scribe

Original：🇺🇸 English

Translated

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.

8installs

Sourceanthropics/knowledge-work-plugins

Added on2026-04-10

NPX Install

npx skill4agent add anthropics/knowledge-work-plugins scribe

SKILL.md Content

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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.

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:
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

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 +
```
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.