# varrd

> Use this tool when you need to test and validate trading ideas on various financial instruments, including stocks, futures, and crypto. Varrd solves problems related to trading strategy development and optimization through event studies, backtesting, and statistical validation. It provides a comprehensive interface with 8 tools, accessible via MCP server, and can be easily installed using pip install varrd.

Canonical page: https://skillsregistry.net/skills/augiemazza-varrd  
JSON: https://api.skillsregistry.net/v1/skills/augiemazza-varrd

## Description

AI-powered trading research platform. Test any idea on stocks, futures, and crypto with event studies, backtesting, and statistical validation. MCP server with 8 tools. pip install varrd.

## Trust

- **Trust score (0–1):** 0.93
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** finance
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/augiemazza/varrd)

## 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": "augiemazza-varrd"
    }
  }
}
```

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