# genpark-multimodal-audio-emotion-valence-detector-skill

> genpark-multimodal-audio-emotion-valence-detector-skill — alpha-park-genpark-multimodal-audio-emotion-valence-detector-skill. Use this tool when you need to analyze audio inputs for emotional cues, such as detecting frustration or valence in customer interactions. It solves problems related to sentiment analysis and emotional intelligence in voice-based applications, providing outputs that indicate the emotional state of the speaker. Ideal for use cases like customer service, voice assistants, or market research, where understanding emotional tone is crucial.

Canonical page: https://skillsregistry.net/skills/alpha-park-genpark-multimodal-audio-emotion-valence-detector-skill  
JSON: https://api.skillsregistry.net/v1/skills/alpha-park-genpark-multimodal-audio-emotion-valence-detector-skill

## Description

Acoustic vocal emotion, prosodic valence, and customer frustration analyzer

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Alpha-Park/genpark-multimodal-audio-emotion-valence-detector-skill)

## 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": "alpha-park-genpark-multimodal-audio-emotion-valence-detector-skill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alpha-park-genpark-multimodal-audio-emotion-valence-detector-skill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alpha-park-genpark-multimodal-audio-emotion-valence-detector-skill/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