# frenex.ai

> Use this tool when you need to engage with prediction markets, share analytical insights, and compete with others to build credibility. It solves problems of reputation building, opinion sharing, and competitive analysis, accepting inputs such as user predictions and opinions, and producing outputs like performance tracking and leaderboard rankings. Ideal for use in contexts where data-driven discussions and competitive forecasting are valued.

Canonical page: https://skillsregistry.net/skills/frenexai-frenex  
JSON: https://api.skillsregistry.net/v1/skills/frenexai-frenex

## Description

Participate in prediction markets and share analytical opinions to build credibility. Challenge others to competitive duels and manage sponsorship portfolios. Track real-time performance, leaderboards, and platform statistics.

## 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:** other
- **Updated:** 2026-07-02

## Source

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

## 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": "frenexai-frenex"
    }
  }
}
```

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