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Field Guide · No.2 current · May 2026

Codex 2026:
the practical map.

Codex is not one thing. It is a local CLI, a desktop app, cloud tasks in ChatGPT, an IDE extension, mobile access, automations, skills, MCP, AGENTS.md, hooks, subagents, and app worktrees. This guide maps the pieces without pretending every piece should run unattended.

The practical difference: Claude Code feels terminal-first; Codex puts more of the project in an app surface. If you use both, the win is not picking a side. It is knowing where planning, implementation, and verification each belong.

OpenAI docs first practitioner claims marked no local-file references verified May 29, 2026
Using Claude Code? Each Codex section calls out the nearest Claude Code equivalent, then links back to the Claude-side process where the comparison needs more detail.
NEW

Latest updates

If you have read the Codex map before, start here. This is the dated layer for guide changes and recently verified product boundaries.

May 30, 2026

Guide update: surface choice comes first

The Codex guide now treats Codex as a multi-surface tool: CLI, App, cloud tasks, IDE extension, and mobile remote access. The practical question is not "use Codex or not"; it is where the work should run and what proof that surface can produce.

Returning-reader note: start with The Surfaces before jumping to agents, skills, or automations.
Verified May 2026

Remote control is broader, but still host-bound

OpenAI's current remote-connection docs say mobile setup supports Codex App hosts on macOS and Windows. It still starts from Codex App, not the CLI or IDE extension, and the host must be awake, online, and signed in.

Use it for: approvals, steering, diffs, screenshots, and status checks from a phone — not as a fake cloud machine.
Verified May 2026

Automations are useful, but bounded

The automation section now separates standalone runs from thread automations and calls out the host/project boundary. Project-scoped Codex App automations may still depend on the app running and the selected project being available on disk.

Practical move: make the first automation read-only and route findings into a review surface.
Verified May 2026

AGENTS.md and subagents got sharper

The context and agent sections now include the working details that matter in practice: instruction discovery order, the documented project-doc byte budget, built-in agent roles, custom TOML agents, and conservative fan-out defaults.

Why it matters: durable instructions and parallel workers help only when they stay scoped, local, and reviewable.
A

The Surfaces

Codex work can happen locally, in the app, in the cloud, in an IDE, or from your phone. The first practical skill is picking the right surface before the task starts.

SurfaceUse it forWatch out
Codex CLITerminal-native local work, SSH/devbox use, scripts, repo tasks where your local tools and credentials matter.It is powerful, but you still need sandbox and approval discipline.
Codex AppParallel threads, local/worktree/cloud modes, Git UI, terminal, browser/device validation, skills, hooks, and automations.Some automations need the app and project available on disk.
ChatGPT Codex cloudCloud tasks against connected repos: fix bugs, write features, answer codebase questions, propose PRs.Cloud convenience is not a substitute for scoped tasks and review.
IDE extensionWorking beside the editor, with connected repo context and familiar code navigation.Do not split truth between IDE chat and repo docs.
Mobile accessStart or continue threads, approve commands, review diffs, screenshots, and outputs from a phone.The connected host still matters. If the host is asleep or disconnected, remote access stops.
Do not use this when: the environment choice is unclear. If the task needs local secrets, browser/device proof, or an existing dev server, stay local. If it only needs repo code and a reviewable PR, cloud can be enough. If it needs quick steering, mobile is fine; if it needs new setup, use the host.
Claude Code equivalent: Claude's closest pieces are claude, claude agents, background sessions, cloud routines, remote access, and Computer Use. Codex App bundles more of that into one visible desktop surface. Compare Claude agents and sessions →
B

AGENTS.md & Durable Context

Codex's repo memory primitive is AGENTS.md. Treat it like code: short, local, versioned, and specific enough to prevent mistakes.

Discovery order

Codex reads global guidance first, then project-path guidance from the project root down to the current directory. More specific instructions appear later and can override broader ones.

Override files

OpenAI documents AGENTS.override.md as a higher-priority option alongside ordinary AGENTS.md.

Byte budget

The documented default combined project-doc limit is 32768 bytes. You can raise it, but that is not a free lunch.

Fallback names

Codex can be configured to look for fallback instruction filenames. Useful for teams migrating from other agent conventions.

Using Codex?Using Claude Code?
Put durable repo rules in AGENTS.md and project-local agent/config files.Put always-true repo rules in CLAUDE.md; defer optional material to skills and path-scoped rules.
Use ~/.codex/AGENTS.md for personal operating rules.Use ~/.claude/CLAUDE.md for personal operating rules.
Keep instructions under the byte budget and close to the code.Keep root CLAUDE.md lean; "Would removing this cause mistakes?" remains the test.
Do not use this when: the material is a long procedure, a stale architecture tour, a temporary plan, or a one-time preference. Put procedures in skills, current state in a living project note, and proof in reports or tests.

AGENTS.md audit prompt

Use this before bloating repo memory. The goal is fewer mistakes, not more lore.

Inspect the AGENTS.md instructions that apply to this directory before changing code.

Report:
- which files you read
- which instructions affect this task
- which lines are stale, duplicated, contradictory, or too broad
- one small cleanup that would prevent a real mistake

Do not edit yet. Keep the recommendation under 10 bullets.
C

Skills, Hooks & Plugins

Codex uses the same broad idea as Claude Code: progressive disclosure for procedures, deterministic hooks for guarantees, and plugins for packaging repeated capability.

Skills

Use skills for repeatable procedures and reference material that should load only when relevant. OpenAI's Codex docs include skill creation and skill management as first-class app/CLI concepts.

Practical move: turn repeated prompts into skills, not giant AGENTS.md paragraphs.

Hooks

Use hooks for events that must happen regardless of model mood: block risky commands, format after writes, capture state, or enforce checks before stopping.

Practical move: if skipping it would be dangerous, make it deterministic.

Plugins

Package skills, hooks, MCP, and project helpers into installable bundles when a procedure should travel across repos or teammates.

Practical move: keep local one-offs local; package only proven repeated procedures.

Verification skills

The highest ROI skills are not fancy. They summarize diffs, run checks, generate PR notes, review risky areas, and produce evidence.

Practical move: automate proof, not just production.

Skill extraction prompt

Use this when you notice the same long prompt showing up for the third time.

I keep repeating this process:
<paste the steps or prompt>

Turn it into a Codex skill design.

Return:
- trigger phrases
- a short SKILL.md outline
- what belongs in reference files instead of AGENTS.md
- one verification step
- one case where this should stay a normal prompt

Do not propose a plugin unless this process needs to travel across repos or teammates.
Do not use this when: the work is a one-off, the guard must run every time, or a simple checklist would do. Use hooks for guarantees; use skills for optional procedure.
Claude Code equivalent: Claude's skills, hooks, plugins, and slash-command-as-skill model map closely. The teaching point is identical: skills are for procedures; hooks are for guarantees; memory files are for facts. Open the Claude skills map →
D

Subagents, Threads & Worktrees

Codex subagents are configurable workers. The app adds the practical surface for parallel threads, worktrees, and cloud/local mode selection.

Codex conceptWhat to learnWhy it matters
Built-in agentsdefault, worker, explorer.Use different workers for execution vs. investigation.
Custom agentsPersonal agents in ~/.codex/agents/*.toml; project agents in .codex/agents/*.toml.Make recurring roles explicit instead of re-prompting them every time.
Agent settingsagents.max_threads, agents.max_depth, runtime bounds.Fan-out has cost and risk. Defaults are conservative for a reason.
WorktreesUse app worktrees for parallel implementation.Parallel agents need file isolation or they step on each other.
First safe pattern

Run one explorer to map files, one worker to implement a scoped fix, then one fresh reviewer to inspect the diff. Do not start with five writers.

Explorer-to-worker handoff

This keeps the reader and writer roles separate without creating a management mess.

Explorer task:
Map the files, commands, and risks for this change. Do not edit. Return exact paths, likely tests, and unknowns.

Worker task:
Use the explorer notes only as input. Implement the smallest safe diff for:
<task>

Rules:
- stay inside <allowed paths>
- ask before touching shared contracts
- done means tests/checks run and changed files listed
Do not use this when: the task is tiny, the files heavily overlap, the acceptance criteria are still fuzzy, or the change needs one continuous model of security, data, or product risk. Start with one lead session, then split only the independent pieces.
Claude Code equivalent: Claude has subagents, background sessions, agent teams, Agent View, and worktree isolation. Codex's equivalent is more app/thread oriented; Claude's is more terminal/TUI oriented. Open the Claude agent map →
E

Automations & Remote Control

Codex automations are recurring background tasks. The useful version is not "let it do everything"; it is "wake up, inspect, produce a useful artifact, and stop."

Standalone automations

Use when each run should be independent: daily triage, weekly docs drift, recurring dependency checks, periodic deploy health reports.

Thread automations

Use when the recurring work should preserve a continuing conversation: ongoing project triage, long-running investigation, recurring status synthesis.

Triage inbox

Codex can put automation findings into an inbox. That matters because the human needs a review surface, not a silent transcript graveyard.

Mobile host

Mobile access lets you steer from the phone, but the host still supplies the environment. Use it for approvals and steering, not as a fake cloud machine.

Read-only triage automation

The safest first automation produces a reviewable artifact and changes nothing.

Every weekday morning, inspect the project and produce a triage note.

Scope:
- read issues, failing checks, recent commits, and TODOs
- do not edit files
- do not run migrations, deploys, dependency updates, or external writes

Output:
- top 5 items by urgency
- evidence for each item
- suggested owner/action
- anything that needs human approval
Do not use this when: the task can spend money, contact users, deploy, migrate data, change dependencies, or needs taste and judgment on every run. Automate inspection first; make changes only after the pattern proves boring.
Claude Code equivalent: Claude Routines are cloud scheduled agents; /loop is session-scoped; Remote Control drives a local session from phone/web. Codex automations are app-centered and can be tied to project/thread state. Compare Claude cloud and remote surfaces →
F

MCP & Integrations

MCP gives Codex access to tools and data beyond the repo. Treat every integration as a capability with a blast radius, not a novelty to collect.

IntegrationBest useRule
OpenAI Docs MCPCurrent OpenAI API/platform documentation.Good default for fast-moving OpenAI work.
Context7Library docs and modern framework references.Use when training cutoff is likely stale.
Playwright / browser toolsRendered UI verification, screenshots, console logs, flows.Browser proof beats "looks right in code."
GitHubIssues, PRs, review context, CI failures.Scope tokens and permissions. Do not let it rewrite history unattended.
Sentry / logsProduction error triage and regressions.Treat external data as untrusted context.

MCP fit check

Run this before adding another integration. Tool access should replace real tab switching or stale guessing.

Before adding MCP for this task, decide if it is worth it.

Need:
<what live data or action the agent needs>

Return:
- whether repo files or public docs are enough
- the minimum MCP server and permissions needed
- whether read-only access is sufficient
- what the agent must never do through this tool
- how we will verify the result without trusting the tool blindly
Do not use this when: static docs, repo search, or a copied error log answer the question. Do not hand an agent broad production write access just to avoid opening a dashboard.
Claude Code equivalent: both ecosystems use MCP. The decision table is the same: use MCP for live external systems; use skills for reusable instructions; use hooks for deterministic enforcement. Open the Claude integration map →
G

The Practical Process

Practitioner writeups that hold up converge on a boring loop: plan, persist truth, scope one ticket, execute, verify, report, update durable docs.

StepCodex moveClaude Code analog
1. PlanUse ChatGPT/Codex thread as conductor for the next bounded outcome.Use a lead Claude session or Ultraplan for larger design.
2. Persist truthUpdate AGENTS.md, ticket docs, current state, verification notes.Update CLAUDE.md, skills, memory, and project docs.
3. ExecuteUse CLI/App/cloud/worktree based on environment needs.Use solo session, subagent, background agent, or team.
4. VerifyRun tests, inspect diffs, capture browser/app screenshot evidence where relevant.Run tests, hooks, browser automation, Computer Use, or reviewer subagent.
5. ReportRequire a completion report and unresolved-risk list.Same. Never accept "done" without evidence.

Proof ladder

Start with the cheapest proof that could catch the bug: diff inspection, targeted test, broader test, type/lint/build, browser or device smoke, then a fresh review. Do not skip the rendered check for UI work.

Good completion report

It names changed files, commands run, what passed, what was not tested, screenshots or links when relevant, and one plain remaining-risk sentence. Anything less is a status update, not proof.

Bounded ticket prompt

This is the default shape for useful Codex work: scope, evidence, then a report.

Work on exactly this ticket:
<paste ticket>

Before editing:
- inspect the relevant files
- name the smallest safe diff
- list any paths you will not touch

Rules:
- do not edit outside <allowed paths>
- keep behavior changes explicit
- preserve unrelated work

Done means:
- changed files listed
- tests/checks run with results
- manual verification noted if relevant
- proof attached when UI, mobile, data, or external behavior changed
- remaining risks named plainly
Do not use this when: the ticket cannot name allowed paths, acceptance criteria, and proof steps. Do a planning pass first; implementation before scope usually creates a larger review bill.
H

Using Codex + Claude Code Together

The strongest process is a conductor pattern: one deep context holder owns the project truth, while Claude Code and Codex do bounded work in separate lanes. Use them to create independent evidence, not more tabs to babysit.

Using Claude Code? Start from the same acceptance criteria, put each tool in its own branch or worktree, and judge the outputs with a fresh session. Open the Claude-side process →
Use both forCodex laneClaude Code lane
Alternative reviewsUse Codex App or CLI as the fresh reviewer with repo/browser context.Use Claude Code reviewer subagent, /code-review, or a background session.
Parallel implementationRun one worktree/thread on the same acceptance criteria.Run one worktree/background session or team teammate on the same acceptance criteria.
Project steeringUse Codex App and mobile access as the dashboard.Use claude agents, /goal, /loop, and routines for terminal/cloud automation.
Final callAsk Codex to compare diffs and risks.Ask Claude to compare diffs and risks. If they disagree, demand evidence.

Competition build prompt

Use this with either tool. Replace the competitor name honestly: Claude Code, Codex, or a named teammate.

You are competing against <competitor name>. Build the best solution to this exact task.

Task:
<paste the task>

Acceptance criteria:
<paste the checklist>

Rules:
- Same repo, same constraints, no shortcuts.
- Optimize for correctness, smallest safe diff, clear product fit, and verification evidence.
- Do not imitate the competitor. Beat them by being more precise.
- Done means: changed files listed, tests/checks run, risks named, and any manual verification described.

Cross-tool review prompt

Give Codex Claude's diff, or give Claude Codex's diff. The review should be sharper because it has no sunk cost.

Review this work as if <competitor name> already approved it and your job is to find what they missed.

Focus on:
- correctness and hidden edge cases
- security, data loss, privacy, and permission mistakes
- missing tests or weak verification
- unnecessary scope creep
- mobile/browser/product regressions

Give file/line evidence. Rank findings by severity. If there are no real issues, say that clearly and name the residual risk.

Judge-and-merge prompt

Use a fresh session for this. The judge should not be the same context that wrote either attempt.

Compare Solution A and Solution B. Pick the winner or merge the best parts.

Judge by:
- correctness
- maintainability
- smallest safe diff
- test and browser evidence
- product fit
- risk of hidden follow-up work

Do not compromise by averaging. Make a decision, explain it, and give the next concrete action.
Do not use this when: the work is urgent, tiny, tightly coupled, or blocked on one product decision. Cross-tool competition helps when independent approaches can expose blind spots; it wastes review attention when there is only one obvious edit.
Reality check: the competition prompt is not magic. It is useful only when you pair it with boring discipline: separate worktrees, identical acceptance criteria, fresh review, and proof.
I

Debunked & Caveated

J

Codex Mastery Checklist

This mirrors the Claude Code checklist style. The next step is making these interactive in the Dojo.

Codex 2026 — learn this
36 items
Surfaces
Install and launch Codex CLI from the official docs.
Choose local vs cloud vs worktree before starting work.
Use Codex App as a thread dashboard, not just another chat window.
Pair mobile access and understand host availability.
Use the IDE extension without splitting repo truth out of files.
Context
Write a lean root AGENTS.md.
Add a nested AGENTS.md for one package or app.
Use AGENTS.override.md only when override semantics are really needed.
Know the project_doc_max_bytes budget.
Keep current-state docs separate from standing rules.
Skills and hooks
Create one skill from a repeated process.
Use a skill reference file instead of stuffing docs into AGENTS.md.
Add one safe hook for a deterministic guard or formatter.
Package proven process pieces into a plugin only after repeated use.
Agents and worktrees
Use explorer for read-heavy investigation.
Use worker for scoped implementation.
Create one custom TOML agent with a narrow role.
Keep agents.max_depth conservative.
Use worktrees for parallel implementation.
MCP and verification
Add one MCP server that removes real tab switching.
Authenticate HTTP MCP with the documented flow.
Use browser tools for rendered UI proof.
Make completion reports mandatory.
Separate tests passing from product correctness.
Automations
Create a read-only triage automation.
Create a thread automation for a long-lived project question.
Use Triage inbox output instead of silent transcripts.
Promote automation only after two useful manual runs.
Define human checkpoints for deploys, migrations, dependencies, and external copy.
Cross-tool operating
Map a Claude Code process to Codex using the comparison rows above.
Map a Codex process to Claude Code when terminal-native work is better.
Use the Workforce blueprint for conductor/worker/verifier roles.
Keep one durable source of truth so multiple agents do not drift.
Spend premium reasoning only where judgment matters.
Close the loop with evidence every time.
S

Sources

Primary sources first. Reviews and community writeups are included only as practitioner signal.

SourceWhat it supports
OpenAI Codex CLI docsCLI surface, install, local operation, command references.
OpenAI openai/codex repoOpen-source client and CLI implementation.
OpenAI Codex App featuresApp modes, Git UI, worktrees, terminal, browser/device features, skills, hooks.
OpenAI Codex AutomationsStandalone and thread automations, Triage inbox, app/project requirements.
OpenAI Remote ConnectionsMobile access and host boundaries.
OpenAI AGENTS.md guideInstruction discovery, override files, byte budget, fallback names.
OpenAI Codex SubagentsBuilt-in agents, custom TOML agents, max threads/depth/runtime settings.
OpenAI Codex MCPMCP transports, auth, config, server instructions, examples.
OpenAI Codex SkillsSkill concepts and management.
OpenAI Codex HooksDeterministic lifecycle automation.
OpenAI Codex Best PracticesPlanning, verification, scoped work, and automation caution.
OpenAI Help: Using Codex with your planPlan and product access reference.
Augment Code reviewThird-party review signal, not used as primary fact source.
Practitioner process threadAnecdotal pattern: conductor, scoped tickets, durable docs.