# analysis-gym

> analysis-gym — defog-ai-analysis-gym. Use this tool when you need to evaluate the performance of AI agents in predicting equity earnings, compare different agent configurations, or optimize forecasting models. It takes in predictions and actual earnings data as input and outputs a scorecard of each agent's performance. This tool is ideal for use cases involving financial forecasting, model optimization, and AI agent benchmarking.

Canonical page: https://skillsregistry.net/skills/defog-ai-analysis-gym  
JSON: https://api.skillsregistry.net/v1/skills/defog-ai-analysis-gym

## Description

Records and scores prospective equity earnings predictions made by AI agents, allowing comparison of different agent configurations.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/zs9b4qvj3d)
- **Repository:** <https://github.com/defog-ai/analysis-gym>

## 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": "defog-ai-analysis-gym"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/defog-ai-analysis-gym` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/defog-ai-analysis-gym/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