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Scribe

AnthropicOfficialCreated by ZoomDistributed by Anthropic

  • Skill
  • Tool integration
  • Automation and integrations
  • MIT
  • No issues found
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From the author

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.
— the description by Zoom

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Scribe is a Zoom AI service providing transcription capabilities for uploaded or stored media. It supports both synchronous fast-mode transcription for individual files and asynchronous batch processing for larger archives. The skill covers authentication via Build-platform JWTs, API endpoint usage, webhook integration for status updates, and architectural patterns for handling media transcription pipelines.

What it does

  • Provides documentation for synchronous transcription of single media files.
  • Details asynchronous batch job submission and management.
  • Explains Build-platform JWT generation and credential handling.
  • Outlines webhook integration for receiving batch job status notifications.
  • Offers guidance on managing media inputs and transcript outputs via S3.
  • Provides API reference for managing transcription jobs and file results.

When to use it

  • When you need to transcribe stored audio or video files.
  • When implementing batch processing for large sets of media files.
  • When building an ETL pipeline to store transcripts in a database.
  • When you need to integrate Zoom transcription into custom applications using JWT authentication.

Advantages

  • Supports both synchronous and asynchronous processing modes.
  • Enables automated transcription workflows for stored media.
  • Provides structured API endpoints for job lifecycle management.
  • Allows for webhook-driven status tracking for batch operations.

Usage examples

“How do I perform a synchronous transcription of a single audio file?”
The agent provides the endpoint for POST /aiservices/scribe/transcribe and explains the required file and configuration parameters.
“What are the steps to submit a batch transcription job?”
The agent outlines the process of using POST /aiservices/scribe/jobs with S3 source URIs and configuring the necessary output and notification settings.
“How do I authenticate my requests to the Scribe API?”
The agent explains the requirement for generating an HS256 JWT using the Build-platform API key and secret.
“How can I track the status of a batch transcription job?”
The agent describes using the GET /aiservices/scribe/jobs/{jobId} endpoint or configuring a webhook URL for status notifications.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/anthropics/scribe/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip scribe.zip -d .agents/skills

Documentation by Zoom

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

  • Stored Zoom recordings -> ../rest-api/SKILL.md + scribe

  • Webhook verification hardening -> ../webhooks/SKILL.md

  • Real-time live transcript/media -> ../rtms/SKILL.md

  • Cross-product routing -> ../general/SKILL.md

Operations

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

Files

references/samples-validation.md

Samples Validation

Validated against:

  • https://github.com/zoom/scribe-quickstart/

  • official docs pages under docs/ai-services/

  • AI Services OpenAPI inventory at api-hub/ai-services/methods/endpoints.json

  • Zoom blog context:

    • introducing-zoom-ai-services

    • voice-insights-modernize-customer-support-with-scribe

What the official quickstart confirms

  • Node/Express proxy architecture is a valid implementation model.

  • Fast mode can be proxied as multipart upload handling on your server even though the docs show JSON examples.

  • Batch mode commonly injects AWS credentials into request payloads.

  • Webhook verification uses x-zm-signature + x-zm-request-timestamp with HMAC-SHA256 and sha256= prefix.

  • The quickstart uses ZOOM_API_KEY / ZOOM_API_SECRET naming.

Useful implementation details from the sample

  • multer memory storage is enough for a small fast-mode demo.

  • Batch helper routes are naturally expressed as:

    • POST /batch/jobs

    • GET /batch/jobs

    • GET /batch/jobs/:jobId

    • GET /batch/jobs/:jobId/files

    • DELETE /batch/jobs/:jobId

  • It is practical to keep one generateJWT() helper and inject the bearer token per request.

Caveats from the sample

  • It assumes Node >=24, which is stricter than many deployment environments actually need. Verify your runtime before copying that constraint unchanged.

  • It uses environment-injected AWS credentials. Production pipelines may prefer pre-signed URLs or short-lived STS credentials only.

  • The sample is an app demo, not a complete production reference for job retry policy, durable queues, or transcript storage.

What the blog posts add

  • They reinforce the highest-value downstream use cases:

    • post-call summaries

    • ticket enrichment

    • compliance/audit logging

    • searchable archives

    • customer-support QA workflows

  • They are useful for scenario framing, but not as authoritative API surface documentation.

  • Keep endpoint and request-shape decisions anchored to the AI Services docs and API Hub inventory, not the blog wording.

Requirements and compatibility

Written for: Claude Code, Claude apps

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter, Needs Node.js

Security

No issues found by our static scan· No issues found

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Attribution and licence

Created by
Zoom
Publisher
Anthropic (Official)
Distributed by
Anthropic
Source
anthropics/knowledge-work-plugins · partner-built/zoom-plugin/skills/scribe · commit e050c2e
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from partner-built/zoom-plugin/LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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AutoGineer is not affiliated with or endorsed by Zoom or Anthropic.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download scribe.zip