oh-my-codex is a workflow layer for OpenAI Codex CLI that adds prompts, agent teams, skills, hooks, HUDs, and other runtime assistance while leaving Codex as the execution engine. It is for people who use Codex CLI and want structured workflows and additional help as tasks become larger. The catalogue entries are its skills, hooks, and MCP integrations for those Codex workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Yeachan-Heo/oh-my-codex --skill visual-ralphgit clone --depth 1 https://github.com/Yeachan-Heo/oh-my-codexWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yeachan-heo/oh-my-codex/visual-ralph)<a href="https://agentmods.dev/skills/yeachan-heo/oh-my-codex/visual-ralph"><img src="https://agentmods.dev/badge/skills/yeachan-heo/oh-my-codex/visual-ralph/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yeachan-heo/oh-my-codex/visual-ralph"><img src="https://agentmods.dev/badge/skills/yeachan-heo/oh-my-codex/visual-ralph.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00052 | $0.01159 |
| Opus 5.5 | $0.00021 | $0.00464 |
| Sonnet 5.5 | $0.00010 | $0.00232 |
| Haiku 4.5 | $0.00005 | $0.00116 |
Grade A, and why
visual-ralph scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Visual Ralph Skill
Use $visual-ralph for measured frontend implementation from an approved generated reference, static image, or live-URL baseline. The loop is:
description / URL -> approved reference -> $ultragoal implementation -> Visual Ralph verdict + pixel diff -> reusable design system.
For URL cloning, this skill owns the migrated $web-clone use case; preserve URL, viewport, fidelity, and interaction notes here. Do not invoke standalone $web-clone.
Shared operating, delegation, state, hook, team, cancellation, and verification invariants live in templates/AGENTS.md. Follow that source instead of duplicating its rules here.
Use when
- The user wants a web/app UI built or restyled against a visual target.
- A live URL or generated raster mockup needs measured implementation and pixel-level iteration.
- The result must leave reusable repo-native tokens/components, not only a matching screenshot.
Do not use it for a durable DESIGN.md brief ($design), non-visual backend work, comparison-only fixes that can be executed directly, or deterministic SVG/code-native assets.
Workflow
1. Ground the repository
Inspect package manager/scripts, frontend framework and routes, styling/token conventions, screenshot tooling, and reusable components. Choose stack-specific commands only when repository evidence supports them.
2. Establish a reference
For a live URL, capture or document an artifact containing source URL and permission/scope, viewport(s), route/state, seed/login assumptions, baseline screenshot path or capture command, visible-control parity notes, and exclusions (backend/API/auth, personalized data, crawling, third-party widgets).
For a generated concept, use $imagegen with classification ui-mockup, viewport/aspect ratio, surface, layout hierarchy, typography, color mood, exact text, no logos/watermarks/unrequested marks, and readable/feasible UI details. In OMX runtime, queue the continuation checkpoint before the built-in image tool:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · +2 tokens per session f18a5a686678
- 1mo ago First seen · 84 lines · 50 tokens per session scan A d2da6f86a297
visual-ralph is a skill published in the GitHub repository Yeachan-Heo/oh-my-codex (33,629 stars, last pushed today), licensed MIT. It adds 52 tokens to every session and 1,159 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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