# Beneat

> Use this tool when you need to manage and mitigate risks for autonomous trading agents on the Solana blockchain, solving problems such as excessive losses and non-optimal position sizing. Beneat provides quantitative risk management infrastructure, enforcing limits and interventions through on-chain contracts, and offers analytics and optimization capabilities. It takes in trade data and agent behavior as inputs, and outputs optimized position sizes, loss limits, and enforcement measures.

Canonical page: https://skillsregistry.net/skills/beneat  
JSON: https://api.skillsregistry.net/v1/skills/beneat

## Description

Beneat provides quantitative risk management infrastructure for autonomous trading agents operating on the Solana blockchain. It enforces position sizing, loss limits, and behavioral interventions through on-chain vault contracts with automated lockout mechanisms. The system includes Kelly criterion optimization, trust scoring, agent archetype classification, and comprehensive trade analytics with causal inference to measure enforcement impact.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** finance
- **Updated:** 2026-05-16

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/beneat)
- **Repository:** <https://github.com/beneat-ai/beneat-agentic-trading-mcp/tree/HEAD/mcp-server>

## 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": "beneat"
    }
  }
}
```

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