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Cc Codex

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Dianel555
cc-codex

Delegates coding tasks to Codex CLI for prototyping, debugging, and code review. Use when: (1) Backend/logic implementation, (2) Algorithm design and optimization, (3) Bug analysis and debugging, (4) API/database code generation, (5) Code quality review and refactoring. Triggers: "implement algorithm", "debug", "analyze code", "backend task", "API implementation", "optimize performance", "refactor", "generate prototype", "code review". IMPORTANT: Default sandbox="read-only" (analysis/review/patch generation); use sandbox="workspace-write" only when codex must run tests/builds to verify. Always request unified diff patches only. Supports multi-turn sessions via SESSION_ID.

Overview

PublisherDianel555
RepositoryDSkills
Skill namecc-codex
Stars
65
Forks
8
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Dianel555 on GitHub. Read the source before you install it.

Installation

Install the Cc Codex AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Dianel555/DSkills/tree/main/skills/cc-codex
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Dianel555/DSkills.git /tmp/DSkills
mkdir -p .claude/skills
cp -r /tmp/DSkills/skills/cc-codex .claude/skills/cc-codex
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cc Codex in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cc Codex on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cc Codex is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Quick Start

bash
python scripts/codex_bridge.py --cd "/path/to/project" --PROMPT "Your task"

Output: JSON with success, SESSION_ID, agent_messages, stream_file (path to the raw JSONL stream persisted line-by-line), optional stderr (codex diagnostics; lines repeated verbatim except for their timestamp are collapsed to one line with an [xN] count), and optional error.

Headless exec runs with approvals disabled by Codex itself; bridge --yolo maps to Codex's --dangerously-bypass-approvals-and-sandbox. Stdin is detached, so an approval prompt could never be answered. On Windows the PROMPT is delivered via stdin (- positional) to bypass cmd.exe quoting/length limits.

Parameters

usage: codex_bridge.py [-h] [--PROMPT PROMPT] [--cd CD]
                       [--sandbox {read-only,workspace-write,danger-full-access}]
                       [--SESSION_ID SESSION_ID] [--skip-git-repo-check]
                       [--return-all-messages] [--image IMAGE] [--model MODEL]
                       [--yolo] [--profile PROFILE] [--stream-file STREAM_FILE]
                       [--idle-timeout IDLE_TIMEOUT] [--ignore-user-config]
                       [--dangerously-bypass-hook-trust]
                       {mcp,plugin} ...

Codex Bridge

options:
  --PROMPT PROMPT       Instruction for the task to send to codex.
  --cd CD               Set the workspace root for codex before executing the task.
  --sandbox {read-only,workspace-write,danger-full-access}
                        Sandbox policy for model-generated commands. Defaults to `read-only`.
  --SESSION_ID SESSION_ID
                        Resume the specified session of the codex.
  --skip-git-repo-check
                        Allow codex running outside a Git repository.
  --return-all-messages
                        Return all messages (reasoning, tool calls, etc.).
  --image IMAGE         Attach image files to the initial prompt.
  --model MODEL         Model for the session (only when user explicitly requests).
  --yolo                Bypass approvals/sandboxing (last resort).
  --profile PROFILE     Load `~/.codex/<name>.config.toml` profile (only when user requests).
  --stream-file STREAM_FILE
                        Persist raw JSONL stream path.
  --idle-timeout IDLE_TIMEOUT
                        Kill codex if no output for N seconds (default 600; 0 disables).
  --ignore-user-config  Do not load `$CODEX_HOME/config.toml` (auth still uses CODEX_HOME).
  --dangerously-bypass-hook-trust
                        Run Codex hooks without persisted hook trust. DANGEROUS.

subcommands:
  mcp                   Thin passthrough to `codex mcp` (list/get/add/remove/login/logout).
  plugin                Thin passthrough to `codex plugin` (add/list/remove/marketplace).

Multi-turn Sessions

Always capture SESSION_ID from the first response for follow-up:

bash
# Initial task
python scripts/codex_bridge.py --cd "/project" --PROMPT "Analyze auth in login.py"

# Continue with SESSION_ID
python scripts/codex_bridge.py --cd "/project" --SESSION_ID "uuid-from-response" --PROMPT "Write unit tests for that"

Config Inheritance

SourceInherited by default?
~/.codex/config.tomlYes (unless --ignore-user-config)
Profile (--profile)Only when explicitly passed
Project .codex/ (trusted)Yes, when Codex trusts the project
Hooks / MCP / plugins / skills / AGENTS.mdYes, via Codex runtime

Management Passthrough

bash
python scripts/codex_bridge.py mcp list
python scripts/codex_bridge.py plugin list

Common Patterns

Prototyping (read-only, request diffs):

bash
python scripts/codex_bridge.py --cd "/project" --PROMPT "Generate unified diff to add logging"

Verification (codex must run tests/builds — read-only blocks them):

bash
python scripts/codex_bridge.py --cd "/project" --sandbox workspace-write --PROMPT "Run pytest, fix the failure, output a unified diff patch"

Keep requesting patch text; audit afterwards with git status && git diff.

Debug with full trace:

bash
python scripts/codex_bridge.py --cd "/project" --PROMPT "Debug this error" --return-all-messages

Headless hooks (vetted automation only):

bash
python scripts/codex_bridge.py --cd "/project" --PROMPT "..." --dangerously-bypass-hook-trust

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cc Codex AI skill do?

Delegates coding tasks to Codex CLI for prototyping, debugging, and code review. Use when: (1) Backend/logic implementation, (2) Algorithm design and optimization, (3) Bug analysis and debugging, (4) API/database code generation, (5) Code quality review and refactoring. Triggers: "implement algorithm", "debug", "analyze code", "backend task", "API implementation", "optimize performance", "refactor", "generate prototype", "code review". IMPORTANT: Default sandbox="read-only" (analysis/review/patch generation); use sandbox="workspace-write" only when codex must run tests/builds to verify. Alw...

Why use Cc Codex on TypingMind?

Because you install it once and use it with any model. Cc Codex is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cc Codex in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Dianel555/DSkills/tree/main/skills/cc-codex. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cc Codex?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cc Codex?

As many as you like. As long as a model supports skills, you can use Cc Codex with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cc Codex AI skill free?

Yes. It is published on GitHub by Dianel555 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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