codex
Invoke Codex CLI for complex coding tasks requiring high reasoning capabilities. Trigger phrases include "use codex", "ask codex", "run codex", "call codex", "codex cli", "GPT-5 reasoning", "OpenAI reasoning", or when users request complex implementation challenges, advanced reasoning, architecture design, or high-reasoning model assistance. Automatically triggers on codex-related requests and supports session continuation for iterative development.
npx skills add majiayu000/claude-skill-registry --skill codex-alchimie-di-circe-extractor-desktop-ap-2 --agent codex
Same command for any agent — swap --agent for claude-code, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Implements a Codex-based assistant that routes requests to a code-focused or general task model, and enforces the non-interactive codex exec workflow for all invocations. It supports explicit edit semantics to switch sandbox modes, session continuation, and a fallback model chain for availability.
How it works
- Detects whether the task is code-related or general and selects the appropriate Codex model: use gpt-5.2-codex for code tasks, or gpt-5.2 for general tasks. Fallbacks exist (gpt-5.2 → gpt-5.1 → gpt-5.1-codex-max or gpt-5.1).
- Enforces non-interactive execution via codex exec for all invocations; interactive codex is explicitly prohibited.
- Uses a sandbox model: default read-only; switch to workspace-write only when the user explicitly requests editing (e.g., phrases like edit/modify/write).
- Defaults include model_reasoning_effort=xhigh and web_search_request enabled; supports explicit edit prompts to grant workspace-write access.
- Provides a structured CLI command pattern for code tasks and general tasks, with explicit examples illustrating read-only vs. edit modes.
- Includes a session continuation workflow: resume using codex exec resume --last or by session-id, with guidance on when to start fresh vs continue.
When to use it
Use this skill when the user explicitly mentions Codex or requests high-reasoning coding help, architecture design, or iterative development requiring Codex collaboration. It should trigger for complex implementation challenges or requests for advanced model reasoning and continued Codex sessions.
What it can touch
- Commands and tools:
codex execandcodex resume. - Models:
gpt-5.2-codex,gpt-5.2,gpt-5.1-codex-max,gpt-5.1. - Sandbox modes:
read-only,workspace-write. - Configuration:
model_reasoning_effort(e.g., xhigh),model_verbosity,--enable web_search_request.
Caveats
- Requires Codex CLI v0.71.0+ and appropriate subscription.
- Interactive mode with
codexis not allowed; must usecodex execfor non-interactive automation. - Some flags available only in interactive mode may not be usable in exec mode; use provided alternatives where applicable.
- Default reasoning effort is set to xhigh for maximum capability.
# Codex: High-Reasoning AI Assistant for Claude Code --- ## DEFAULT MODEL: Task-Based Model Selection with Read-Only Default **Codex uses task-based model selection. Sandbox is `read-only` by default - only use `workspace-write` when user explicitly requests file editing.** | Task Type | Model | Sandbox (default) | Sandbox (explicit edit) | |-----------|-------|-------------------|------------------------| | Code-related tasks | `gpt-5.2-codex` | read-only | workspace-write | | General tasks | `gpt-5.2` | read-only | workspace-write | - **Code-related tasks**: Use `gpt-5.2-codex` - optimized for agentic coding (56.4% SWE-Bench Pro) - **General tasks**: Use `gpt-5.2` - high-reasoning general model - **Sandbox default**: Always `read-only` unless user explicitly requests editing - **Explicit editing**: Only when user says "edit", "modify", "write changes", etc., use `workspace-write` - Always use `-c model_reasoning_effort=xhigh` for maximum capability ```bash # Code task (read-only default) codex exec -m gpt-5.2-codex -s read-only \ -c model_reasoning_effort=xhigh \ "analyze this function implementation" # General task (read-only default) codex exec -m gpt-5.2 -s read-only \ -c mode
- DEFAULT MODEL: Task-Based Model Selection with Read-Only Default
- Model Fallback Chain
- CRITICAL: Always Use codex exec
- IMPORTANT: Interactive vs Exec Mode Flags
- Trigger Examples
- When to Use This Skill
- How It Works
- Detecting New Codex Requests
- Bash CLI Command Structure
- Model Selection Logic
- Default Configuration
- CLI Flags Reference
- Configuration Parameters
- Model Selection Guide
Code task (read-only default) codex exec -m gpt-5.2-codex -s read-only \ General task (read-only default) codex exec -m gpt-5.2 -s read-only \ Code task with explicit edit request codex exec -m gpt-5.2-codex -s workspace-write \ General task with explicit edit request codex exec -m gpt-5.2 -s workspace-write \ CORRECT - works in codex exec codex exec --enable web_search_request "research topic"
What does the codex skill do?
Invoke Codex CLI for complex coding tasks requiring high reasoning capabilities. Trigger phrases include "use codex", "ask codex", "run codex", "call codex", "codex cli", "GPT-5 reasoning", "OpenAI reasoning", or when users request complex implementation challenges, advanced reasoning, architecture design, or high-reasoning model assistance. Automatically triggers on codex-related requests and supports session continuation for iterative development.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill codex-alchimie-di-circe-extractor-desktop-ap-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.
