# codexCLI

> Use this tool when you need to quickly access and manage frequently used data from the command line, solving problems of information overload and disorganization. It provides a simple interface with dot notation paths and shell completions, and integrates with AI agents via MCP server. Ideal for use cases where rapid reference and data retrieval are crucial, such as development, research, or data-intensive tasks.

Canonical page: https://skillsregistry.net/skills/seabeardev-codexcli  
JSON: https://api.skillsregistry.net/v1/skills/seabeardev-codexcli

## Description

A command-line information store for quick reference of frequently used data, with dot notation paths, shell completions, and MCP server for AI agent   integration.

## 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:** 2026-05-09

## Source

- **Source listing:** [GitHub](https://github.com/seabearDEV/codexCLI)

## 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": "seabeardev-codexcli"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/seabeardev-codexcli` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/seabeardev-codexcli/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