codex-cli
Skill14 starsChanged 10 days agoMITView on GitHub
Use Codex CLI as a subagent. Lets the main agent prompt Codex CLI from the terminal in headless mode with the `codex` command, and send the goal, the decisions and the scope with the task. Use when the user asks to delegate work to Codex CLI, when a task needs a second independent agent, or when a plan needs a fresh perspective.
- Installs packages
24 other projects use a version of this.
Adopted by
Most recently taken up by
- kortix-ai/sunatheir own version, first seen Nov 8, 2026
- Awakehsh/awesome-agent-toolstheir own version, first seen Nov 8, 2026
- kortix-ai/CompanyOStheir own version, first seen Nov 8, 2026
- legibet/agent-skillstheir own version, first seen Nov 1, 2026
- samirpatil2000/skillstheir own version, first seen Nov 1, 2026
- sugarforever/01coder-agent-skillstheir own version, first seen Nov 1, 2026
Used with
Projects with it also use claude-cli, terraform and 3 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
julweberSkillclaude-cli
Expert control of the `claude` CLI (Claude Code). Use when running Claude Code interactively or non-interactively, managing sessions, configuring MCP servers, managing plugins, handling authentication, or piping prompts through claude for scripting.
Also in 3 projects that use this
ihiteshguptaSkillterraform
Expert in Infrastructure as Code with Terraform. Use for creating, managing, and versioning infrastructure across cloud providers.
Also in 3 projects that use this
GoogleSkillponytail
Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).
Also in 4 projects that use this
MicrosoftSkillcaveman
Ultra-compressed response style that reduces output token count while preserving technical accuracy, with intensity levels and auto-clarity safety rules
Also in 3 projects that use this
GoogleSkillgrill-me
A relentless interview to sharpen a plan or design.
Also in 3 projects that use this
Other versions24 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 24
- kortix-ai/suna★ 21ksame name
- kortix-ai/CompanyOS★ 21ksame name
- wentorai/Research-Claw★ 858same name
- scarletkc/agents★ 227same name
- revfactory/skills★ 160same name
- sugarforever/01coder-agent-skills★ 139same name
- georgekhananaev/claude-skills-vault★ 28same name
- samirpatil2000/skills★ 17same name
- mr-ske1r/1c-ai-devstart★ 16same name
- Awakehsh/awesome-agent-tools★ 8same name
14 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository24 other files it gives its agents.
- antigravity-cliSkill
- claude-codeSkill
- cline-cliSkill
- copilot-cliSkill
- cursor-cliSkill
- deepagents-codeSkill
- devin-cliSkill
- gemini-cliSkill
- goose-cliSkill
- grok-cliSkill
- hermes-agentSkill
- junie-cliSkill
- kilocode-cliSkill
- kimi-codeSkill
- kiro-cliSkill
- mistral-vibeSkill
- oh-my-piSkill
- openclaw-cliSkill
- opencode-cliSkill
- openhands-cliSkill
- pi-cliSkill
- qoder-cliSkill
- qwen-codeSkill
- <skill-name>Skill
The file
We split this skill into the rules it gives an agent
11 rules. 0 are common, 8 are distinctive, and 3 are very specific to this project.
0
Common
Most of the 21 edited versions we read keep these.
8
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 48
Secrets or policy-sensitive work: Do not pipe credentials into a subagent.
- Distinctive: line 50
Low return on investment: If writing the handoff costs more than doing the edit, do the edit.
- Distinctive: line 61
Treat every call as stateless delegation: the subagent keeps nothing between calls, so each command must carry its own state.
- Distinctive: line 71
Write the prompt as a transfer of shared state, not as a title.
- Distinctive: line 82
Prefer sequential delegations with explicit carry-over.
- Distinctive: line 96
After the subagent returns:
- Distinctive: line 104
Every vendor has its own terminal rules.
- Distinctive: line 108
Exit code 0 is not success: If stdout is empty, treat the run as failed and read stderr.
- Very specific: line 119
Keep all seven sub-headings, in this order, even if the answer is "none".
- Very specific: line 167
Run codex debug models. It prints the raw model catalogue as JSON.
- Very specific: line 172
If the user names a model, use it.
“Common” is measured: kept by at least 6 in 10 of the 21 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Codex CLI (subagent / task delegation)
<!-- =============================================================================
GLOBAL HALF — sections 1 to 5.
These sections are identical in every skill in this repository.
Copy them without any change. Do not put a vendor name or a flag in them.
A change here must be made in all skills at the same time.
============================================================================= -->What is it
This skill teaches your agent to use an agent from another vendor as a subagent.
Almost every coding agent has a headless mode. Headless mode runs the agent from the terminal with one command and returns the answer to stdout. This skill gives the command pattern for one such agent, and the protocol to transfer enough context with the task.
You stay the main agent. You keep the plan, the decisions and the conversation with the user. The subagent does one bounded task and reports back.
When to delegate
- The user asks for it. The user names another agent, or asks for a second opinion.
- Large or multi-step work. The task covers several files, phases or checkpoints.
- Code review with a fresh mind. Another agent reviews the work with a different lens and no memory of the decisions that produced it.
- Planning that needs different ideas. A second agent proposes options that you did not consider.
- An internal council. Several subagents answer the same question, and you compare the answers.
- Deep research. The other CLI has web search, web extraction or browser automation.
- Background investigation. A long task runs in the background while you continue in the foreground.
When not to delegate
- Small or single-step tasks. One or two edits, or a short explanation, are faster in this thread.
- Tight feedback loops. The user wants quick back-and-forth in one conversation.
- Secrets or policy-sensitive work. Do not pipe credentials into a subagent. Redact first.
- Context you already hold. Repeating the whole plan in a prompt adds no value.
- Low return on investment. If writing the handoff costs more than doing the edit, do the edit.
- Work that needs high precision and full judgement. A subagent without your context will break a task that depends on a detail only this session knows.
Delegation and context transfer protocol
An isolated subagent saves tokens, but it splits the story. The subagent does not see this conversation. It has no memory of the goal you agreed with the user, the decisions you already made, or the paths you agreed not to touch. A poor handoff causes misread tasks, wrong assumptions about the stack or the style, and wasted edits.
Treat every call as stateless delegation: the subagent keeps nothing between calls, so each command must carry its own state. A good handoff happens when you keep these practices in mind:
- Shared state handoff. The prompt carries the original goal, the decisions already made, and the explicit scope, to bridge the subagent's missing session history.
- Contextual preservation. The high-volume work stays in the isolated process, so the bulk never enters this conversation and no "split story" forms from missing history.
- Result reconciliation. What comes back is folded into this thread afterwards, so there is a single source of truth.
Write the prompt as a transfer of shared state, not as a title. Include all six fields:
| Include | Why |
| Goal | The same objective as the user, not only the immediate micro-task. |
| Decisions | Framework, patterns, naming, "use X not Y" — anything that would otherwise be guessed wrong. |
| Scope | The absolute paths and modules to touch, and the areas to leave alone. A relative path may not resolve where you expect. |
| Constraints | Performance, accessibility, compatibility, review gates, "no new dependencies". |
| Verification | The exact command the subagent must run and pass before it returns. |
| Output | For example: "report only, no edits", "apply edits with a minimal diff", "list the files changed". |
Prefer sequential delegations with explicit carry-over. Parallel runs diverge unless every run gets the same briefing.
Run the subagent in the mode that does the work without asking for approval. Headless mode has nobody to answer a permission prompt. Any mode that stops to ask will stall, or return an empty answer with a success exit code. Each CLI names this mode differently — take the flag from the vendor card below.
Never call a subagent in plan mode. Many CLIs have a plan or read-only mode. That mode makes the other agent write a plan for itself, which is not what you asked for: you want its work or its answer, and you keep the planning. Plan mode also waits for someone to approve that plan, so the run comes back with nothing. If you want no file changes, keep the auto-approving mode and write "report only, no edits" in the Output field. Do not use plan mode to make a run read-only.
After the subagent returns:
- Report to the user. Give a short summary. Do not paste long logs unless the user asks.
- Reconcile the context. Record the decisions it made, the files it changed, and the open risks, so this session stays the single source of truth.
CLI failure modes
Every vendor has its own terminal rules. A headless run fails quietly more often than it fails loudly.
- Wrap the call in an external timeout. A headless CLI can stall before its own timeout starts.
- Exit code 0 is not success. If stdout is empty, treat the run as failed and read stderr. A permission the CLI could not ask for, and a prompt that never arrived, both look like success.
- Never carry a flag habit from one CLI to another. The same short flag means different things in
different tools. In OpenCode,
-pis--password: passing a prompt to it empties the message and the run waits on stdin forever. Confirm every flag against the CLI's own--help. - An unrecognized-flag error means this skill is stale, not that the task is impossible. Read
--help, continue with the flags that exist, and tell the user which line in this file is wrong.
<!-- =============================================================================
VENDOR HALF — section 6.
Everything below is specific to this CLI.
Keep all seven sub-headings, in this order, even if the answer is "none".
Take every flag from the installed binary (`<cli> --help`), not from memory
and not from another skill in this repository.
============================================================================= -->Vendor card
Binary and prompt form
- Binary:
codex - Install:
npm install -g @openai/codex, orbrew install --cask codex(from the vendor GitHub README). - Prompt form: positional, under the
execsubcommand (aliascodex e).codex exec "prompt"runs non-interactively and exits when the task completes; the prompt string is a plain argument toexec, not a flag's value. A barecodex "prompt"(noexec) opens the interactive TUI and never returns. Stdin handoff also works:cat instructions.txt | codex exec -.
Headless and output flags
| Need | Flag |
| Run once and exit | exec "prompt" (alias e) |
| NDJSON event stream instead of formatted text | --json |
| Write the final assistant message to a file | --output-last-message, -o <path> |
| Layer a config profile | --profile, -p <name> |
| Skip loading the standard config file | --ignore-user-config |
Approvals and permissions
- Sandbox policy —
--sandbox,-s <read-only\|workspace-write\|danger-full-access>— bounds what model-generated shell commands can touch. - Approval policy —
--ask-for-approval,-a <on-request|never>— the current CLI reference lists these two values. It is a global flag, so put it beforeexecif you use it.execalready defaults tonever, so you rarely need it.--ask-for-approval neversuppresses prompts but does not by itself grant network access — that's a separatesandbox_workspace_write.network_accessconfig setting. - Full bypass —
--dangerously-bypass-approvals-and-sandbox(alias--yolo) — sets the sandbox todanger-full-accessand the approval policy tonevertogether. This is the flag to use for unattended delegation; only run it in an already-hardened environment (container/VM/CI). - Middle ground —
--approve-for-me(alias--not-so-yolo) — uses automatic approval review withon-requestapprovals and theworkspace-writesandbox. It conflicts with--sandboxand--yolo, and the interactive CLI rejects--ask-for-approvalwith it. This card does not verify it insideexec; checkcodex exec --helpfirst. codex execdefaults toAskForApproval::Nevereven without any flag — headless mode does not wait for approval by default.- What happens with nobody to answer: the official docs state plainly that when an approval is needed but unavailable in non-interactive mode, "Codex exits with an error." It does not stall.
Models and how to list them
Run codex debug models. It prints the raw model catalogue as JSON. Add --bundled to skip the
refresh and print only the catalogue bundled with the installed binary. Select the model for a run with
--model, -m <identifier>; reasoning effort/tier is a config-level concern, not part of the model
string. Interactively, /model lets you change the model and effort mid-session.
If the user names a model, use it. Otherwise run codex debug models (or check the docs below) and
Artificial Analysis for current identifiers and pricing before
picking one — Codex model names and retirements change often enough that a pinned one can fail
outright.
Command pattern
codex exec "GOAL: [goal] | DECISIONS: [decisions] | SCOPE: [paths] | CONSTRAINTS: [constraints] | VERIFICATION: [test_command] | OUTPUT: [format]" \
--dangerously-bypass-approvals-and-sandbox --model <identifier> 2>&1Prompt examples
- Implement:
codex exec "GOAL: [goal] | DECISIONS: [decisions] | SCOPE: [paths] | CONSTRAINTS: [constraints] | VERIFICATION: [test_command] | OUTPUT: [format]" --yolo - Logic check:
codex exec "GOAL: Analyze logic for edge cases and race conditions | SCOPE: [paths] | CONSTRAINTS: report only, no edits | VERIFICATION: [check_command] | OUTPUT: detailed report" --model <identifier> - Audit:
codex exec "GOAL: Security audit of the authentication layer | SCOPE: [paths] | CONSTRAINTS: report only, no edits | OUTPUT: audit report"
Docs and reference
- Flags, sandbox/approval values, delegation checklist: reference.md
- Vendor documentation: https://learn.chatgpt.com/docs/developer-commands?surface=cli
- Checked against the official documentation on 2026-11-05 (latest npm version 0.166.0). Not run
against an installed binary — confirm with
codex --helpbefore trusting a flag. Note on--full-auto: an earlier version of this card recommended it. It is now deprecated — it still works for one release cycle and prints a warning, but it is scheduled for hard removal, so a command relying on it will start failing. The bypass flag is--dangerously-bypass-approvals-and-sandbox(alias--yolo).
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

