{"uid":"cap_BMZu4x7tElfdhc6-NXRj6","slug":"interview-transcripts-string-normalisation-keyed-dataset-comparison-5b51bd9e","name":"Interview Transcripts — String Normalisation + Keyed Dataset Comparison","description":"Interview transcripts — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison for supplied interview transcripts records (transcript_words, audio_minutes). 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-news-12-036?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","channel_group","date","transcript_words","audio_minutes"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"audio_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"channel_group":{"type":"string","default":"","maxLength":80},"transcript_words":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","audio_minutes":1,"channel_group":"group-a","transcript_words":10},{"date":"2026-10-02","row_id":"row-2","audio_minutes":2,"channel_group":"group-b","transcript_words":20},{"date":"2026-10-03","row_id":"row-3","audio_minutes":3,"channel_group":"group-a","transcript_words":15},{"date":"2026-10-04","row_id":"row-4","audio_minutes":4,"channel_group":"group-b","transcript_words":30}],"maxItems":200,"minItems":1},"other":{"type":"array","items":{"type":"object","required":["row_id","channel_group","date","transcript_words","audio_minutes"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"audio_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"channel_group":{"type":"string","default":"","maxLength":80},"transcript_words":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","audio_minutes":1,"channel_group":"group-a","transcript_words":10},{"date":"2026-10-02","row_id":"row-2","audio_minutes":2,"channel_group":"group-b","transcript_words":21},{"date":"2026-10-03","row_id":"row-3","audio_minutes":3,"channel_group":"group-a","transcript_words":17},{"date":"2026-10-04","row_id":"row-4","audio_minutes":4,"channel_group":"group-b","transcript_words":33}],"maxItems":200,"minItems":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_jkDr96w7reYxsqYk8zkFa","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 performs keyed dataset comparison on two sets of interview transcript records (transcript_words, audio_minutes), returning 2 analytical reports for up to 200 rows each.","exampleAgentPrompt":"Compare these two sets of interview transcript records for me — one is my baseline and one is the updated version — normalise the strings and tell me where the transcript_words and audio_minutes differ by row_id and channel_group. I have about 50 rows in each set.","exampleUseCases":[{"title":"Audit transcript pipeline output differences","prompt":"I ran our interview transcripts through two different processing pipelines and I need to compare the word counts and audio minutes row by row — can you normalise the strings and highlight where the two datasets diverge? I have 80 rows in each set, keyed by row_id."},{"title":"QA check across interviewer channel groups","prompt":"We have transcript data from two rounds of interviews, both with up to 120 rows, and I want to see if the transcript_words and audio_minutes are consistent across channel groups between the two rounds — run the string normalisation and keyed comparison for me."},{"title":"Validate transcript records before merging datasets","prompt":"Before I merge these two interview transcript datasets — each about 150 rows — I need a report showing any mismatches in transcript_words or audio_minutes when matched by row_id and channel_group, with strings normalised first."}],"resultDescription":"Returns 2 independent analytical reports: one covering string normalisation of the supplied transcript fields (transcript_words, audio_minutes) and one covering keyed dataset comparison between the 'rows' and 'other' input arrays, matched by row_id. Reports are generated locally with no external lookups, covering up to 200 rows per dataset.","failureModes":["More than 200 rows submitted — request rejected with validation error","Missing required fields (row_id, channel_group, date, transcript_words, audio_minutes) — row-level validation failure","Invalid date format (not YYYY-MM-DD) — schema validation error","Empty rows array — minItems constraint violation","Numeric values outside allowed range — schema rejection"],"whenToPreferThis":"Choose this endpoint when you need to compare two structured interview transcript datasets side-by-side using keyed matching (by row_id) and also want string normalisation applied, all within a single low-cost call. It is ideal for data quality audits, pipeline output validation, or pre-merge checks on transcript records up to 200 rows. It does not perform live transcription, prediction, or AI-based assessment — use it for deterministic analytical reporting on already-captured transcript data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:34:06.220Z","isFirstParty":false,"canonicalSlug":"interview-transcripts-string-normalisation-keyed-dataset-comparison-5b51bd9e"}