Zoom RTMS Meeting Assistant

Headless capture service for Zoom meetings using Real-Time Media Streams (RTMS). Receives webhook events, connects to RTMS WebSockets, records all media, and runs AI analysis via OpenClaw.

Webhook Events Handled

This skill processes two Zoom webhook events:

meeting.rtms_started
— Zoom sends this when RTMS is activated for a meeting. Contains
```
server_urls
```
,
```
rtms_stream_id
```
, and
```
meeting_uuid
```
needed to connect to the RTMS WebSocket.
meeting.rtms_stopped
— Zoom sends this when RTMS ends (meeting ended or RTMS disabled). Triggers cleanup: closes WebSocket connections, generates screenshare PDF, sends summary notification.

Webhook Dependency

This skill needs a public webhook endpoint to receive these events from Zoom.

Preferred: Use the ngrok-unofficial-webhook-skill (

skills/ngrok-unofficial-webhook-skill

). It auto-discovers this skill via

webhookEvents

skill.json

, notifies the user, and offers to route events here.

Other webhook solutions (e.g. custom servers, cloud functions) will work but require additional integration to forward payloads to this service.

Prerequisites

cd skills/zoom-meeting-assistance-rtms-unofficial-community
npm install

Requires

ffmpeg

for post-meeting media conversion.

Environment Variables

Set these in the skill's

.env

file:

Required:

```
ZOOM_SECRET_TOKEN
```
— Zoom webhook secret token
```
ZOOM_CLIENT_ID
```
— Zoom app Client ID
```
ZOOM_CLIENT_SECRET
```
— Zoom app Client Secret

Optional:

```
PORT
```
— Server port (default:
```
3000
```
)
```
AI_PROCESSING_INTERVAL_MS
```
— AI analysis frequency in ms (default:
```
30000
```
)
```
AI_FUNCTION_STAGGER_MS
```
— Delay between AI calls in ms (default:
```
5000
```
)
```
AUDIO_DATA_OPT
```
—
```
1
```
= mixed stream,
```
2
```
= multi-stream (default:
```
2
```
)
```
OPENCLAW_NOTIFY_CHANNEL
```
— Notification channel (default:
```
whatsapp
```
)
```
OPENCLAW_NOTIFY_TARGET
```
— Phone number / target for notifications

Starting the Service

cd skills/zoom-meeting-assistance-rtms-unofficial-community
node index.js

This starts an Express server listening for Zoom webhook events on

PORT

⚠️ Important: Before forwarding webhooks to this service, always check if it's running:

# Check if service is listening on port 3000
lsof -i :3000

If nothing is returned, start the service first before forwarding any webhook events.

Typical flow:

Start the server as a background process
Zoom sends
```
meeting.rtms_started
```
webhook → service connects to RTMS WebSocket
Media streams in real-time: audio, video, transcript, screenshare, chat
AI processing runs periodically (dialog suggestions, sentiment, summary)
```
meeting.rtms_stopped
```
→ service closes connections, generates screenshare PDF

Recorded Data

All recordings are stored organized by date:

skills/zoom-meeting-assistance-rtms-unofficial-community/recordings/YYYY/MM/DD/{streamId}/

Each stream folder contains:

File	Content	Searchable
`metadata.json`	Meeting metadata (UUID, stream ID, operator, start time)	✅
`transcript.txt`	Plain text transcript with timestamps and speaker names	✅ Best for searching — grep-friendly, one line per utterance
`transcript.vtt`	VTT format transcript with timing cues	✅
`transcript.srt`	SRT format transcript	✅
`events.log`	Participant join/leave, active speaker changes (JSON lines)	✅
`chat.txt`	Chat messages with timestamps	✅
`ai_summary.md`	AI-generated meeting summary (markdown)	✅ Key document — read this first for meeting overview
`ai_dialog.json`	AI dialog suggestions	✅
`ai_sentiment.json`	Sentiment analysis per participant	✅
`mixedaudio.raw`	Mixed audio stream (raw PCM)	❌ Binary
`activespeakervideo.h264`	Active speaker video (raw H.264)	❌ Binary
`processed/screenshare.pdf`	Deduplicated screenshare frames as PDF	❌ Binary

All summaries are also copied to a central folder for easy access:

skills/zoom-meeting-assistance-rtms-unofficial-community/summaries/summary_YYYY-MM-DDTHH-MM-SS_{streamId}.md

Searching & Querying Past Meetings

To find and review past meeting data:

# List all recorded meetings by date
ls -R recordings/
List meetings for a specific date
ls recordings/2026/01/28/
Search across all transcripts for a keyword
grep -rl "keyword" recordings/////transcript.txt
Search for what a specific person said
grep "Chun Siong Tan" recordings/////transcript.txt
Read a meeting summary
cat recordings/YYYY/MM/DD/<streamId>/ai_summary.md
Search summaries for a topic
grep -rl "topic" recordings/////ai_summary.md
Check who attended a meeting
cat recordings/YYYY/MM/DD/<streamId>/events.log
Get sentiment for a meeting

cat recordings/YYYY/MM/DD/<streamId>/ai_sentiment.json

The

.txt

.md

.json

, and

.log

files are all text-based and searchable. Start with

ai_summary.md

for a quick overview, then drill into

transcript.txt

for specific quotes or details.

API Endpoints

# Toggle WhatsApp notifications on/off
curl -X POST http://localhost:3000/api/notify-toggle -H "Content-Type: application/json" -d '{"enabled": false}'
Check notification status

curl http://localhost:3000/api/notify-toggle

Post-Meeting Processing

When

meeting.rtms_stopped

fires, the service automatically:

Generates PDF from screenshare images
Converts
```
mixedaudio.raw
```
→
```
mixedaudio.wav
```

Converts

activespeakervideo.h264

→

activespeakervideo.mp4

Muxes mixed audio + active speaker video into
```
final_output.mp4
```

Manual conversion scripts are available but note that auto-conversion runs on meeting end, so manual re-runs are rarely needed.

Reading Meeting Data

After or during a meeting, read files from

recordings/YYYY/MM/DD/{streamId}/

# List recorded meetings by date
ls -R recordings/
Read transcript
cat recordings/YYYY/MM/DD/<streamId>/transcript.txt
Read AI summary
cat recordings/YYYY/MM/DD/<streamId>/ai_summary.md
Read sentiment analysis

cat recordings/YYYY/MM/DD/<streamId>/ai_sentiment.json

Prompt Customization

Want different summary styles or analysis? Customize the AI prompts to fit your needs!

Edit these files to change AI behavior:

File	Purpose	Example Customizations
`summary_prompt.md`	Meeting summary generation	Bullet points vs prose, focus areas, length
`query_prompt.md`	Query response formatting	Response style, detail level
`query_prompt_current_meeting.md`	Real-time meeting analysis	What to highlight during meetings
`query_prompt_dialog_suggestions.md`	Dialog suggestion style	Formal vs casual, suggestion count
`query_prompt_sentiment_analysis.md`	Sentiment scoring logic	Custom sentiment categories, thresholds

Tip: Back up the originals before editing, so you can revert if needed.

Zoom Meeting Assistance Rtms Unofficial Community

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Zoom RTMS Meeting Assistant

Webhook Events Handled

Webhook Dependency

Prerequisites

Environment Variables

Starting the Service

Recorded Data

Searching & Querying Past Meetings

List meetings for a specific date

Search across all transcripts for a keyword

Search for what a specific person said

Read a meeting summary

Search summaries for a topic

Check who attended a meeting

Get sentiment for a meeting

API Endpoints

Check notification status

Post-Meeting Processing

Reading Meeting Data

Read transcript

Read AI summary

Read sentiment analysis

Prompt Customization

Quick Start

Manual Installation

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