Skill UI

This tool manages isolated profiles for Codex CLI and Codex Desktop, ensuring that different accounts, projects, and local states do not interfere with each other. It provides dedicated CODEX_HOME directories, allowing users to securely switch contexts (e.g., work, personal, client) on a single machine without manual environment variable management.

Professional code review integrated with Codex AI that inspects changes before commits and automatically generates CHANGELOG entries matching the actual diff.

This skill enables launching OpenAI's Codex CLI as an isolated subagent for bounded coding, review, or verification tasks. It runs non-interactively in a sandbox, streaming progress while keeping context separate. Ideal for parallel work, independent verification, and self-contained coding tasks with clear success criteria. Users must ensure authentication and handle file ownership explicitly.

Delegates coding and analysis tasks from Claude Code to OpenAI Codex CLI or Google Antigravity CLI, maintains topic-aware sessions, and critiques returned results.

This guide details the comprehensive workflow for distributing a single AI skill across various local agent skill directories (Codex, Claude, Pi, Hermes). It addresses canonical locations, symlink management, and specific synchronization commands to ensure that all agents detect the latest skill version while correctly navigating common development pitfalls.

This skill helps developers create highly focused, folder-specific documentation (`CLAUDE.md` and `AGENTS.md`). It systematically analyzes all files in a target directory to extract project purpose, operational constraints, naming conventions, and critical decisions. This deep context ensures that future AI agents (like Claude or Codex) operate with localized knowledge, preventing them from relying on global, generalized instructions and improving their accuracy in that specific domain.

Maintain a review-first engineering wiki with provenance, citation-aware queries, explicit capture and promotion, and deterministic checks. Helps teams capture durable lessons and verify knowledge before turning it into rules.

Open Dynamic Workflows (ODW) is an advanced, open-source engine designed to manage complex coding tasks using multiple AI agents. It operates in three stages: planning the task into parallel subtasks, orchestrating various coding agents (like Codex or Antigravity) to work concurrently, and finally, performing an adversarial verification pass to challenge and validate the combined output before merging. It supports multiple model providers and is ideal for structured, high-reliability software development.

This skill provides comprehensive diagnosis and optimization for agent skill libraries. By analyzing historical session transcripts from platforms like Claude Code and Codex, alongside static skill file checks, it scores each skill across 8 dimensions. It identifies issues such as low trigger rates, poor post-invocation user reaction, and incomplete workflow execution, generating a prioritized report (P0/P1/P2) to significantly improve the agent's overall performance and reliability.

A Python utility to preview conservative tool-name translations and copy complete local skill bundles for manual adaptation to Google Antigravity. Supports Claude Code, Cursor, Codex, and generic agent skill directories. Ensures safe migration with dry-run modes and workspace installation.

Freezes PRD, technical design, and acceptance criteria before medium-to-large Codex work, then coordinates multiple agents with explicit file ownership and judges delivery from diffs, tests, and evidence-backed acceptance.

Vexor is a command-line interface tool that utilizes vector embeddings to perform semantic file searches. It is designed to enhance workflow efficiency by allowing users to query files based on meaning rather than keywords, particularly when integrated with AI models like Claude or Codex. Ideal for developers needing context-aware file retrieval within codebases or documentation.