# deepgram

> deepgram — nerkn-deepgram. Use this tool when you need to transcribe spoken audio into text, solving problems such as inaccurate or inefficient manual transcription, and enabling use cases like podcast subtitles, meeting notes, and voice command analysis. Deepgram takes audio files or streams as input and outputs text transcripts, providing a simple command-line interface for integration into various workflows. It is ideal for applications requiring fast and accurate speech recognition, such as media analysis, customer service, or language learning platforms.

Canonical page: https://skillsregistry.net/skills/nerkn-deepgram  
JSON: https://api.skillsregistry.net/v1/skills/nerkn-deepgram

## Description

— command-line interface for Deepgram speech-to-text.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-23

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-09-13

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/nerkn-deepgram)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "nerkn-deepgram"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nerkn-deepgram` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nerkn-deepgram/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt