{"uid":"cap_3LMx-zr0nPkWz7hOVBnkE","slug":"texture-streaming-analytics-string-normalisation-adjacent-row-changes-ecda2cc7","name":"Texture Streaming Analytics — String Normalisation + Adjacent Row Changes","description":"Texture streaming — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied texture streaming records (loaded_mb, stream_ms). 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-game-09-029?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","game_area","date","loaded_mb","stream_ms"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"game_area":{"type":"string","default":"","maxLength":80},"loaded_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"stream_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","game_area":"group-a","loaded_mb":10,"stream_ms":1},{"date":"2026-10-02","row_id":"row-2","game_area":"group-b","loaded_mb":20,"stream_ms":2},{"date":"2026-10-03","row_id":"row-3","game_area":"group-a","loaded_mb":15,"stream_ms":3},{"date":"2026-10-04","row_id":"row-4","game_area":"group-b","loaded_mb":30,"stream_ms":4}],"maxItems":200,"minItems":1},"field":{"enum":["loaded_mb","stream_ms"],"type":"string","default":"loaded_mb"}}},"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_pwQ_M0Lc1hRFzlddCXoxe","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":"Analyzes texture streaming records (loaded_mb, stream_ms) by applying string normalisation and computing adjacent row changes across up to 200 supplied rows.","exampleAgentPrompt":"I have 4 texture streaming records — row-1 on 2026-10-01 for group-a with loaded_mb=10 and stream_ms=1, row-2 on 2026-10-02 for group-b with loaded_mb=20 and stream_ms=2, row-3 on 2026-10-03 for group-a with loaded_mb=15 and stream_ms=3, row-4 on 2026-10-04 for group-b with loaded_mb=30 and stream_ms=4 — can you run string normalisation and adjacent row change analysis on the loaded_mb field?","exampleUseCases":[{"title":"Game area streaming load delta tracking","prompt":"I've got daily texture streaming records for two game areas over a week — can you normalise the area name strings and compute the adjacent row changes in loaded_mb so I can see how load shifts between consecutive days?"},{"title":"Stream latency change detection across sessions","prompt":"Here are 50 rows of texture streaming session data with stream_ms readings. Run string normalisation and adjacent row change analysis on the stream_ms field so I can spot where latency jumps between back-to-back sessions."},{"title":"QA audit of texture streaming pipeline output","prompt":"We just ran our texture streaming pipeline and got 120 records across several game areas. Can you normalise the game_area strings and report the row-to-row differences in loaded_mb to help us catch any anomalies in the output?"}],"resultDescription":"Returns two analytical reports: one for string normalisation applied to the game area and related string fields, and one showing adjacent (consecutive) row changes in the selected numeric metric (loaded_mb or stream_ms), covering up to 200 input rows with no external data lookups.","failureModes":["More than 200 rows submitted — request rejected at maxItems limit","Missing required fields (row_id, date, game_area, loaded_mb, stream_ms) — validation error","Invalid date format (not YYYY-MM-DD) — schema pattern mismatch","Invalid field enum value (not loaded_mb or stream_ms) — rejected","Null numeric values in selected field may produce null deltas in adjacent row report"],"whenToPreferThis":"Choose this endpoint when you have raw texture streaming records and need both string normalization of categorical fields and row-to-row delta computation on a numeric streaming metric in a single low-cost call. It is best suited for offline batch analysis of up to 200 rows of game telemetry data where no live lookup or prediction is required.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:49:43.702Z","isFirstParty":false,"canonicalSlug":"texture-streaming-analytics-string-normalisation-adjacent-row-changes-ecda2cc7"}