Scribe
AnthropicOfficialCreated by ZoomDistributed by Anthropic
- Skill
- Tool integration
- Automation and integrations
- MIT
- No issues found
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
Download the skill as a ZIP:
https://autogineer.com/agent-skills/anthropics/scribe/downloadUnzip 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:
https://developers.zoom.us/api-hub/ai-services/methods/endpoints.json
Quickstart sample: https://github.com/zoom/scribe-quickstart/
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 MBand2 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
32-34son the backendsome ~59.2 MB browser requests still surfaced as frontend
504while backend logs later showed200
Treat frontend
504plus backend200as 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
scribedoes 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 secondsacceptable range:
5-10 secondsin-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
Stored Zoom recordings -> ../rest-api/SKILL.md +
scribeWebhook 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
- ATTRIBUTION.mdAdded by AutoGineer968 B
- LICENSELicence file added by AutoGineer1.1 KiB
- RUNBOOK.md4.2 KiB
- SKILL.md5.8 KiB
- concepts/auth-and-processing-modes.md3.2 KiB
- examples/batch-webhook-pipeline.md1.6 KiB
- examples/fast-mode-node.md1.8 KiB
- references/api-reference.md2.6 KiB
- references/environment-variables.md1.5 KiB
- references/samples-validation.md2.0 KiB
- references/versioning-and-drift.md2.0 KiB
- scenarios/high-level-scenarios.md3.1 KiB
- troubleshooting/common-drift-and-breaks.md4.6 KiB
RUNBOOK.md
Scribe 5-Minute Preflight Runbook
Use this before deep debugging.
1) Confirm the Right Product
File-based or storage-based transcription -> stay on
scribe.Live meeting media stream or botless live transcription -> use
rtmsinstead.Meeting bot that joins and records before transcription -> chain Meeting SDK Linux first.
2) Confirm Credentials
Build-platform issuer credential pair available.
JWT generation uses
HS256with one-hour-or-less expiry.Secret stays server-side.
Reject placeholder values such as
${ZOOM_API_KEY}and${ZOOM_API_SECRET}. They can make a naive health check look configured while every real call still fails.
3) Confirm Mode Selection
Fast mode for one short file and immediate JSON response.
Batch mode for many files, long recordings, or archive-style processing.
Browser microphone pseudo-streaming for short repeated chunks uploaded through the async fast-mode wrapper.
Fast mode current limits from the API spec:
maximum file size:
100 MBmaximum duration:
2 hours
If fast mode is exposed through a hosted browser UI, prefer an async wrapper:
browser uploads once
backend returns
202with a request IDfrontend polls for completion This avoids losing successful transcriptions to edge/client timeout races.
Observed hosted timing from the deployed sample:
~17.2 MB MP4 completed in ~26s
~38.6 MB MP4 completed in ~26-37s
~59.2 MB MP4 completed in ~32-34s on the backend
some ~59.2 MB requests still surfaced as frontend
504even though the backend later completed with200Treat these as deployment observations, not hard API guarantees.
Recommended starting browser mic cadence:
chunk size:
5 secondsacceptable range:
5-10 secondskeep only
2-3chunks in flight at once This gives incremental transcript updates without trying to hold a single long browser request open.
For browser mic capture, rotate the recorder per chunk so each uploaded blob is a standalone file. Do not assume
MediaRecorder.start(timeslice)later chunks will always be independently transcribable.Do not treat this as the default production solution for live transcription. Prefer
rtmswhen the user actually needs a live-audio product instead of a browser demo.
4) Confirm Storage / Webhook Inputs
Fast mode file URL or upload path resolves.
Batch input/output URIs are valid.
AWS or pre-signed access is set correctly for S3 mode.
Webhook URL is public HTTPS if you expect notifications.
5) Confirm Post-Processing Contract
Decide whether downstream code expects
text_display, segments, or word-level timings.Decide whether channel separation or diarization is required before shipping.
6) Quick Probes
JWT generation works locally.
POST /aiservices/scribe/transcribesucceeds with a known small file.For browser-uploaded files, backend forwarding should use
multipart/form-datato Zoom, not a JSONdata:URI wrapper.Batch submit returns
201withjob_id.Webhook signature verification works with the configured secret.
7) Fast Decision Tree
401/auth failure -> wrong credential pair or expired JWT.Fast mode returns schema error -> wrong request body or config fields.
Fast mode returns
413 Request Entity Too Largebefore the app logs anything -> reverse proxy limit, not Scribe.Frontend returns
504but backend logs later show200-> browser/edge timeout race; poll by request ID instead of assuming failure.Browser mic feature needs true continuous low-latency media instead of chunked uploads -> switch to
rtms, notscribe.Browser mic chunk 1 works but chunk 2 onward is empty -> recorder/container boundary issue; restart the recorder for each chunk.
Batch jobs queue but never complete -> storage auth / URI / webhook issues.
Missing transcripts for some files -> inspect
/jobs/{jobId}/filesbefore re-submitting whole batch.
8) Source Checkpoints
Official docs
Raw docs in repo tooling output
tools/zoom-crawler/raw-docs/developers.zoom.us/docs/ai-services/
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
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
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)
- Synced
AutoGineer is not affiliated with or endorsed by Zoom or Anthropic.
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