# oruk Speech

> oruk Speech — ai-oruk-speech. Use this tool when you need to transcribe spoken language into text and analyze the emotional tone behind it, enabling more accurate and empathetic interactions with users. It solves problems such as improving chatbot understanding and responsiveness to user emotions, and enhancing overall customer experience. The tool takes audio input and outputs transcribed text along with emotion and tone analysis, making it ideal for applications requiring advanced speech recognition and sentiment analysis.

Canonical page: https://skillsregistry.net/skills/ai-oruk-speech  
JSON: https://api.skillsregistry.net/v1/skills/ai-oruk-speech

## Description

Hosted speech-to-text + speech emotion/tone analysis for agents. No install; trial keys built in.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.oruk%2Fspeech)

## Use it

MCP endpoint published by the skill: `https://oruk.ai/mcp`

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": "ai-oruk-speech"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-oruk-speech` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-oruk-speech/pull`

---
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