codex
Codex
Concept of the skill
What it is: Codex is OpenAI's terminal-first agent harness that drives a frontier GPT model (the GPT-5.5 generation). It is the GPT-running counterpart to Claude Code, with its own differentiators: resumable sessions, non-interactive exec piping, sandbox permission modes, MCP, on-demand subagents, and a /review code-review agent.
Mental model: Same harness-vs-model split as any agent CLI — Codex is the body, a frontier GPT is the brain. What makes Codex distinct among bodies is statefulness: a session is a durable object holding transcript, plan, and approvals that you can resume by ID, plus an exec mode that pipes results to stdout for scripting and in-process dispatch.
Why it exists: To operate a codebase with a GPT model under a controllable permission boundary, while making runs resumable and scriptable — so a long task can be continued across invocations (keeping its plan and approval history) and automated into pipelines instead of restarting cold every time.
What it is NOT: It is not the GPT model itself (the model is selectable inside Codex via /model), not the OpenAI SDK/API, and not the Claude Code harness — choosing Codex is a harness decision distinct from the GPT-vs-Claude model-routing decision.
Adjacent concepts: Claude Code (the rival harness), gpt-5-5 (the model-routing decision for the GPT the harness runs), the OpenAI API (the SDK surface), and generic resumable-loop patterns (the topology underneath).
One-line analogy: Codex is a cockpit with a flight recorder and autopilot resume — you can land, walk away, and later climb back into the exact same flight with its plan and clearances intact.
Common misconception: That resuming a Codex session means re-pasting context into a fresh run. It does not — codex exec resume <SESSION_ID> reuses the stored transcript, plan, and approvals; cold one-shots that re-send full context every turn waste tokens and discard that state.