{"uid":"cap_OHaWO5liXoO_0n6ow9mJE","slug":"peer-feedback-string-normalisation-date-by-category-pivot-68e74a07","name":"Peer Feedback String Normalisation + Date by Category Pivot","description":"Peer feedback — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied peer feedback records (review_count, actioned_comments). 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-education-23-035?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","course_group","date","review_count","actioned_comments"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"course_group":{"type":"string","default":"","maxLength":80},"review_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"actioned_comments":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","course_group":"group-a","review_count":10,"actioned_comments":1},{"date":"2026-10-02","row_id":"row-2","course_group":"group-b","review_count":20,"actioned_comments":2},{"date":"2026-10-03","row_id":"row-3","course_group":"group-a","review_count":15,"actioned_comments":3},{"date":"2026-10-04","row_id":"row-4","course_group":"group-b","review_count":30,"actioned_comments":4}],"maxItems":200,"minItems":1},"field":{"enum":["review_count","actioned_comments"],"type":"string","default":"review_count"}}},"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_xcWXJrYEQ8zIG14cSYI3d","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 strings and produces a date-by-category pivot table from peer feedback records containing review counts and actioned comments (up to 200 rows, 2 reports per call).","exampleAgentPrompt":"Can you run string normalisation and a date-by-category pivot on my peer feedback records? I have rows with course_group, date, review_count, and actioned_comments — pivot on review_count across groups like group-a and group-b for dates from 2026-10-01 to 2026-10-04.","exampleUseCases":[{"title":"Course review volume trends by group","prompt":"I have 150 rows of peer feedback from our LMS with fields row_id, course_group, date, review_count, and actioned_comments — can you normalize the strings and pivot review_count by course group and date so I can see which groups had the most reviews each day?"},{"title":"Actioned comments audit across cohorts","prompt":"Please process my peer feedback dataset (about 80 rows, with course_group, date, review_count, and actioned_comments) and give me a string-normalised report plus a date-by-category pivot on actioned_comments so I can track which cohorts are acting on feedback over time."},{"title":"Education program feedback cleanup and summary","prompt":"I've collected peer feedback records from three course groups over the past month — can you normalize the text fields and pivot the review_count data by course_group and date? There are around 60 rows total with the standard row_id, course_group, date, review_count, and actioned_comments fields."}],"resultDescription":"Two analytical reports: (1) a string-normalised version of the supplied peer feedback records, and (2) a date-by-category pivot table for the selected numeric field (review_count or actioned_comments) broken down by course_group and date. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request exceeds maxItems limit and will be rejected","Missing required fields (row_id, course_group, date, review_count, or actioned_comments) causes validation failure","Invalid date format (not YYYY-MM-DD) causes schema validation error","Invalid field enum value (not review_count or actioned_comments) causes rejection","Payment not included or insufficient USDC causes 402 Payment Required response","All-null numeric values may produce empty or degenerate pivot output"],"whenToPreferThis":"Choose this endpoint when you have structured peer feedback data (up to 200 rows) from an education or course context and need both string normalisation and a date-by-category pivot in a single low-cost call ($0.01 USDC for both reports). It is ideal for offline/batch analytical processing of course review data where no live prediction, external lookup, or professional assessment is needed. Prefer alternatives if you need more than 200 rows, real-time enrichment, or different analytical transforms (e.g. histograms, outlier detection, or correlation).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:35:35.282Z","isFirstParty":false,"canonicalSlug":"peer-feedback-string-normalisation-date-by-category-pivot-68e74a07"}