# design.reprise/reprise

> Use this tool when you need to restructure and edit flat AI designs, as it enables the un-flattening of designs into editable layers and reproduces them with precision. This tool solves problems of design rigidity and facilitates seamless editing, allowing for bit-perfect reproduction from your agent. It takes flat AI designs as input and outputs editable, layered designs, ideal for use cases requiring design flexibility and precision.

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

## Description

Un-flatten any flat AI design into editable layers, reproduce it bit-perfect, from your agent.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 0.3.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-03

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/design.reprise%2Freprise)

## Use it

MCP endpoint published by the skill: `https://tepesama-reprise-mcp.hf.space/gradio_api/mcp/http`

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": "design-reprise-reprise"
    }
  }
}
```

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