oh-my-hermes is an operating layer for Hermes Agent that organizes requests into workflows for planning, research, creation, coding handoffs, operations, and project memory. Hermes users run these workflows through the desktop app, CLI, or messenger app, while the catalogue add-ons extend its native capabilities.
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 rlaope/oh-my-hermes --skill omh-code-reviewgit clone --depth 1 https://github.com/rlaope/oh-my-hermesWrote 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/rlaope/oh-my-hermes/omh-code-review)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-code-review"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-code-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/rlaope/oh-my-hermes/omh-code-review"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-code-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 | $0.00048 | $0.02206 |
| Opus 5.5 | $0.00019 | $0.00882 |
| Sonnet 5.5 | $0.00010 | $0.00441 |
| Haiku 4.5 | $0.00005 | $0.00221 |
Grade A, and why
omh-code-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 2d 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
This is an OMH code-review workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
Why This Exists
code-review exists to make review bug-first and evidence-grounded: findings must cite concrete files, diffs, commands, or artifacts before any summary or fix proposal.
Do Not Use When
- The user asks to implement the fix rather than review existing code or claims.
- There is no diff, file set, claim, artifact, or expected behavior to review.
- The request is broad product critique, strategy, or planning rather than code or evidence review.
Examples
Good example:
- Prompt: $code-review review this PR for install/update UX regressions and missing tests.
- Expected behavior: Lead with ranked findings, cite concrete evidence, then list open questions and test gaps.
- Why: The task is explicitly review-shaped and has a behavioral risk surface.
Bad example:
- Prompt: $code-review add the missing setup flag and commit it.
- Expected behavior: Route implementation to a selected executor/runtime after review findings are established.
- Why: Review can identify the issue, but code mutation is a separate execution step.
Completion Checklist
- Findings come first: rank ordinary findings by severity; keep gaps unranked in
verification_gaps. - Every finding cites file, diff, command output, artifact, or expected behavior evidence.
- Both axes appear in the report: correctness/risk findings, and a spec-axis verdict naming its Claim source or the
not_assessedreason. - No-issue reviews still name residual risk, missing tests, and independent review evidence if unavailable.
- The closing carries the checked-and-clean list and the could-not-assess list, each naming its surfaces.
- The dispatch schema matches the return, candidate validation states remain distinct, and selected checks are not reported as observed coverage.
- Fix implementation, architecture follow-up, and CI/merge claims stay separate from the review result.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago Changed cbc93cae9212
- 3d ago Changed · +5 lines b70a4f9dc50b
- 4d ago Changed 05b6b799c130
- 6d ago Changed 27ea9fee9832
- 11d ago Changed 63a841359ae8
- 12d ago Changed · +1 lines f7350eadafcb
- 24d ago Changed · +1 lines 64a62cd6c7e6
- 26d ago Changed · +3 lines 07c554deb7df
- 1mo ago Changed · +2 tokens per session c05a6ed92db3
- 1mo ago First seen · 133 lines · 46 tokens per session scan A 46393359af8f
omh-code-review is a skill published in the GitHub repository rlaope/oh-my-hermes (4,206 stars, last pushed today), licensed MIT. It adds 48 tokens to every session and 2,206 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.
Other skills, from other repositories
nlpm-audit
Audit SKILL.md, AGENTS.md, prompts, hooks, and plugin manifests for instruction conflicts, quality, broken references, and manifest-to-disk drift.
api-design-reviewer
Use when reviewing API designs for consistency, usability, versioning, error semantics, security, backward compatibility, and developer experience before implementation or release.
pr-review-expert
Review GitHub PRs or GitLab MRs for correctness, security, compatibility, and affected test coverage, with actionable evidence tied to the diff.
improve-codebase-architecture
Review module boundaries, interface depth and high-leverage refactors with evidence.
gh-address-comments
Use when addressing GitHub PR review comments or issue comments on the current branch with gh CLI, including auth checks, comment triage, edits, verification, and replies.
doubt-driven-development
Review high-risk or uncertain engineering decisions adversarially when independent verification can expose costly assumptions before implementation.