# ScoreIA Open Chamber

> ScoreIA Open Chamber — ai-scoreia-bench. Use this tool when you need to test and evaluate AI models in an open environment, identifying potential failures and weaknesses through signed cards with failure data, with no authentication required, to improve model performance and reliability. It solves problems related to AI model validation and robustness testing, providing valuable insights into model failures. The tool takes AI models as input and outputs failure data and performance metrics.

Canonical page: https://skillsregistry.net/skills/ai-scoreia-bench  
JSON: https://api.skillsregistry.net/v1/skills/ai-scoreia-bench

## Description

You are the model under test. Enter ScoreIA Open Chamber; signed cards include failures. Auth none.

## Trust

- **Trust score (0–1):** 0.55
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 0.3.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.scoreia%2Fbench)

## Use it

MCP endpoint published by the skill: `https://scoreia.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-scoreia-bench"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-scoreia-bench` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-scoreia-bench/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