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Codex Subagent

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davidondrej
codex-subagent

Launch OpenAI Codex CLI as a subagent (ChatGPT subscription auth, no API key). Use when delegating a self-contained coding task to Codex from another agent — parallel implementation work, a second opinion, or an independent verification pass.

Overview

Publisherdavidondrej
Repositoryskills
Skill namecodex-subagent
Stars
4.1K
Forks
599
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Codex Subagent 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.
  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/davidondrej/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/agent-orchestration/codex-subagent .claude/skills/codex-subagent
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Codex Subagent 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 Codex Subagent 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 Codex Subagent 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.

Codex CLI as a Subagent

Codex CLI is OpenAI's terminal coding agent. codex exec runs it non-interactively: it works autonomously in a sandbox, streams progress to stderr, and prints only the final message to stdout. Auth reuses the user's ChatGPT subscription — never an API key.

When to delegate

  • Self-contained coding task with clear success criteria (fix, feature, refactor, review).
  • Parallel work: several independent tasks at once (see Parallel runs).
  • Second opinion / independent verification of your own changes.

Do NOT delegate tasks that need conversation context you can't fully write into the prompt.

Preflight

bash
codex --version       # missing? npm i -g @openai/codex  (or: brew install --cask codex)
codex login status    # exit 0 + "Logged in using ChatGPT" = ready

Not logged in → stop and tell the user to run codex login (one-time browser OAuth). Never read, print, or copy credentials (~/.codex/auth.json).

Launch

bash
OUT=$(mktemp /tmp/codex-out.XXXXXX)
codex exec \
  --cd /path/to/repo \
  --model gpt-5.6-sol \
  --config model_reasoning_effort=high \
  --sandbox workspace-write \
  --output-last-message "$OUT" \
  "Full task prompt: goal, constraints, files to touch, definition of done." \
  </dev/null
  • Always use GPT 5.6 Sol (gpt-5.6-sol). Default reasoning effort to high. Pass both flags explicitly on every new Codex run.
  • Do NOT use Codex fast mode.
  • </dev/null is MANDATORY when stdin is not a real terminal (background shells, scripts): codex treats open stdin as extra context and waits forever for EOF.
  • Codex sees NOTHING of your conversation. Put all context in the prompt: goal, relevant paths, constraints, and how to verify it's done.
  • Long prompt? Pipe it via stdin instead: codex exec [flags] - < /tmp/task.md.
  • Wrap the command in a background/Bash subagent if your host agent has one (Cursor: Task tool with a shell subagent) so Codex's verbose stream stays out of the parent context. Fallback: a plain background terminal.
  • Runs take minutes and have no built-in timeout — background it and monitor.
  • Optional: --json for JSONL event stream.

Collect results

bash
cat "$OUT"                            # final message = the deliverable
git -C /path/to/repo status --short   # see what Codex actually changed

Follow-up in the same session (run from the same cwd — resume filters by cwd):

bash
codex exec resume --last "follow-up instruction" </dev/null

Parallel runs

Parallelize only genuinely independent tasks, and assign file ownership upfront so results merge cleanly. One git worktree per Codex run — never two in the same tree:

bash
git worktree add /tmp/wt-taskA -b codex/task-a
codex exec --cd /tmp/wt-taskA --model gpt-5.6-sol \
  --config model_reasoning_effort=high --sandbox workspace-write \
  -o /tmp/outA.md "task A" </dev/null

Failure modes

  • Hangs forever with no output → stdin was left open. Kill it, relaunch with </dev/null.
  • codex login status non-zero → the user must run codex login. Don't work around it.
  • ChatGPT plan rate limit hit → report to the user; never retry in a loop.
  • "Not a git repo" error → add --skip-git-repo-check, or init a repo first.
  • Network is blocked inside the workspace-write sandbox by default. If the task needs it (installs, API calls): -c sandbox_workspace_write.network_access=true.
  • NEVER use --dangerously-bypass-approvals-and-sandbox.

Rules

  • One task per launch. Split big jobs into multiple launches.
  • Review Codex's diff yourself before declaring the task done.

Cursor-native wrapper (optional)

For auto-routing and /codex invocation inside Cursor, add ~/.cursor/agents/codex.md — a custom subagent whose description is "delegates coding tasks to Codex CLI" and whose body points at this skill.

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 Codex Subagent AI skill do?

Launch OpenAI Codex CLI as a subagent (ChatGPT subscription auth, no API key). Use when delegating a self-contained coding task to Codex from another agent — parallel implementation work, a second opinion, or an independent verification pass.

Why use Codex Subagent on TypingMind?

Because you install it once and use it with any model. Codex Subagent 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 Codex Subagent in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/davidondrej/skills/tree/main/skills/agent-orchestration/codex-subagent. 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 Codex Subagent?

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 Codex Subagent?

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

Is the Codex Subagent AI skill free?

Yes. It is published on GitHub by davidondrej 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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