# loomcycle

> loomcycle — denn-gubsky-loomcycle. Use this tool when you need to create a runtime environment for agentic systems, enabling agents to interact, learn, and adapt with support for multiple LLM providers and configurable sandbox or development settings. It solves problems related to agent development, testing, and deployment, providing a flexible and manageable substrate. Ideal for use cases involving autonomous agents, AI development, and machine learning model integration.

Canonical page: https://skillsregistry.net/skills/denn-gubsky-loomcycle  
JSON: https://api.skillsregistry.net/v1/skills/denn-gubsky-loomcycle

## Description

The runtime substrate for agentic systems — one Go binary, six LLM providers, MCP-native, configurable as a managed sandbox or full agentic dev environment. Where agents live, talk, and learn.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/denn-gubsky/loomcycle)

## 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": "denn-gubsky-loomcycle"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/denn-gubsky-loomcycle` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/denn-gubsky-loomcycle/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