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scribe

Build transcription workflows for uploaded or stored audio and video using Zoom AI Services Scribe. Consult guidance on authentication, single-file requests, batch jobs, completion notifications, and saving transcript results for further processing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Reference skill for Zoom AI Services Scribe. Use after routing to a transcription workflow when handling uploaded or stored media, Build-platform JWT auth, fast mode transcription, batch jobs, or transcript pipeline design.

anthropics/knowledge-work-plugins
연동 도구Zoom
설치 방법 보기

이럴 때 유용합니다

  • Adding transcription for uploaded recordings
  • Transcribing stored call archives in batches
  • Saving transcripts after job completion notifications
  • Investigating browser timeouts during transcription

포함된 파일(11)

  • SKILL.md5.8 KB
  • concepts/auth-and-processing-modes.md3.2 KB
  • examples/batch-webhook-pipeline.md1.6 KB
  • examples/fast-mode-node.md1.8 KB
  • references/api-reference.md2.6 KB
  • references/environment-variables.md1.5 KB
  • references/samples-validation.md2.0 KB
  • references/versioning-and-drift.md2.0 KB
  • RUNBOOK.md4.2 KB
  • scenarios/high-level-scenarios.md3.1 KB
  • troubleshooting/common-drift-and-breaks.md4.6 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Zoom AI Services Scribe

Background reference for Zoom AI Services Scribe across:

  • synchronous single-file transcription (POST /aiservices/scribe/transcribe)
  • asynchronous batch jobs (/aiservices/scribe/jobs*)
  • browser microphone pseudo-streaming via repeated short file uploads
  • webhook-driven batch status updates
  • Build-platform JWT generation and credential handling

Official docs:

Routing Guardrail

  • If the user needs uploaded or stored media transcribed into text, route here first.
  • If the user needs live meeting media without file-based upload/batch jobs, route to ../rtms/SKILL.md.
  • If the user needs Zoom REST API inventory for AI Services paths, chain ../rest-api/SKILL.md.
  • If the user needs webhook signature patterns or generic HMAC receiver hardening, optionally chain ../webhooks/SKILL.md.

Quick Links

  1. concepts/auth-and-processing-modes.md
  2. scenarios/high-level-scenarios.md
  3. examples/fast-mode-node.md
  4. examples/batch-webhook-pipeline.md
  5. references/api-reference.md
  6. references/environment-variables.md
  7. references/samples-validation.md
  8. references/versioning-and-drift.md
  9. troubleshooting/common-drift-and-breaks.md
  10. RUNBOOK.md

Core Workflow

  1. Get Build-platform credentials and generate an HS256 JWT.
  2. Choose fast mode for one short file or batch mode for stored archives / large sets.
  3. Submit the transcription request.
  4. For batch jobs, poll job/file status or receive webhook notifications.
  5. Persist and post-process transcript JSON.

Hosted Fast-Mode Guardrail

  • The formal fast-mode API limits are 100 MB and 2 hours, but hosted browser flows can still time out before the upstream response returns.
  • Current deployed-sample observations:
    • ~17.2 MB MP4 completed in about 26s
    • ~38.6 MB MP4 completed in about 26-37s
    • ~59.2 MB MP4 completed in about 32-34s on the backend
    • some ~59.2 MB browser requests still surfaced as frontend 504 while backend logs later showed 200
  • Treat frontend 504 plus backend 200 as a browser/edge timeout race, not an automatic transcription failure.
  • For hosted UIs, prefer an async request/polling wrapper for fast mode instead of holding the browser open for the full upstream response.
  • For larger or less predictable media, prefer batch mode even when the file is still within the formal fast-mode size limit.

Browser Microphone Pattern

  • scribe does not expose a documented real-time streaming API surface.
  • If you want a browser microphone experience, use pseudo-streaming:
    1. capture microphone audio in short chunks
    2. upload each chunk through the async fast-mode wrapper
    3. poll for completion
    4. append chunk transcripts in sequence
  • Recommended starting cadence:
    • chunk size: 5 seconds
    • acceptable range: 5-10 seconds
    • in-flight chunk requests: 2-3
  • This is a practical UI pattern for incremental transcript updates, not a substitute for rtms.
  • Treat this as a fallback demo pattern, not the preferred production architecture.
  • It adds repeated upload overhead, chunk-boundary drift, browser codec/container variability, and transcript stitching complexity.
  • If the user asks for actual live stream ingestion, low-latency continuous media, or server-push media transport, route to ../rtms/SKILL.md instead.

Endpoint Surface

ModeMethodPathUse
FastPOST/aiservices/scribe/transcribeSynchronous transcription for one file
BatchPOST/aiservices/scribe/jobsSubmit asynchronous batch job
BatchGET/aiservices/scribe/jobsList jobs
BatchGET/aiservices/scribe/jobs/{jobId}Inspect job summary/state
BatchDELETE/aiservices/scribe/jobs/{jobId}Cancel queued/processing job
BatchGET/aiservices/scribe/jobs/{jobId}/filesInspect per-file results

High-Level Scenarios

  • On-demand clip transcription after a user uploads one recording.
  • Batch transcription of stored S3 call archives.
  • Webhook-driven ETL pipeline that writes transcripts to your database/search index.
  • Re-transcription of Zoom-managed recordings after exporting them to your own storage.
  • Offline compliance or QA workflows that need timestamps, channel separation, and speaker hints.

Chaining

Operations

  • RUNBOOK.md - 5-minute preflight and debugging checklist.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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