# random-agent

> Use this tool when you need to automate complex task management and orchestrate multiple autonomous agents. It solves problems of task decomposition, parallel processing, and review by enabling multi-worker autonomy and generating follow-up tasks. The random-agent tool takes in complex tasks as input and outputs optimized, parallelized workflows via the Model Context Protocol interface.

Canonical page: https://skillsregistry.net/skills/randomchips-random-agent  
JSON: https://api.skillsregistry.net/v1/skills/randomchips-random-agent

## Description

Enables multi-worker autonomous agent orchestration: decompose complex tasks, run parallel workers, auto-review, and generate follow-up tasks via the Model Context Protocol.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** productivity
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/eagxnknlhv)
- **Repository:** <https://github.com/randomchips/random_agent>

## 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": "randomchips-random-agent"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/randomchips-random-agent` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/randomchips-random-agent/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
