# CouchLoop EQ

> Use this tool when you need to ensure reliable and consistent AI responses, as it monitors and governs LLM output for hallucination, inconsistency, and unsafe reasoning patterns, providing stateful session management and guided journeys with memorable interactions. It takes in AI responses as input and outputs governed, safe, and consistent output. Ideal for applications requiring high-fidelity AI interactions, such as conversational systems or virtual assistants.

Canonical page: https://skillsregistry.net/skills/couchloop-ceq  
JSON: https://api.skillsregistry.net/v1/skills/couchloop-ceq

## Description

CouchLoop EQ provides behavioral governance for LLMs. It monitors AI responses for hallucination, inconsistency, tone drift, and unsafe reasoning patterns, while also managing stateful sessions and guided journeys that remember where you left off.

## 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:** ai-ml
- **Updated:** 2026-05-10

## Source

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

## 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": "couchloop-ceq"
    }
  }
}
```

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