# multi-agent-collab

> Use this tool when you need to facilitate cooperation among multiple AI agents, enabling them to work together seamlessly to solve complex problems. It provides a universal methodology for collaboration, allowing agents to share inputs and produce coordinated outputs. Ideal for use cases requiring collective decision-making, task allocation, and synchronized action among multiple agents.

Canonical page: https://skillsregistry.net/skills/vdc-k-multi-agent-collab  
JSON: https://api.skillsregistry.net/v1/skills/vdc-k-multi-agent-collab

## Description

Universal multi-agent collaboration methodology for Claude Code.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-05-15

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/vdc-k-multi-agent-collab)

## 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": "vdc-k-multi-agent-collab"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vdc-k-multi-agent-collab` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vdc-k-multi-agent-collab/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