# percept-speaker-id

> percept-speaker-id — jarvis563-percept-speaker-id. Use this tool when you need to identify and manage individual speakers in multi-person conversations, solving problems like speaker tracking and dialogue attribution. It takes audio inputs and outputs identified speaker labels, enabling accurate conversation analysis and transcription. Ideal for applications like meeting transcription, podcast analysis, and customer service call tracking.

Canonical page: https://skillsregistry.net/skills/jarvis563-percept-speaker-id  
JSON: https://api.skillsregistry.net/v1/skills/jarvis563-percept-speaker-id

## Description

Speaker identification and management for multi-person conversations.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-05-18

## 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/jarvis563-percept-speaker-id)

## 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": "jarvis563-percept-speaker-id"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jarvis563-percept-speaker-id` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jarvis563-percept-speaker-id/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