Codex CLI handles planning, design, and complex code implementation.

MITAuto-check passedDevelopment

Install Codex System

skills CLI
$ npx skills add DeL-TaiseiOzaki/claude-code-orchestra --skill codex-system -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install DeL-TaiseiOzaki/claude-code-orchestra codex-system --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/DeL-TaiseiOzaki/claude-code-orchestra.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/codex-system .claude/skills/codex-system && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
codex-system
GitHub stars
199
Token cost
~4.2k tokens
SKILL.md length
1,509 words
Files
6 (incl. references)
Skills in repo
15
Repo updated
First seen
Licence
MIT

At a glance

Codex CLI handles planning, design, and complex code implementation.

  • Works in 2 steps: Planning & Design → Complex Implementation
  • : architecture design
  • SKILL.md covers Two Roles of Codex, When to Delegate, How to Consult and Task Templates, plus 4 more sections
  • Calls python3, codex and bash

What it does

Codex System is an agent skill from DeL-TaiseiOzaki/claude-code-orchestra. Codex CLI handles planning, design, and complex code implementation. Use for: architecture design, implementation planning, complex algorithms, debugging (root cause analysis), trade-off evaluation, code review. External research is NOT Codex's job — use general-purpose-opus instead. Explicit triggers: "plan", "design", "architecture", "think deeper", "analyze", "debug", "complex", "optimize".

Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/agent-prompts.md`, `references/code-review-task.md` and `references/delegation-patterns.md`).

It sits in Development, covering Root cause analysis and Debugging. The licence is MIT.

When your agent uses it

  • : architecture design
  • Implementation planning
  • Complex algorithms
  • Debugging (root cause analysis)

Example prompts

  • “s job — use general-purpose-opus instead. Explicit triggers:”
  • “design”
  • “architecture”
  • “/codex-system”

Requirements

  • Python 3
  • Node.js

Workflow steps

2 steps, taken from the step headings in SKILL.md.

  1. Planning & Design
  2. Complex Implementation

What it can do on your machine

Read from SKILL.md and the folder at commit ef0d8f8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3
    • codex
    • bash
    • claude
    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Codex System loads about 4.2k tokens when it runs, and up to ~7.8k if it reads all its reference files. Until then it costs about 102 tokens; SKILL.md has 1,509 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~102
When it runs · the whole SKILL.md, loaded when a task matches
~4.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from DeL-TaiseiOzaki/claude-code-orchestra at commit ef0d8f8, republished under its MIT licence (© DeL-TaiseiOzaki). 1,509 words, ~4,223 tokens.

Download SKILL.mdSave it as .claude/skills/codex-system/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
codex-system
description
Codex CLI handles planning, design, and complex code implementation. Use for: architecture design, implementation planning, complex algorithms, debugging (root cause analysis), trade-off evaluation, code review. External research is NOT Codex's job — use general-purpose-opus instead. Explicit triggers: "plan", "design", "architecture", "think deeper", "analyze", "debug", "complex", "optimize".
metadata.short-description
Codex CLI — planning, design, and complex implementation

Codex System — Planning, Design & Complex Implementation

Codex CLI handles planning, design, and complex code implementation.

Preflight (SSOT): Update CLIs before each session — claude update && npm install -g @openai/codex@latest. Releases drift frequently (model names, flags, sandbox semantics). Other skills reference this line instead of repeating it. Delegation policy (when to delegate): .claude/rules/codex-delegation.md

Two Roles of Codex

1. Planning & Design
  • Architecture design, module composition
  • Implementation plan creation (step breakdown, dependency ordering)
  • Trade-off evaluation, technology selection
  • Code review (quality and correctness analysis)
2. Complex Implementation
  • Complex algorithms, optimization
  • Debugging with unknown root causes
  • Advanced refactoring
  • Multi-step implementation tasks

When to Delegate

Delegation policy — when to consult, when NOT to, and trigger criteria — lives in .claude/rules/codex-delegation.md (SSOT). This skill covers how to consult. The other half of "how" is how to verify what came back: root AGENTS.md → Guardrails (Completion Verification) is mandatory for every write-access call, and Verify Before Trusting below is its executable form. A delegated CLI is never trusted on its self-report.

How to Consult

Invoke Codex through the wrapper — .claude/skills/_shared/codex_consult.py — instead of calling codex exec directly. codex exec itself waits for stdin EOF and hangs indefinitely when stdin is left open (e.g. background shells); the wrapper always runs it with stdin closed, so callers never need < /dev/null. It also passes the prompt as a single argv element (no shell, so nested quotes in the prompt body never break it), captures stdout/stderr to timestamped files under .claude/logs/codex/, and reports one JSON result instead of silently discarding stderr.

python3 .claude/skills/_shared/codex_consult.py (--prompt-file PATH | --prompt-stdin) [--label L] [--caller AGENT] [--sandbox {read-only,workspace-write,danger-full-access}] [--model M] [--timeout N] [--cwd DIR] [--project-root DIR] [--skip-git-repo-check] [--config KEY=VALUE]

Consulting a peer CLI instead of Codex. Claude Code and Antigravity go through .claude/skills/_shared/cli_consult.py --cli {claude,antigravity} --prompt-file PATH, unrestricted unless --read-only — which Antigravity refuses, because its headless mode auto-approves every tool call and the restriction cannot be enforced from the caller (--resume SESSION is Claude-only; --cli-arg forwards a native flag; default timeout 900 s; same four exit codes as below). Never shell out to a CLI directly — the wrapper-only rule and the per-callee permission mapping live in root AGENTS.md. Codex's sandbox and --config semantics stay here because they are Codex-specific; everything cross-CLI is in that rule file.

  • Write the prompt body (Objective / Constraints / Relevant files / Acceptance checks / Output format) to a file and pass it via --prompt-file; use --prompt-stdin to pipe a short prompt instead. Any path works — the ad-hoc snippets below use mktemp, while skills write to .claude/logs/codex/prompt-{label}.md so the prompt sits next to the response the wrapper writes for it, which is what makes a disappointing answer diagnosable afterwards.
  • --sandbox defaults to danger-full-access, matching .codex/config.toml. Pass --sandbox read-only explicitly for planning and review calls — see Sandbox Modes below.
  • --model defaults to $CODEX_MODEL, else gpt-5.6-sol. --label is a [a-z0-9-]+ slug used in the log filenames (default consult). --timeout defaults to 600 seconds. --skip-git-repo-check covers the non-Git working directory case — see references/troubleshooting.md.
  • --config KEY=VALUE (repeatable) forwards a Codex config override, e.g. --config model_reasoning_effort=low for a cheap question. Keys naming a sandbox or approval setting are refused: --sandbox must stay the single visible statement of what Codex is allowed to touch.
  • The wrapper prints exactly one JSON object: {ok, exit_code, model, sandbox, write_access, timed_out, duration_sec, response_file, stderr_file, response_chars, response_head, error}. response_head is only a ~400-char preview — read the file at response_file for the full response, and stderr_file (non-null whenever Codex wrote to stderr) when diagnosing a failure.
  • Exit codes: 0 succeeded · 1 bad args or unreadable prompt file · 2 codex not on PATH · 3 codex exited non-zero or timed out.
Task tool parameters:
- subagent_type: "general-purpose-opus"
- run_in_background: true (optional)
- prompt: |
    Consult Codex about: {topic}

    Write the prompt body below to a file, then run the wrapper against it:

    Objective: {single-sentence objective}
    Constraints:
    - {constraint 1}
    Relevant files:
    - {file paths}
    Acceptance checks:
    - {commands}
    Output format:
    ## Analysis
    ## Recommendation
    ## Implementation Plan
    ## Risks
    ## Next Steps

    python3 .claude/skills/_shared/codex_consult.py --prompt-file {prompt_path} --label {short-slug} --sandbox read-only

    Parse the JSON result. ok: true means only that codex exec exited 0 — it is
    not a completion report. Read response_file for the full analysis, and judge
    it yourself: state which claims you verified and which you could not.
    Return CONCISE summary (key recommendation + rationale + what is unverified).

For a write-access subagent call, add the Verify Before Trusting steps to the delegated prompt as well, and require the subagent to return the verify.sh and verify_delegation.py verdicts. A subagent that summarises Codex's self-report without them has not verified anything, and its summary must not be treated as a completion.

Direct Call (short questions, responses up to ~50 lines)
bash
echo "Objective: {brief question}" | python3 .claude/skills/_shared/codex_consult.py --prompt-stdin --label quick-question --sandbox read-only
Having Codex Implement Code
bash
prompt_file="$(mktemp)"
cat > "${prompt_file}" << 'EOF'
Objective: Implement {detailed implementation task}
Constraints:
- Follow existing project conventions
- Keep diffs minimal
Relevant files:
- {file paths}
Acceptance checks:
- {commands}
Output format:
## Changes Made
## Validation
## Remaining Risks
EOF
python3 .claude/skills/_shared/codex_consult.py --prompt-file "${prompt_file}" --label implement --sandbox danger-full-access

The call is not finished here. Continue with the next section.

Verify Before Trusting

Mandatory after every workspace-write / danger-full-access call (Codex or a peer CLI), per root AGENTS.md → Guardrails. ok: true from the wrapper means only that codex exec exited 0; it says nothing about whether the change is correct, complete, or honest.

1. Run the acceptance checks from your own prompt, plus the project gates:

bash
bash .claude/skills/_shared/verify.sh

Exit 0 = overall: "pass". Exit 2 = a gate failed, or no gate ran at all (overall: "no_gates") — a delegated code change must never be accepted with zero checks executed. Exit 1 bad arguments, 3 the log file could not be written. Read log_file for the full output.

2. Collect the Guardrail evidence from the diff, naming the scope the prompt actually authorised:

bash
python3 .claude/skills/_shared/verify_delegation.py --base HEAD \
  --expect-files {file the task was supposed to change} \
  --forbid-outside {directory the task was scoped to}

It reports deletions, placeholders, weakened_tests, out_of_scope_files, missing_expected_files, scope_empty, and the captured diff at diff_file. Exit 0 = nothing actionable and no violated expectation — deletions alone land here, reported but not actionable on their own, and exit 0 is still not an accept. Exit 2 = an actionable finding (placeholders, weakened_tests) or a violated expectation (out_of_scope_files, missing_expected_files, scope_empty). Use --base <pre-delegation ref> when Codex committed its work; the default HEAD covers the usual uncommitted case.

3. Read the diff and decide. verdict is always needs-review and there is no verdict that means "accepted" — deliberately. The pattern list is heuristic (a legitimate test deletion exists, and a TODO in a docstring is not a stub), and only you know what the prompt authorised. Reject the completion when the diff shows any of:

  • tests deleted, skipped (@pytest.mark.skip), or weakened (assertions removed or loosened) to make the suite pass;
  • exceptions silently swallowed (except: pass or equivalent) to hide failures;
  • hard-coded return values substituted for real logic — the one Guardrail item no script screens for, so it is listed under not_automated and only your read of the diff catches it;
  • stub or placeholder completions where real logic was requested;
  • files changed that the task never mentioned, or unapproved deletions.

4. On failure, follow the re-delegate-once protocol (cli-execution.md (c)): report the specific failures with evidence, re-delegate once with the original prompt plus the failure context appended, and if the second attempt also fails verification, halt and require explicit user approval before proceeding. Never patch over a failed delegation silently.

Show full SKILL.md (500 more words)Show less
Sandbox Modes
ModeSandboxUse Case
Analysisread-only (explicit opt-in)Design review, debugging, trade-off analysis
Implementationdanger-full-access (default)Implementation, fixes, refactoring

The wrapper's own default is danger-full-access, the same value .codex/config.toml sets, so an implementation call needs no flag and an analysis call must pass --sandbox read-only explicitly. The wrapper used to default to read-only — deliberately stricter than a bare codex exec — which meant the access Codex had depended on whether it was reached through the wrapper or directly, and neither call site said so. Aligning the two removes that divergence; what has not changed is that the wrapper always sends --sandbox explicitly, so the granted access is readable in the command rather than inherited from a config file, and --config keys naming a sandbox or approval setting stay refused.

Because the default is unrestricted, every call is bracketed by an edit snapshot and the JSON result carries an edits object naming the files Codex created, changed, or deleted, plus caller and label. Pass --caller <your agent name> so .claude/logs/cli-tools.jsonl records which subagent asked for a change, not only which CLI made it.

Task Templates

Implementation Planning
bash
prompt_file="$(mktemp)"
cat > "${prompt_file}" << 'EOF'
Create an implementation plan for: {feature}

Context: {relevant architecture/code}

Provide:
1. Step-by-step plan with dependencies
2. Files to create/modify
3. Key design decisions
4. Risks and mitigations
EOF
python3 .claude/skills/_shared/codex_consult.py --prompt-file "${prompt_file}" --label plan --sandbox read-only
Design Review
bash
prompt_file="$(mktemp)"
cat > "${prompt_file}" << 'EOF'
Review this design approach for: {feature}

Context: {relevant code or architecture}

Evaluate:
1. Is this approach sound?
2. Alternative approaches?
3. Potential issues?
4. Recommendations?
EOF
python3 .claude/skills/_shared/codex_consult.py --prompt-file "${prompt_file}" --label design-review --sandbox read-only
Debug Analysis
bash
prompt_file="$(mktemp)"
cat > "${prompt_file}" << 'EOF'
Debug this issue:

Error: {error message}
Code: {relevant code}
Context: {what was happening}

Analyze root cause and suggest fixes.
EOF
python3 .claude/skills/_shared/codex_consult.py --prompt-file "${prompt_file}" --label debug --sandbox read-only

Language Protocol

Ask Codex in English and receive English back. The user-facing report follows AGENTS.md ## Language Protocol for language and .claude/rules/language.md ## Response Style for how that reply reads.

Codex Plugin Commands (codex-plugin-cc)

When the openai/codex-plugin-cc plugin is installed, these slash commands are available:

Plugin source: https://github.com/openai/codex-plugin-cc

Availability precondition: run /codex:setup first. Nothing in this repository verifies the plugin is installed, so if the commands are absent, use codex_consult.py instead of assuming a route exists. Audit-trail caveat: plugin commands run Codex outside the wrapper, so they produce no .claude/logs/codex/ response or stderr capture and no .claude/logs/cli-tools.jsonl entry (log-cli-tools.py keys on the wrapper filenames). Prefer the wrapper wherever both work, and note the gap when you use a plugin route for work that needs a record.

Code Review
bash
/codex:review                    # Review current uncommitted changes
/codex:review --base main        # Review branch diff against main
/codex:review --background       # Run review in background
/codex:review --wait             # Synchronous: block until review finishes
Adversarial Review
bash
/codex:adversarial-review                           # Challenge design decisions
/codex:adversarial-review --base main               # Branch-level adversarial review
/codex:adversarial-review --background look for race conditions
Task Delegation (Rescue)
bash
/codex:rescue investigate why the tests started failing
/codex:rescue fix the failing test with the smallest safe patch
/codex:rescue --resume apply the top fix from the last run
/codex:rescue --model gpt-5.5-mini --effort medium investigate flaky test
/codex:rescue --background investigate the regression
Job Management
bash
/codex:status                    # Check progress of background jobs
/codex:result                    # Show finished job output
/codex:cancel                    # Cancel active background job
Setup
bash
/codex:setup                     # Check if Codex is installed and authenticated
/codex:setup --enable-review-gate   # Enable auto-review gate (use with caution)
/codex:setup --disable-review-gate  # Disable review gate
When to Use Plugin vs Direct CLI
ScenarioUse
Pre-ship code review/codex:review
Challenge design/codex:adversarial-review
Delegate investigation/fix/codex:rescue
Background work + trackingPlugin --background
Ad-hoc design questioncodex_consult.py (direct)
Unrestricted implementationcodex_consult.py (the default) + Verify Before Trusting
Subagent delegationcodex_consult.py via general-purpose-opus
Consulting Claude Code or Antigravitycli_consult.py --cli {claude,antigravity}

Plugin routes (the first four rows) leave no wrapper log, no cli-tools.jsonl entry, and no record of which files they changed; the codex_consult.py routes leave all three. Whichever route made the change, an unrestricted run is verified the same way.

Why Codex?

  • Deep reasoning: Complex analysis and problem-solving
  • Planning expertise: Architecture and implementation strategies
  • Code mastery: Complex algorithms, optimization, debugging

References

Detailed templates and patterns in references/:

Also .claude/docs/CODEX_HANDOFF_PLAYBOOK.md — the handoff templates .claude/rules/codex-delegation.md points at, kept there because they are shared with non-Codex handoffs.

© DeL-TaiseiOzaki, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in .claude/skills/codex-system of DeL-TaiseiOzaki/claude-code-orchestra.

  • SKILL.md
  • references/agent-prompts.md
  • references/code-review-task.md
  • references/delegation-patterns.md
  • references/refactoring-task.md
  • references/troubleshooting.md

Open the folder on GitHubat commit ef0d8f8

Compare with similar skills

Codex System next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Codex System compared with similar skills
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Bug Finder for daisyUIsaadeghi/daisyui43k—~2.3kAutomated safety check: PassMIT
Root Cause Debugginggarrytan/gstack136k—~1.4kAutomated safety check: PassMIT
Graph-Based Bug Tracingtirth8205/code-review-graph32k1 repos~287Automated safety check: PassMIT
Systematic DebuggingChrisWiles/claude-code-showcase6.1k3 repos~1.2kAutomated safety check: PassNone

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Categories

Questions about Codex System

What does Codex System do?

Codex CLI handles planning, design, and complex code implementation. Codex System is an agent skill from DeL-TaiseiOzaki/claude-code-orchestra. Codex CLI handles planning, design, and complex code implementation.

When should I use Codex System?

Codex System fits situations like: : architecture design; implementation planning; complex algorithms; debugging (root cause analysis).

How do I install Codex System in Claude Code?

Run `npx skills add DeL-TaiseiOzaki/claude-code-orchestra --skill codex-system -a claude-code`. Or copy the skill folder (.claude/skills/codex-system in DeL-TaiseiOzaki/claude-code-orchestra) into .claude/skills/codex-system in your project. Claude Code loads it when a task matches its description.

How do I install Codex System in Codex?

Run `npx skills add DeL-TaiseiOzaki/claude-code-orchestra --skill codex-system -a codex`. Or copy the skill folder (.claude/skills/codex-system in DeL-TaiseiOzaki/claude-code-orchestra) into .agents/skills/codex-system in your project. Codex loads it when a task matches its description.

Can I use Codex System in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add DeL-TaiseiOzaki/claude-code-orchestra --skill codex-system -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/codex-system, .gemini/skills/codex-system, .github/skills/codex-system and .opencode/skills/codex-system in your project.

What does Codex System need to run?

Going by SKILL.md and its folder, Codex System needs the command-line tools its instructions call (python3, codex, bash, claude and npm). Our summary lists: Python 3; Node.js.

Does Codex System access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Codex System safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Codex System use?

Codex System is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Codex System use?

About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.6k tokens, read only when the agent opens those files.

What are the alternatives to Codex System?

Skills that share tags, products or a category with Codex System: OpenLogi macOS Permissions Triage (AprilNEA/OpenLogi, 23k stars), Bug Finder for daisyUI (saadeghi/daisyui, 43k stars), Root Cause Debugging (garrytan/gstack, 136k stars) and Graph-Based Bug Tracing (tirth8205/code-review-graph, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Codex System?

DeL-TaiseiOzaki (a GitHub user) maintains it in DeL-TaiseiOzaki/claude-code-orchestra, which has 199 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on September 20, 2026.

Source: DeL-TaiseiOzaki/claude-code-orchestra on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.