Awesome-omni-skill codex

Use the OpenAI Codex CLI (codex exec) as a coding agent for writing code, debugging, code review, and automated refactoring. Always runs with high reasoning effort for maximum depth.

install
source · Clone the upstream repo
git clone https://github.com/diegosouzapw/awesome-omni-skill
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/development/codex-nmotlagh" ~/.claude/skills/diegosouzapw-awesome-omni-skill-codex-e31d00 && rm -rf "$T"
manifest: skills/development/codex-nmotlagh/SKILL.md
source content

Codex CLI Skill

Use the OpenAI Codex CLI to delegate coding tasks that benefit from fast, focused code generation, debugging, and review.

When to Use Codex

  • Code review — reviewing diffs, files, or modules for bugs and edge cases
  • Writing new functions or modules where requirements are clear
  • Debugging — Codex has found nuanced bugs that are easy to miss
  • Targeted refactors — renaming, restructuring single files or small groups
  • Boilerplate generation — tests, config files, repetitive patterns

When NOT to Use Codex

  • Tasks requiring multi-file architectural reasoning across the whole repo
  • Interactive exploration or codebase understanding (use Claude directly)
  • Tasks that need internet access on an airgapped cluster
  • When Codex is not installed (
    which codex
    returns nothing)

Installation

npm i -g @openai/codex

Requires Node.js 20+. Authenticate on first run (ChatGPT Plus/Pro/API key).

Required Flags

Every invocation MUST include these flags:

FlagValueWhy
--full-auto
(no value)Non-interactive, no approval prompts
-m
gpt-5.3-codex
Best model for code reasoning
-c
reasoning_effort="high"
Maximum depth for catching subtle bugs

Core Usage

Non-Interactive Execution

# Basic task
codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" "your task here"

# Set working directory
codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  -C ~/binom-abstain "your task here"

# Read prompt from stdin
echo "fix the failing test in tests/test_eval.py" | codex exec --full-auto \
  -m gpt-5.3-codex -c reasoning_effort="high" -

# Save output to file
codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  -o result.md "explain what src/train/sft.py does"

Code Review Patterns

Quick Diff Review

Review only what changed — fast, focused.

codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  "Review the uncommitted changes. Look for bugs, edge cases, and correctness issues."

Deep File Review

Review an entire file for latent bugs, not just recent changes.

codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  "Do a thorough review of src/pipeline/run_pipeline.py. Check for bugs, race conditions, and edge cases."

Read-Only Review (No Edits)

Use

--sandbox read-only
to ensure Codex only reads and reports, never modifies files.

codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  -s read-only \
  "Review src/train/sft.py. Report issues but do not modify any files."

Multi-File Module Review

codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  "Review all files in src/eval/ for correctness and consistency."

Staged / PR Review

# Review staged changes (pre-commit)
codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  "Review the staged git changes. Flag any issues before I commit."

# Review a PR diff against main
codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  "Review the diff between main and HEAD. Summarize changes and flag problems."

Debugging Patterns

# Point Codex at a failing test
codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  "the test tests/test_sft.py::test_lora_training is failing. diagnose and fix the bug."

# Focused debugging on a specific issue
codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  "Review src/sampling/generate.py focusing on OOM risks and GPU memory usage."

Writing & Refactoring Patterns

# Implement a new function
codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  "Implement function X that does Y. File: src/module/file.py"

# Targeted refactor
codex exec --full-auto -m gpt-5.3-codex -c reasoning_effort="high" \
  "Refactor src/train/sft.py to extract the data loading into a separate function."

All Flags Reference

FlagShortDescription
--model
-m
Model to use (always
gpt-5.3-codex
)
--full-auto
No approvals, workspace-write sandbox
--config
-c
Inline config (e.g.,
reasoning_effort="high"
)
--cd
-C
Set working directory
--output-last-message
-o
Write final response to file
--sandbox
-s
read-only
,
workspace-write
,
danger-full-access
--ask-for-approval
-a
untrusted
,
on-failure
,
on-request
,
never
--image
-i
Attach screenshot/image to prompt
--json
Emit newline-delimited JSON events
--skip-git-repo-check
Run outside a git repo
--search
Enable live web search

Resuming Sessions

codex exec resume --last        # Most recent session
codex exec resume <SESSION_ID>  # Specific session

Guidelines

  • Always verify Codex is installed first:
    which codex
  • Always use
    high
    reasoning — research code demands maximum scrutiny
  • Use
    --sandbox read-only
    when you only want a report, not fixes
  • Use
    -o review.md
    to capture reviews for later reference
  • Break large tasks into focused chunks (one module or file group at a time)
  • After Codex makes changes, run
    python -m pytest tests/ -v
    to verify
  • Review Codex output before committing — it may introduce subtle issues in unfamiliar codebases
  • Codex cannot access the internet — it works only with local files