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by anthropic · part of anthropics/knowledge-work-plugins

Reference skill for Zoom AI Services Scribe. Use after routing to a transcription workflow when handling uploaded or stored media, Build-platform JWT auth,…

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Reference skill for Zoom AI Services Scribe. Use after routing to a transcription workflow when handling uploaded or stored media, Build-platform JWT auth,…

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by anthropic

Reference skill for Zoom AI Services Scribe. Use after routing to a transcription workflow when handling uploaded or stored media, Build-platform JWT auth,… npx skills add https://github.com/anthropics/knowledge-work-plugins --skill scribe Download ZIPGitHub22.3k

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

Core Workflow

  • Get Build-platform credentials and generate an HS256 JWT.

  • Choose fast mode for one short file or batch mode for stored archives / large sets.

  • Submit the transcription request.

  • For batch jobs, poll job/file status or receive webhook notifications.

  • 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:

  • capture microphone audio in short chunks

  • upload each chunk through the async fast-mode wrapper

  • poll for completion

  • 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

Mode Method Path Use Fast POST /aiservices/scribe/transcribe Synchronous transcription for one file Batch POST /aiservices/scribe/jobs Submit asynchronous batch job Batch GET /aiservices/scribe/jobs List jobs Batch GET /aiservices/scribe/jobs/{jobId} Inspect job summary/state Batch DELETE /aiservices/scribe/jobs/{jobId} Cancel queued/processing job Batch GET /aiservices/scribe/jobs/{jobId}/files Inspect 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.