{"uid":"cap_XHFu8aqLAO49LSsHBy_qd","slug":"peer-feedback-string-normalisation-numeric-interval-filter-dab59e86","name":"Peer Feedback String Normalisation + Numeric Interval Filter","description":"Peer feedback — String normalisation + Numeric interval filter: String normalisation + Numeric interval filter 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-23-026?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_PUaYBaiMJ63DNpjZHwoVZ","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 string fields and filters rows by a numeric interval for peer feedback records containing review_count and actioned_comments fields, returning up to 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Take my peer feedback records for groups A and B across October 2026 and normalize the course_group strings, then filter rows where review_count is between 10 and 25 — I have 4 rows total.","exampleUseCases":[{"title":"Filter reviews by activity threshold","prompt":"I have a set of peer feedback records for my online courses and I want to keep only the rows where review_count falls between 5 and 50 — can you normalize the course group names and apply that interval filter across my 120 rows?"},{"title":"Validate actioned comments range","prompt":"Can you run my 80 peer feedback rows through string normalization on the course_group field and filter so I only see records where actioned_comments is between 1 and 10?"},{"title":"Education cohort feedback cleanup","prompt":"I've got peer review data from two course cohorts — normalize the group name strings and give me only the rows where review_count is between 0 and 30, using my 50 feedback records."}],"resultDescription":"Returns up to 2 analytical reports per call covering: (1) normalised string fields for course_group and related text columns, and (2) rows filtered to only those where the chosen numeric field (review_count or actioned_comments) falls within the specified [minimum, maximum] interval, for up to 200 input rows.","failureModes":["Input array exceeds 200 rows — request will be rejected","Missing required row fields (row_id, date, review_count, actioned_comments) cause validation errors","Date field not matching YYYY-MM-DD pattern causes schema rejection","minimum greater than maximum results in empty filtered output or error","Null numeric values in review_count or actioned_comments may be excluded from interval filtering"],"whenToPreferThis":"Choose this endpoint when you have peer feedback or education review datasets (up to 200 rows) that need both string normalization on categorical fields like course_group and numeric range filtering on review_count or actioned_comments. It is ideal for lightweight, offline analytical preprocessing of structured tabular feedback data without needing a live database, prediction model, or external lookup service.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T12:44:59.874Z","isFirstParty":false,"canonicalSlug":"peer-feedback-string-normalisation-numeric-interval-filter-dab59e86"}