Agent skill

Deepgram Core Workflow B

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Implement real-time streaming transcription with Deepgram WebSocket.

MITAuto-check passedMedia & Creative

Install Deepgram Core Workflow B

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill deepgram-core-workflow-b -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace deepgram-core-workflow-b --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/deepgram-core-workflow-b .claude/skills/deepgram-core-workflow-b && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
deepgram-core-workflow-b
GitHub stars
2.8k
Token cost
~2.4k tokens
SKILL.md length
288 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Implement real-time streaming transcription with Deepgram WebSocket.

  • Works in 6 steps: Basic Live Transcription → Microphone Capture with Sox → Live Diarization → …
  • Building live transcription
  • SKILL.md covers Examples, Overview, Prerequisites and Instructions, plus 4 more sections
  • Calls apt and brew; needs DEEPGRAM_API_KEY

What it does

Deepgram Core Workflow B is an agent skill from jeremylongshore/tons-of-skills-marketplace. Implement real-time streaming transcription with Deepgram WebSocket. Use when building live transcription, voice interfaces, real-time captioning, or voice AI applications. Trigger: "deepgram streaming", "real-time transcription", "live transcription", "websocket transcription", "voice streaming", "deepgram live".

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/streaming-implementation.md`). Compatibility notes: Designed for Claude Code

It sits in Media & Creative, covering Transcription, Realtime and WebSockets and Speech recognition and synthesis. It works with Deepgram. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Building live transcription
  • Voice interfaces
  • Real-time captioning
  • Voice AI applications

Example prompts

  • “deepgram streaming”
  • “real-time transcription”
  • “live transcription”
  • “/deepgram-core-workflow-b”

Requirements

  • A credential in DEEPGRAM_API_KEY
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(npm:*), Bash(pip:*), Grep

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Basic Live Transcription
  2. Microphone Capture with Sox
  3. Live Diarization
  4. Auto-Reconnect with Backoff
  5. SSE Endpoint for Browser Clients
  6. KeepAlive for Long Sessions

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash(npm:*)
    • Bash(pip:*)
    • Grep

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • apt
    • brew

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • developers.deepgram.com
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • DEEPGRAM_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Deepgram Core Workflow B loads about 2.4k tokens when it runs, and up to ~3.4k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 288 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 288 words, ~2,429 tokens.

Download SKILL.mdSave it as .claude/skills/deepgram-core-workflow-b/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
deepgram-core-workflow-b
description
Implement real-time streaming transcription with Deepgram WebSocket. Use when building live transcription, voice interfaces, real-time captioning, or voice AI applications. Trigger: "deepgram streaming", "real-time transcription", "live transcription", "websocket transcription", "voice streaming", "deepgram live".
allowed-tools
Read, Write, Edit, Bash(npm:*), Bash(pip:*), Grep
compatibility
Designed for Claude Code
version
1.13.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, deepgram, voice-ai, transcription, streaming, websocket

Deepgram Core Workflow B: Live Streaming Transcription

Examples

Open a development streaming session with a non-sensitive test utterance, verify connection/authentication, partial/final transcript state, timeout, and close behavior. Enforce the session's data/consent policy and log a correlation ID plus state transitions—not audio bytes, API keys, or full participant speech.

Overview

Real-time streaming transcription using Deepgram's WebSocket API. The SDK manages the WebSocket connection via listen.live(). Covers microphone capture, interim/final result handling, speaker diarization, UtteranceEnd detection, auto-reconnect, and building an SSE endpoint for browser clients.

Prerequisites

  • @deepgram/sdk installed, DEEPGRAM_API_KEY configured
  • Audio source: microphone (via Sox/rec), file stream, or WebSocket audio from browser
  • For mic capture: sox installed (apt install sox / brew install sox)

Instructions

Step 1: Basic Live Transcription
typescript
import { createClient, LiveTranscriptionEvents } from '@deepgram/sdk';

const deepgram = createClient(process.env.DEEPGRAM_API_KEY!);

const connection = deepgram.listen.live({
  model: 'nova-3',
  language: 'en',
  smart_format: true,
  punctuate: true,
  interim_results: true,      // Show in-progress results
  utterance_end_ms: 1000,     // Silence threshold for utterance end
  vad_events: true,           // Voice activity detection events
  encoding: 'linear16',       // 16-bit PCM
  sample_rate: 16000,         // 16 kHz
  channels: 1,                // Mono
});

// Connection lifecycle events
connection.on(LiveTranscriptionEvents.Open, () => {
  console.log('WebSocket connected to Deepgram');
});

connection.on(LiveTranscriptionEvents.Close, () => {
  console.log('WebSocket closed');
});

connection.on(LiveTranscriptionEvents.Error, (err) => {
  console.error('Deepgram error:', err);
});

// Transcript events
connection.on(LiveTranscriptionEvents.Transcript, (data) => {
  const transcript = data.channel.alternatives[0]?.transcript;
  if (!transcript) return;

  if (data.is_final) {
    console.log(`[FINAL] ${transcript}`);
  } else {
    process.stdout.write(`\r[interim] ${transcript}`);
  }
});

// UtteranceEnd — fires when speaker pauses
connection.on(LiveTranscriptionEvents.UtteranceEnd, () => {
  console.log('\n--- utterance end ---');
});
Step 2: Microphone Capture with Sox
typescript
import { spawn } from 'child_process';

function startMicrophone(connection: any) {
  // Sox captures from default mic: 16kHz, 16-bit signed LE, mono
  const mic = spawn('rec', [
    '-q',              // Quiet (no progress)
    '-r', '16000',     // Sample rate
    '-e', 'signed',    // Encoding
    '-b', '16',        // Bit depth
    '-c', '1',         // Mono
    '-t', 'raw',       // Raw PCM output
    '-',               // Output to stdout
  ]);

  mic.stdout.on('data', (chunk: Buffer) => {
    if (connection.getReadyState() === 1) {  // WebSocket.OPEN
      connection.send(chunk);
    }
  });

  mic.on('error', (err) => {
    console.error('Microphone error:', err.message);
    console.log('Install sox: apt install sox / brew install sox');
  });

  return mic;
}

// Usage
const mic = startMicrophone(connection);

// Graceful shutdown
process.on('SIGINT', () => {
  mic.kill();
  connection.finish();  // Sends CloseStream message, waits for final results
  setTimeout(() => process.exit(0), 2000);
});
Step 3: Live Diarization
typescript
const connection = deepgram.listen.live({
  model: 'nova-3',
  smart_format: true,
  diarize: true,
  interim_results: false,  // Only final for cleaner diarization
  utterance_end_ms: 1500,
  encoding: 'linear16',
  sample_rate: 16000,
  channels: 1,
});

connection.on(LiveTranscriptionEvents.Transcript, (data) => {
  if (!data.is_final) return;

  const words = data.channel.alternatives[0]?.words ?? [];
  if (words.length === 0) return;

  // Group consecutive words by speaker
  let currentSpeaker = words[0].speaker;
  let segment = '';

  for (const word of words) {
    if (word.speaker !== currentSpeaker) {
      console.log(`Speaker ${currentSpeaker}: ${segment.trim()}`);
      currentSpeaker = word.speaker;
      segment = '';
    }
    segment += ` ${word.punctuated_word ?? word.word}`;
  }
  console.log(`Speaker ${currentSpeaker}: ${segment.trim()}`);
});
Step 4: Auto-Reconnect with Backoff
typescript
class ReconnectingLiveTranscription {
  private client: ReturnType<typeof createClient>;
  private connection: any = null;
  private reconnectAttempts = 0;
  private maxReconnectAttempts = 10;
  private baseDelay = 1000;

  constructor(apiKey: string, private options: Record<string, any>) {
    this.client = createClient(apiKey);
  }

  connect() {
    this.connection = this.client.listen.live(this.options);

    this.connection.on(LiveTranscriptionEvents.Open, () => {
      console.log('Connected');
      this.reconnectAttempts = 0;  // Reset on success
    });

    this.connection.on(LiveTranscriptionEvents.Close, () => {
      this.scheduleReconnect();
    });

    this.connection.on(LiveTranscriptionEvents.Error, (err: Error) => {
      console.error('Connection error:', err.message);
      this.scheduleReconnect();
    });

    return this.connection;
  }

  private scheduleReconnect() {
    if (this.reconnectAttempts >= this.maxReconnectAttempts) {
      console.error('Max reconnection attempts reached');
      return;
    }
    const delay = this.baseDelay * Math.pow(2, this.reconnectAttempts)
      + Math.random() * 1000;  // Jitter
    this.reconnectAttempts++;
    console.log(`Reconnecting in ${Math.round(delay)}ms (attempt ${this.reconnectAttempts})`);
    setTimeout(() => this.connect(), delay);
  }

  send(chunk: Buffer) {
    if (this.connection?.getReadyState() === 1) {
      this.connection.send(chunk);
    }
  }

  close() {
    this.maxReconnectAttempts = 0;  // Prevent reconnect
    this.connection?.finish();
  }
}
Step 5: SSE Endpoint for Browser Clients
typescript
import express from 'express';
import { createClient, LiveTranscriptionEvents } from '@deepgram/sdk';

const app = express();

app.get('/api/transcribe/stream', (req, res) => {
  res.setHeader('Content-Type', 'text/event-stream');
  res.setHeader('Cache-Control', 'no-cache');
  res.setHeader('Connection', 'keep-alive');

  const deepgram = createClient(process.env.DEEPGRAM_API_KEY!);
  const connection = deepgram.listen.live({
    model: 'nova-3',
    smart_format: true,
    interim_results: true,
    encoding: 'linear16',
    sample_rate: 16000,
    channels: 1,
  });

  connection.on(LiveTranscriptionEvents.Transcript, (data) => {
    const transcript = data.channel.alternatives[0]?.transcript;
    if (transcript) {
      res.write(`data: ${JSON.stringify({
        transcript,
        is_final: data.is_final,
        speech_final: data.speech_final,
      })}\n\n`);
    }
  });

  // Client provides audio via a paired WebSocket (see browser setup)
  req.on('close', () => {
    connection.finish();
  });
});
Step 6: KeepAlive for Long Sessions
typescript
// Deepgram closes idle connections after ~10s of no audio.
// Send KeepAlive messages during silence periods.
connection.on(LiveTranscriptionEvents.Open, () => {
  const keepAliveInterval = setInterval(() => {
    if (connection.getReadyState() === 1) {
      connection.keepAlive();
    }
  }, 8000);  // Every 8 seconds

  connection.on(LiveTranscriptionEvents.Close, () => {
    clearInterval(keepAliveInterval);
  });
});

Output

  • Live WebSocket transcription with interim/final results
  • Microphone capture pipeline (Sox -> Deepgram)
  • Speaker diarization in streaming mode
  • Auto-reconnect with exponential backoff and jitter
  • SSE endpoint for browser integration
  • KeepAlive handling for long sessions

Error Handling

IssueCauseSolution
WebSocket closes immediatelyInvalid API key or bad encoding paramsCheck key, verify encoding/sample_rate match audio
No transcripts receivedAudio not being sent or wrong formatVerify connection.send(chunk) is called with raw PCM
High latencyNetwork congestionUse interim_results: true for perceived speed
rec command not foundSox not installedapt install sox or brew install sox
Connection drops after 10sNo audio + no KeepAliveSend connection.keepAlive() every 8s
Garbled outputSample rate mismatchEnsure audio sample rate matches sample_rate option

Resources

Next Steps

Proceed to deepgram-data-handling for transcript processing and storage patterns.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/deepgram-core-workflow-b of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/streaming-implementation.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Deepgram Core Workflow B next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Deepgram Core Workflow B compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Deepgram Core Workflow B this skilljeremylongshore/tons-of-skills-marketplace2.8k—~2.4kAutomated safety check: PassMIT
Deepgram JS Audio Intelligencedeepgram/deepgram-js-sdk276—~1.5kAutomated safety check: PassMIT
Deepgram Python Speech-to-Textdeepgram/deepgram-python-sdk469—~2.9kAutomated safety check: PassMIT
Deepgram JS Speech To Textdeepgram/deepgram-js-sdk276—~1.8kAutomated safety check: PassMIT
Deepgram Python Text-to-Speechdeepgram/deepgram-python-sdk469—~1.8kAutomated safety check: PassMIT
Speech Engineelevenlabs/skills482—~2.5kAutomated safety check: WarnMIT

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Works with

Questions about Deepgram Core Workflow B

What does Deepgram Core Workflow B do?

Implement real-time streaming transcription with Deepgram WebSocket. Deepgram Core Workflow B is an agent skill from jeremylongshore/tons-of-skills-marketplace. Implement real-time streaming transcription with Deepgram WebSocket.

When should I use Deepgram Core Workflow B?

Deepgram Core Workflow B fits situations like: building live transcription; voice interfaces; real-time captioning; voice AI applications.

How do I install Deepgram Core Workflow B in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill deepgram-core-workflow-b -a claude-code`. Or copy the skill folder (skills/.curated/deepgram-core-workflow-b in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/deepgram-core-workflow-b in your project. Claude Code loads it when a task matches its description.

How do I install Deepgram Core Workflow B in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill deepgram-core-workflow-b -a codex`. Or copy the skill folder (skills/.curated/deepgram-core-workflow-b in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/deepgram-core-workflow-b in your project. Codex loads it when a task matches its description.

Can I use Deepgram Core Workflow B in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill deepgram-core-workflow-b -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deepgram-core-workflow-b, .gemini/skills/deepgram-core-workflow-b, .github/skills/deepgram-core-workflow-b and .opencode/skills/deepgram-core-workflow-b in your project.

What does Deepgram Core Workflow B need to run?

Going by SKILL.md and its folder, Deepgram Core Workflow B needs the command-line tools its instructions call (apt and brew) and credentials named DEEPGRAM_API_KEY. Our summary lists: A credential in DEEPGRAM_API_KEY. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(npm:*), Bash(pip:*), Grep. Compatibility (from SKILL.md): Designed for Claude Code.

Does Deepgram Core Workflow B access the network?

SKILL.md names 2 domains. As links in the text: developers.deepgram.com and github.com. This is read from the text; nothing was executed.

Is Deepgram Core Workflow B safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Deepgram Core Workflow B use?

Deepgram Core Workflow B is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Deepgram Core Workflow B use?

About 2.4k tokens (SKILL.md is roughly 9.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 966 tokens, read only when the agent opens those files.

What are the alternatives to Deepgram Core Workflow B?

Skills that share tags, products or a category with Deepgram Core Workflow B: Deepgram JS Audio Intelligence (deepgram/deepgram-js-sdk, 276 stars), Deepgram Python Speech-to-Text (deepgram/deepgram-python-sdk, 469 stars), Deepgram JS Speech To Text (deepgram/deepgram-js-sdk, 276 stars) and Deepgram Python Text-to-Speech (deepgram/deepgram-python-sdk, 469 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deepgram Core Workflow B?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.