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-docsgit 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-docs)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-docs"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-docs/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-docs"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-docs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 30 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00082 | $0.01150 |
| Opus 5 | $0.00041 | $0.00575 |
| Sonnet 5 | $0.00016 | $0.00230 |
| Haiku 4.5 | $0.00008 | $0.00115 |
Grade A, and why
omh-docs 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 7d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OMH Docs
Use this skill to answer questions about OMH itself from current sources. It defaults to passive inspection; it is not a generic documentation writer, workflow picker, or settings workflow.
Default Behavior
- Classify the question as a public-product fact, a current-local-install fact, or both. Keep those claim sets separate in the answer.
- Retrieve only the sources needed for the question. Current public facts must
come from official
rlaope/oh-my-hermessources; current local facts must come from passive CLI output, or narrowly scoped non-secret metadata. If a diagnostic command records state, disclose that side effect before running it. - Disclose the source URL or command/path and the relevant ref, version, or commit. If freshness cannot be established or official sources conflict, name that boundary.
- Answer the one-shot question directly. Do not create a durable artifact unless the user requests one.
For a public catalog count, inspect the generated catalog on the current
official ref. For an installed count, run omh list --json and count only that
installation manifest. Never quote a remembered or embedded count.
Source Route
For public/product questions, start with live GitHub repository metadata and
the current default branch, then read the relevant current source. Load
references/product-and-sources.md for the full official-source hierarchy,
product identity, conflict handling, and disclosure shape.
For current capability and public skill-name questions, load
references/capability-map.md. It covers the six public capability families,
representative exact skill names, catalog retrieval, and the public ULW labels.
For model routing or this machine's installation, load
references/model-routing-and-local-state.md. It separates published routing
behavior from passive local inspection, the state-writing omh doctor --json
diagnostic, and safe inspection of the resolved OMH home (~/.omh by default,
but overridable).
What ships with it
4 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.
- 7d ago First seen · 119 lines · 82 tokens per session scan A 62387c1197d0
omh-docs is a skill published in the GitHub repository rlaope/oh-my-hermes (1,677 stars, last pushed today), licensed MIT. It adds 82 tokens to every session and 1,150 once invoked, about $0.0004 per session on Opus 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 2026-09-05.
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