# StratProof

> Use this tool when you need to validate and backtest trading strategies with real-world accuracy, solving problems of over-optimization and unrealistic expectations. StratProof takes in strategy descriptions and outputs a verdict with diagnosis, using inputs from Binance spot data and aggregated research output. Use it to confirm the effectiveness of your trading strategies and get live performance updates through its adaptive engine.

Canonical page: https://skillsregistry.net/skills/pmort2222-stratproof  
JSON: https://api.skillsregistry.net/v1/skills/pmort2222-stratproof

## Description

StratProof runs honest backtests: real fees, real slippage, walk-forward validation. Six public tools, no OAuth. Call prove_strategy to test any strategy description ("Buy ETH when RSI(7) below 25, exit on 1.5% gain") and get a CONFIRMED / MIXED / DEBUNKED verdict with diagnosis. Call get_live_proof to see how our adaptive engine is actually performing in paper trading right now. Data sources: Binance spot (3 years), aggregated research output from 7,000+ tested candidates.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** finance
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/pmort2222/stratproof)

## 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": "pmort2222-stratproof"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/pmort2222-stratproof` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/pmort2222-stratproof/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