-03","pm25":15,"row_id":"row-3","station":"group-a","humidity_percent":3},{"date":"2026-10-04","pm25":30,"row_id":"row-4","station":"group-b","humidity_percent":4}],"maxItems":200,"minItems":1},"field":{"enum":["pm25","humidity_percent"],"type":"string","default":"pm25"}}},"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_PwNYT0xQqgF65nzxIfDG5","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":"Computes row-to-row (period-over-period) changes in air quality metrics (PM2.5 or humidity) across up to 200 supplied observation records.","exampleAgentPrompt":"I have a list of daily air quality readings from several stations — can you calculate the adjacent row changes in PM2.5 for these records: station A on 2024-01-01 with PM2.5=12 and humidity=45, station A on 2024-01-02 with PM2.5=18 and humidity=50, station B on 2024-01-03 with PM2.5=9 and humidity=38?","exampleUseCases":[{"title":"Daily pollution spike detection","prompt":"Here are a week's worth of PM2.5 readings from our downtown monitoring station — can you calculate how much the pollution level changed between each consecutive day so I can spot any sudden spikes?"},{"title":"Multi-station humidity trend review","prompt":"I've got humidity readings from three different air quality stations across the month of March — can you compute the day-over-day humidity_percent changes for each row so I can see which periods had the sharpest swings?"},{"title":"Environmental compliance change audit","prompt":"We need to audit our air quality sensor logs for consecutive measurement changes in PM2.5 — here are 150 rows with station, date, PM2.5, and humidity values. Can you run the adjacent row change analysis on the pm25 field?"}],"resultDescription":"A bounded descriptive analytics report showing the row-to-row change in the chosen field (PM2.5 or humidity_percent) for each consecutive pair of supplied observation records, with no external enrichment or forecasting applied.","failureModes":["Fewer than 1 row supplied — minItems validation failure","More than 200 rows supplied — maxItems validation failure","Missing required fields (row_id, station, date, pm25, humidity_percent) — schema validation error","Invalid date format (not YYYY-MM-DD) — pattern validation error","Invalid field enum value (not 'pm25' or 'humidity_percent') — enum validation error","Null numeric values in the selected field — may produce null/undefined delta for affected rows","Payment failure — x402 protocol payment not completed"],"whenToPreferThis":"Choose this endpoint when you have a local batch of timestamped air quality observations and need fast, inexpensive period-over-period change calculations without external data enrichment or forecasting. Ideal for auditing sensor logs, spotting consecutive reading anomalies, or generating a simple delta report before further analysis. Not suitable when you need forecast data, cross-dataset enrichment, or more than 200 records processed at once.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T19:13:11.900Z","isFirstParty":false,"canonicalSlug":"air-quality-observations-adjacent-row-changes-2e0f28d9"}