# music-attribution-scaffold

> music-attribution-scaffold — petteriteikari-music-attribution-scaffold. Use this tool when you need to research and analyze multi-source music attribution with transparent confidence scoring. It solves problems related to governing generative music, attribution limits, and creator income by providing a scaffold for investigation. The tool accepts research data as input and outputs confidence scores, making it ideal for use cases involving music attribution and academic research.

Canonical page: https://skillsregistry.net/skills/petteriteikari-music-attribution-scaffold  
JSON: https://api.skillsregistry.net/v1/skills/petteriteikari-music-attribution-scaffold

## Description

Research scaffold for multi-source music attribution with transparent confidence scoring. Companion code to Teikari, Petteri. 2026. “Governing Generative Music: Attribution Limits, Platform Incentives, and the Future of Creator Income.” SSRN Scholarly Paper No. 6109087. SSRN, https://dx.doi.org/10.2139/ssrn.6109087

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/petteriTeikari/music-attribution-scaffold)

## 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": "petteriteikari-music-attribution-scaffold"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/petteriteikari-music-attribution-scaffold` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/petteriteikari-music-attribution-scaffold/pull`

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