# OMC

> OMC — randomcoder-lab-omc. Use this tool when you need to efficiently develop and optimize complex algorithms and machine learning models, particularly those involving harmonic-substrate programming and substrate-native ML frameworks. The OMC tool solves problems related to compiler optimization, algorithmic efficiency, and AI model performance, accepting code inputs and producing optimized outputs through its dual-band LLVM JIT and self-healing compiler. It is ideal for use cases requiring high-performance computing and advanced ML capabilities, such as natural language processing and compiler design.

Canonical page: https://skillsregistry.net/skills/randomcoder-lab-omc  
JSON: https://api.skillsregistry.net/v1/skills/randomcoder-lab-omc

## Description

Harmonic-substrate programming language: first-class φ, dual-band LLVM JIT, self-healing compiler, O(log_φπfib N) algorithms, and a substrate-native ML framework whose substrate-aware transformer attention wins -8.94% val on TinyShakespeare.

## Trust

- **Trust score (0–1):** 0.62
- **Verification tier:** scanned
- **Last scanned:** 2026-08-23

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/RandomCoder-lab/OMC)

## 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": "randomcoder-lab-omc"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/randomcoder-lab-omc` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/randomcoder-lab-omc/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