Oh My Claude Code is a multi-agent orchestration system for Claude Code, coordinating specialized agents, commands, skills, hooks, and workflows. It is designed for developers who want Claude Code to handle coding tasks through coordinated agent roles. Catalogue entries are components of its Claude Code workflow, including agents, commands, skills, hooks, instructions, MCP configuration, and a plugin.
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-claudecode --skill reviewgit clone --depth 1 https://github.com/Yeachan-Heo/oh-my-claudecodeWrote 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-claudecode/review)<a href="https://agentmods.dev/skills/yeachan-heo/oh-my-claudecode/review"><img src="https://agentmods.dev/badge/skills/yeachan-heo/oh-my-claudecode/review/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-claudecode/review"><img src="https://agentmods.dev/badge/skills/yeachan-heo/oh-my-claudecode/review.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 | $0.00018 | $0.00607 |
| Opus 5.5 | $0.00007 | $0.00243 |
| Sonnet 5.5 | $0.00004 | $0.00121 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
omc-review 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 8d 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- omc-review — 100% identical, 13 lines differ
- omc-review — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review
Use this skill to evaluate work that already exists. Review never authors the change it is judging.
This is the canonical review workflow. ai-slop-cleaner is an opt-in lane
within it.
Goal
Find what is actually wrong, ranked by severity, with enough detail to act on.
Workflow
- Establish what changed and what it was meant to do.
- Read the change against that intent.
- Check correctness first, then risk, then simplification.
- Verify each candidate finding before reporting it.
- Report findings most-severe first.
What to check
- Correctness — logic defects, edge cases, error paths, concurrency
- Risk — security boundaries, destructive operations, data integrity
- Reuse — existing utilities or patterns the change should have used
- Simplification — code that could be deleted or collapsed
- Coverage — behavior that ships untested
Two axes, run apart
A substantial diff is reviewed as two parallel sub-agent passes, reported separately — never merged or cross-ranked, because a change can pass one axis and fail the other (standards-conforming but wrong behavior; faithful but convention-breaking):
- Standards axis — the diff against the repo's documented standards plus a judgement-call-only smell baseline; anything tooling already enforces is skipped. The standards set is discovered, not assumed: search the repo for standards documents (CLAUDE.md/AGENTS.md,
docs/standards/volumes,CONTRIBUTING.md,CODING_STANDARDS.mdor equivalents) and review against whatever exists — a standards file you didn't look for is a standard you didn't apply. - Intent axis — the diff against what the work was meant to do — the task, spec, or ticket acceptance criteria: requirements missing or partial, behavior nobody asked for, each finding quoting its source line.
Keep each sub-agent brief under ~400 words and pointed at one axis. Aggregate without picking a single winner across axes — that reranking is what the separation exists to prevent; state each axis's verdict on its own. A small diff stays one pass.
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.
- 8d ago Changed cd0e59528084
- 14d ago Changed 000e40d548ec
- 25d ago Changed · +9 lines c262bb3fe050
- 1mo ago First seen · 43 lines · 18 tokens per session scan A 9ea9e7e3ec29
omc-review is a skill published in the GitHub repository Yeachan-Heo/oh-my-claudecode (40,298 stars, last pushed today), licensed MIT. It adds 18 tokens to every session and 607 once invoked, about $0.0001 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 2026-09-03.
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