# chat.avva/catalog

> chat.avva/catalog — chat-avva-catalog. Use this tool when you need to find expert opinions and connect with proven decision-making models based on real past judgments. It solves problems by providing access to informed decisions and expert insights, helping with complex choices and uncertain situations. The tool takes search queries as input and outputs relevant expert models and their associated judgments.

Canonical page: https://skillsregistry.net/skills/chat-avva-catalog  
JSON: https://api.skillsregistry.net/v1/skills/chat-avva-catalog

## Description

Search Avva for an expert, then connect their model - judgment from real past decisions.

## Trust

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

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Updated:** 2026-09-04

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/chat.avva%2Fcatalog)

## Use it

MCP endpoint published by the skill: `https://avva.chat/mcp-catalog`

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": "chat-avva-catalog"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/chat-avva-catalog` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/chat-avva-catalog/pull`

---
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