# Reprise

> Use this tool when you need to restore and analyze flat AI designs, as Reprise un-flattens them into editable layers with precise reproduction and fidelity scoring. It solves problems of design reproduction, element detection, and diagnosis, providing a valuable interface for agents to work with complex AI designs. Reprise is ideal for use cases where bit-perfect design reconstruction and analysis are crucial, accepting flat designs as input and outputting layered designs with fidelity scores.

Canonical page: https://skillsregistry.net/skills/tepesama-reprise  
JSON: https://api.skillsregistry.net/v1/skills/tepesama-reprise

## Description

Un-flattens flat AI designs into editable layers with bit-perfect reproduction and fidelity scoring, enabling agents to reproduce, detect elements, and diagnose designs via MCP.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/da0vdz13yr)
- **Repository:** <https://github.com/tepesama/reprise>

## 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": "tepesama-reprise"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/tepesama-reprise` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/tepesama-reprise/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