Codex Cli

Codex CLI

Codex is a second agent on the same machine, with its own model behind it. That is the entire reason to reach for it: a model that did not write the code has no memory of intending it to work. Everything below follows from that one asymmetry — who wrote it, who reads it, and how much thinking each step is worth paying for.

This skill is for the supervising agent, not for Codex. If you are Codex, this does not apply — calling yourself buys nothing but a second opinion from the same mind. Claude Code is the intended caller.

It also assumes the machine is already set up: codex on PATH, the user logged in, and whatever MCP servers and tools they want available configured in ~/.codex/config.toml. If the binary is missing, auth has expired, or a run dies on permissions, report that plainly and stop — quietly falling back to doing it yourself hides the fact that the review the user asked for never happened.

Concrete flags belong to codex --help, which is authoritative and moves faster than this file. What follows is the judgment.

When to reach for it

Every invocation is a second model spending the user's money and your wall-clock time. It earns that when the problem is hard enough that another model changes the outcome — not as a reflex after every edit. Doing the work yourself and checking it with the project's own tests remains the normal path.

• When the user asks for it. They have already made the call; don't re-litigate it. Match the model and effort to the task and go.
• After writing something complex or expensive to get wrong. Your own review of your own diff is the weakest review available, because you are checking the code against the intent you already have in your head rather than against what it says. That weakness only matters when the defect would be costly — concurrency, migrations, security-adjacent paths, platform assumptions, anything on a compatibility surface. A routine edit that the suite already covers is not worth a review pass. Counter-example: an agent changed one side of a path comparison to a normalized form and left the other side platform-native; every test it wrote passed, because it wrote them against the same wrong mental model.
• When a demanding change is bounded well enough to describe in a prompt. A hand-off is worth it when you can state the goal, the files, and the acceptance check in a paragraph. That paragraph is also the honest test of whether you understand the change — if you cannot write it, delegating it just moves the confusion downstream. What "bounded" means is scoped-change, and it binds Codex exactly as it binds you: pass the boundary along in the prompt, because Codex cannot infer where the user drew it.
• When the work is long, mechanical, and verifiable. Wide renames, repetitive migrations, and mass edits with a green suite proving them buy throughput rather than insight, and they are cheap to check.
• When you are stuck. After two failed attempts on the same defect, a third attempt from the same context tends to repeat the second. A fresh agent with the symptom and the reproduction, and none of your accumulated theory, is a better use of the next few minutes.

When to keep it

• Ordinary work you can verify yourself. Most changes are this. Writing the prompt, waiting for the run, and reading the diff costs more than the edit, and a delegated pass over a small change mostly returns items you already knew. Absent a reason above, just do it.
• Judgment about words. User-facing copy, documentation, naming, and release notes need the taste and the context of the session that has been talking to the user, and they survive delegation badly. See ux-writing.
• Anything you cannot check afterwards. Delegating work you have no way to verify converts an unknown into a confident-sounding report, which is worse than the unknown. Establish the check first.
• Decisions the user reserved. Choosing the approach, committing, pushing, opening or merging a PR — those stay where the user put them. A permissive sandbox makes it possible for a delegated run to do all of them, which is a reason to scope the prompt tightly, not a licence to let it decide.

Choosing the model

Pick from the task's difficulty, not from habit. Reaching for the strongest model every time wastes the user's money on renames; reaching for the cheapest on a subtle bug wastes the user's afternoon.

• gpt-5.6-sol — the frontier model. Worth it for reviews that must not miss anything, root-cause hunts, concurrency and lock-ordering questions, cross-platform semantics, and any change whose failure mode is silent.
• gpt-5.6-terra — balanced, and the sane default for ordinary feature work inside a boundary you have already defined.
• gpt-5.6-luna — fast and cheap with a lower ceiling. Right when a test suite or a compiler, not the model, is what actually decides whether the result is correct.

Choosing the effort

Reasoning effort buys deliberation, not knowledge, and it multiplies both latency and cost. Scale it with how subtle the failure would be:

• medium — mechanical work with an immediate, objective check.
• high — real implementation work and routine reviews. The usual pick.
• xhigh — subtle bugs, unfamiliar subsystems, anything one attempt has already failed at.
• max — the hardest problems, when a wrong answer costs far more than the extra minutes. Deliberate, not habitual.

The pairing that matters most: review the code at least as high as you wrote it. A cheap review of an expensive change finds the typos and misses the reason you delegated it.

Running it

Drive the non-interactive surface — codex exec for work, codex exec review for review. Model and effort are per invocation: -m <model> and -c model_reasoning_effort=<level>, both overriding the user's config.toml defaults for that run only. Prefer codex exec review over the top-level codex review, which is equally non-interactive but takes the model through -c model="..." rather than -m. Review scope is --base <branch> for a branch, --uncommitted for the working tree, --commit <sha> for one commit. Everything else — --json, output files, resuming a session — is in codex --help.

Give it the permissions the task needs

This is the step that most often turns a delegated run into a wasted one. codex exec is sandboxed, and its own default — before the user's config is applied — is read-only: the model reads the repository, plans the change, and every write is refused. Failures inside the sandbox are handed back to the model rather than raised to you, so what returns is a fluent description of a change that never reached disk.

• Let the user's configuration apply, and reach for -s mainly to narrow. Their config.toml already encodes the permission level they are willing to run at, and on many machines it is the setting that actually works. -s read-only is a sound narrowing for a review or an investigation, since nothing should be written anyway. --ignore-user-config discards their settings wholesale and is rarely what you want.
• Raising the mode is a request, not a guarantee. -s workspace-write asks for a writable workspace; whether it is granted depends on the platform's sandbox backend and on any .rules policy in effect, and on a host without a working backend the writes are refused anyway. So confirm with git status on the target tree rather than with the run's summary. When the answer is "nothing changed", the fix lives in the user's configuration or their host setup — say so, rather than rerunning the same command or escalating the flag yourself.
• Widen the reach deliberately, not by default. --add-dir makes another directory writable, which matters when the work spans a worktree and its main checkout; -C sets the working root; --skip-git-repo-check allows running outside a repository. workspace-write does not imply network access — that is a separate setting (sandbox_workspace_write.network_access), so dependency installs inside it fail until it is enabled.
• Treat full access as the user's call. -s danger-full-access and --dangerously-bypass-approvals-and-sandbox remove the boundary that keeps a delegated agent inside the task. Some users configure exactly that globally and are happy with it; inheriting their setting is different from escalating to it yourself on a task they scoped narrowly.

Write the prompt like a brief

• Put the acceptance check in it. State the goal, the files in scope, the test or command that proves it, and the boundary it must not cross. Codex cannot see your conversation with the user, so anything the user said that constrains the change has to be restated.
• Ask review prompts for specifics. "Review this" returns prose. Naming what you are unsure of — the migration path, the error handling, the platform assumption — returns findings you can act on.

Reading the result back

A Codex run is a proposal, not a merge. You asked for a second model precisely because a single model's confidence is not evidence, and that cuts both ways.

• Read the diff, not the summary. The report describes what Codex meant to do. Only the diff says what it did, and the gap between the two is where the surprises live — the unrelated file it touched, the test it relaxed to make something pass, the fallback it added to keep an error from surfacing.
• Run the suite yourself. "Tests pass" from the agent that changed the tests is a claim about the same run that produced them.
• Findings are input, not a verdict. A review from a strong model still produces items that are wrong about this codebase or out of scope for this change. Judge each one, fix what is real, and say plainly which ones you dismissed and why — an unexplained dismissal reads as an oversight later.
• Report the division of labour. When the user reads the result, they should know which parts another agent wrote and what you verified. That is what makes the supervision worth anything.