Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing
npxskills add majiayu000/claude-skill-registry--skill codexLoading…
gpt-5.2 model. Ask the user (via AskUserQuestion) which reasoning effort to use (xhigh,high, medium, or low). User can override model if needed (see Model Options below).--sandbox read-only unless edits or network access are necessary.-m, --model <MODEL>--config model_reasoning_effort="<high|medium|low>"--sandbox <read-only|workspace-write|danger-full-access>--full-auto-C, --cd <DIR>--skip-git-repo-checkcodex exec --skip-git-repo-check resume --last via stdin. When resuming don't use any configuration flags unless explicitly requested by the user e.g. if he species the model or the reasoning effort when requesting to resume a session. Resume syntax: echo "your prompt here" | codex exec --skip-git-repo-check resume --last 2>/dev/null. All flags have to be inserted between exec and resume.2>/dev/null to all codex exec commands to suppress thinking tokens (stderr). Only show stderr if the user explicitly requests to see thinking tokens or if debugging is needed.| Use case | Sandbox mode | Key flags |
|---|---|---|
| Read-only review or analysis | read-only | --sandbox read-only 2>/dev/null |
| Apply local edits | workspace-write | --sandbox workspace-write --full-auto 2>/dev/null |
| Permit network or broad access | danger-full-access | --sandbox danger-full-access --full-auto 2>/dev/null |
| Resume recent session | Inherited from original |
| Model | Best for | Context window | Key features |
|---|---|---|---|
gpt-5.2-max | Max model: Ultra-complex reasoning, deep problem analysis | 400K input / 128K output | 76.3% SWE-bench, adaptive reasoning, $1.25/$10.00 |
gpt-5.2 ⭐ | Flagship model: Software engineering, agentic coding workflows | 400K input / 128K output | 76.3% SWE-bench, adaptive reasoning, $1.25/$10.00 |
gpt-5.2-mini | Cost-efficient coding (4x more usage allowance) | 400K input / 128K output | Near SOTA performance, $0.25/$2.00 |
gpt-5.1-thinking | Ultra-complex reasoning, deep problem analysis | 400K input / 128K output |
GPT-5.2 Advantages: 76.3% SWE-bench (vs 72.8% GPT-5), 30% faster on average tasks, better tool handling, reduced hallucinations, improved code quality. Knowledge cutoff: September 30, 2024.
Reasoning Effort Levels:
xhigh - Ultra-complex tasks (deep problem analysis, complex reasoning, deep understanding of the problem)high - Complex tasks (refactoring, architecture, security analysis, performance optimization)medium - Standard tasks (refactoring, code organization, feature additions, bug fixes)low - Simple tasks (quick fixes, simple changes, code formatting, documentation)Cached Input Discount: 90% off ($0.125/M tokens) for repeated context, cache lasts up to 24 hours.
codex command, immediately use AskUserQuestion to confirm next steps, collect clarifications, or decide whether to resume with codex exec resume --last.echo "new prompt" | codex exec resume --last 2>/dev/null. The resumed session automatically uses the same model, reasoning effort, and sandbox mode from the original session.codex --version or a codex exec command exits non-zero; request direction before retrying.--full-auto, --sandbox danger-full-access, --skip-git-repo-check) ask the user for permission using AskUserQuestion unless it was already given.AskUserQuestion.Requires Codex CLI v0.57.0 or later for GPT-5.2 model support. The CLI defaults to gpt-5.2 on macOS/Linux and gpt-5.2 on Windows. Check version: codex --version
Use /model slash command within a Codex session to switch models, or configure default in ~/.codex/config.toml.
echo "prompt" | codex exec --skip-git-repo-check resume --last 2>/dev/null (no flags allowed) |
| Run from another directory | Match task needs | -C <DIR> plus other flags 2>/dev/null |
| Adaptive thinking depth, runs 2x slower on hardest tasks |
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CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta Language).