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Found 480 Skills
Manage MCP servers in Codex quickly and safely. Use this skill when the user asks to add, update, remove, inspect, or troubleshoot MCP servers, especially from a GitHub URL. The skill enforces scope selection (project `./.codex/config.toml` vs global `~/.codex/config.toml`), checks for existing entries, and asks the user to choose required options before making changes.
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".
Bridge between Claude Code and OpenAI Codex CLI - generates AGENTS.md from CLAUDE.md, provides Codex CLI execution helpers, and enables seamless interoperability between both tools
Diagnose and fix errors with Codex delegation. Traces error to root cause, researches approach, delegates fix, verifies. Use when: bug reports, error messages, stack traces, test failures.
Run OpenAI's Codex CLI agent in non-interactive mode using `codex exec`. Use when delegating coding tasks to Codex, running Codex in scripts/automation, or when needing a second agent to work on a task in parallel.
Use this skill for multi-model AI code review. Trigger whenever the user asks to review code changes, audit a diff, check code quality, review a PR, review commits, or review uncommitted changes before pushing or merging. Also trigger when they say 'code review', 'review my changes', 'check this before I merge', or want multiple perspectives on code. Runs Codex and Claude reviews in parallel, then synthesizes a unified report. Do NOT use for reviewing documentation, markdown, or non-code files, or for trivial single-line changes.
Analyze a project's past Codex sessions, memory files, and existing local skills to recommend the highest-value skills to create or update. Use when a user asks what skills a project needs, wants skill ideas grounded in real project history, wants an audit of current project-local skills, or wants recommendations for updating stale or incomplete skills instead of creating duplicates.
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.
Create, repair, validate, preview, and package Codex-compatible animated pet spritesheets from character art, screenshots, generated images, or visual references. Use when a user wants to hatch a Codex pet, create a custom animated pet, or build a built-in pet asset with an 8x9 atlas, transparent unused cells, row-by-row animation prompts, QA contact sheets, preview videos, and pet.json packaging. This skill composes the installed $imagegen system skill for visual generation and uses bundled scripts for deterministic spritesheet assembly.
Summarize Codex token usage from local Codex Desktop or CLI session JSONL logs. Use when the user asks to count, audit, total, compare, or report Codex/OpenAI token usage for a period such as today, this week, last month, a calendar month, a rolling 30-day window, peak week, peak day, input/output/cached/reasoning breakdown, or net token usage.
Count the Tokens consumed by the local Codex in recent time by task purpose dimension, and output a Chinese table including model and category proportions; output the Faster x2 status only when explicit session-level fields exist.
Delegate a coding task to the OpenAI Codex CLI as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Codex — phrasings like "have Codex do X", "delegate this to Codex", "run it through Codex", or "use Codex to implement/fix/refactor" — or wants to run a queue of coding tasks through Codex while staying the reviewer. Prefer it over a one-shot Codex forwarder (such as the codex-rescue agent) specifically when the user will review the resulting diff and commit it themselves, or wants the full brief → dispatch → review → commit loop across a single task or a queue. Also reach for it proactively for a separate implementation pass on a bounded, well-specified task (an implementation sweep, a migration, a mechanical refactor, parallel work). Covers writing the Codex brief, dispatching it via the bundled relay.mjs helper, waiting for completion, reviewing the result, and committing. DO NOT USE for tasks small enough to do inline, or when the user wants the code written directly without delegating.