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Found 52 Skills
Generate images with GPT Image 2 (ChatGPT Images 2.0) inside Claude Code, using your existing ChatGPT Plus or Pro subscription — no separate OpenAI access, no per-image billing. Supports text-to-image, image-to-image editing, style transfer, and multi-reference composition via the local Codex CLI. Triggers on "gpt image 2", "gpt-image-2", "ChatGPT Images 2.0", "image 2", or any explicit ask to generate or edit an image through the user's ChatGPT plan.
Plans.mdのタスクを実装。スコープを聞いて自動判断、1タスクから全タスクまで。Use when user mentions '/work', execute plan, implement tasks, build features, work on tasks, 'do everything', 'implement', '実装して', '全部やって', 'ここだけ'. Do NOT load for: planning, reviews, setup, deployment, or breezing (team execution).
Multi-agent orchestration layer for OpenAI Codex CLI. Provides 30 specialized agents, 40+ workflow skills, team orchestration in tmux, persistent MCP servers, and staged pipeline execution.
Automated code review workflow using OpenAI Codex CLI. Implements iterative fix-and-review cycles until code passes validation or reaches iteration limit. Use when building features requiring automated code validation, security checks, or quality assurance through Codex CLI.
This is intended for use when OpenSpec workflows require dependency-aware parallel subagents that are compatible with OPSX commands, legacy OpenSpec commands, and Codex CLI prompt aliases.
Debate implementation plans between Claude Code and Codex CLI. After Claude Code creates a plan, invoke this skill to have Codex review it. Both AIs debate through multiple rounds until reaching full consensus before implementation begins.
Setup and workflow for using sqry semantic code search as an MCP server with OpenAI Codex CLI. Covers installation, MCP configuration via `~/.codex/config.toml`, and recommended patterns for code analysis tasks. Install this skill to give Codex access to sqry's 34 AST-based code analysis tools.
Delegate coding, review, diagnosis, planning, structured output, and native browser research tasks to independent Codex sessions via Codex CLI. Use cases include creating new tasks with `codex exec`, resuming multi-turn sessions with `codex exec resume`, performing read-only reviews with `codex exec review`, as well as scenarios requiring `--json` event streams, `-o` final message persistence, image input, or Computer Use browser operations.
Use Codex CLI in full-auto mode to fix issues iteratively until tests pass. Autonomous debugging and test-fixing loop with sandbox safety.
Multi-instance (Multi-Agent) orchestration workflow for deep research: Split a research goal into parallel sub-goals, run child processes in the default `workspace-write` sandbox using Codex CLI (`codex exec`); prioritize installed skills for networking and data collection, followed by MCP tools; aggregate sub-results with scripts and refine them chapter by chapter, and finally deliver "finished report file path + key conclusions/recommendations summary". Applicable to: systematic web/data research, competitor/industry analysis, batch link/dataset shard retrieval, long-form writing and evidence integration, or scenarios where users mention "deep research/Deep Research/Wide Research/multi-Agent parallel research/multi-process research".
Run, watch, debug, and extend OpenClaw QA testing with qa-lab and qa-channel. Use when Codex needs to execute the repo-backed QA suite, inspect live QA artifacts, debug failing scenarios, add new QA scenarios, or explain the OpenClaw QA workflow. Prefer the live OpenAI lane with regular openai/gpt-5.4 in fast mode; do not use gpt-5.4-pro or gpt-5.4-mini unless the user explicitly overrides that policy.
OpenAI Codex CLI code review with GPT-5.2-Codex, CI/CD integration