Does this skill support interim results?

Yes, the skill includes specific configurations for interim results, allowing developers to show text updates in real-time as speech is processed.

What is the primary use for this skill?

It is designed to help developers implement live, low-latency audio transcription using Deepgram's WebSocket API within their software projects.

Which programming languages are covered?

The skill provides comprehensive implementation examples for TypeScript (both Browser and Node.js environments) and Python.

How does it handle connection interruptions?

It includes a resilient auto-reconnect pattern that uses exponential backoff to ensure the transcription stream remains stable during network drops.

Can I use this for browser-based microphone input?

Yes, it includes specialized logic for integrating with the browser's MediaDevices and AudioContext APIs to capture and stream microphone data.

Deepgram Real-time Streaming

Name: Deepgram Real-time Streaming
Author: jeremylongshore

byjeremylongshore

•

982

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API Development

Implement real-time audio transcription and live voice processing using Deepgram's high-performance WebSocket API.

This skill provides a standardized framework for integrating Deepgram’s low-latency streaming transcription into your applications. It enables Claude to assist with complex WebSocket lifecycle management, real-time event handling, and audio chunking strategies. Whether you are building live captioning tools, voice-controlled interfaces, or real-time meeting analytics, this skill provides the implementation patterns needed for reliable, production-grade streaming audio processing.

Key Features

01Cross-platform support for Node.js and Python implementations

02Resilient auto-reconnect patterns for stable connections

03WebSocket client initialization for low-latency streaming

04982 GitHub stars

05Browser-based microphone integration patterns

06Configuration for interim results and endpointing logic

Use Cases

01Building live closed captioning systems for video streams

02Creating voice-to-text interfaces for real-time AI assistants

03Developing real-time meeting transcription and sentiment analysis tools

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills deepgram-core-workflow-b

For use in Claude.ai and ChatGPT

Download Skill

Key Features

01Cross-platform support for Node.js and Python implementations

02Resilient auto-reconnect patterns for stable connections

03WebSocket client initialization for low-latency streaming

04982 GitHub stars

05Browser-based microphone integration patterns

06Configuration for interim results and endpointing logic

Use Cases

01Building live closed captioning systems for video streams

02Creating voice-to-text interfaces for real-time AI assistants

03Developing real-time meeting transcription and sentiment analysis tools

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills deepgram-core-workflow-b

For use in Claude.ai and ChatGPT

Download Skill