# ai.avasis/quant-research

> ai.avasis/quant-research — ai-avasis-quant-research. Use this tool when you need to analyze and optimize cryptocurrency trading strategies through backtesting, solving problems of strategy evaluation and risk assessment. It provides statistical insights on trading performance, taking trial count into account to ensure accurate results. Ideal for use in contexts where data-driven decision making is crucial, such as portfolio management and risk analysis.

Canonical page: https://skillsregistry.net/skills/ai-avasis-quant-research  
JSON: https://api.skillsregistry.net/v1/skills/ai-avasis-quant-research

## Description

Crypto backtest statistics: the server owns the trial count, so it cannot be understated.

## Trust

- **Trust score (0–1):** 0.84
- **Verification tier:** verified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 0.2.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Updated:** 2026-09-01

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.avasis%2Fquant-research)
- **Repository:** <https://github.com/abhayjnayakk/quant-integrity>

## Use it

MCP endpoint published by the skill: `https://quant-mcp.avasis.ai/mcp`

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": "ai-avasis-quant-research"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-avasis-quant-research` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-avasis-quant-research/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