# create2-vanity

> create2-vanity — nirholas-create2-vanity. Use this tool when you need to model deterministic EVM CREATE2 addresses and estimate salt search difficulty, solving problems related to Ethereum smart contract deployment and address prediction. It takes input parameters such as contract code and salt values, and outputs predicted addresses and difficulty metrics. Ideal for use cases involving Ethereum development, smart contract optimization, and address generation.

Canonical page: https://skillsregistry.net/skills/nirholas-create2-vanity  
JSON: https://api.skillsregistry.net/v1/skills/nirholas-create2-vanity

## Description

Model deterministic EVM CREATE2 addresses and salt search difficulty.

## Trust

- **Trust score (0–1):** 0.51
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/nirholas/create2-vanity)

## 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": "nirholas-create2-vanity"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nirholas-create2-vanity` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nirholas-create2-vanity/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