# venice-transcribe

> Use this tool when you need to convert spoken words into written text, solving problems like inaccessible audio content or manual transcription efforts. It takes audio files as input and outputs transcribed text, leveraging Venice AI's Whisper-based speech recognition for accurate results. Ideal for use cases like podcast transcription, interview analysis, or audio note-taking, where automated transcription can save time and increase productivity.

Canonical page: https://skillsregistry.net/skills/sabrinaaquino-venice-transcribe  
JSON: https://api.skillsregistry.net/v1/skills/sabrinaaquino-venice-transcribe

## Description

Transcribe audio to text using Venice AI's Whisper-based speech recognition.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** media
- **Updated:** 2026-05-16

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/sabrinaaquino-venice-transcribe)

## 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": "sabrinaaquino-venice-transcribe"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sabrinaaquino-venice-transcribe` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sabrinaaquino-venice-transcribe/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