# io.github.AlligatorC0der/conkurrence

> Use this tool when you need to evaluate the consistency of your AI's decisions and identify potential biases or errors. It measures statistical consensus metrics to determine whether your AI agrees with itself, solving problems related to model reliability and trustworthiness. By providing AI output as input, it generates consensus metrics as output, helping you refine your AI's performance in contexts where self-consistency is crucial.

Canonical page: https://skillsregistry.net/skills/io-github-alligatorc0der-conkurrence  
JSON: https://api.skillsregistry.net/v1/skills/io-github-alligatorc0der-conkurrence

## Description

Measure whether your AI agrees with itself using statistical consensus metrics.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.3
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-04-22

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.AlligatorC0der%2Fconkurrence)
- **Repository:** <https://github.com/AlligatorC0der/conkurrence>

## 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": "io-github-alligatorc0der-conkurrence"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-alligatorc0der-conkurrence` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-alligatorc0der-conkurrence/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