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-content-operatorgit 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-content-operator)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-content-operator"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-content-operator/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-content-operator"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-content-operator.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 | $0.00094 | $0.01524 |
| Opus 5 | $0.00047 | $0.00762 |
| Sonnet 5 | $0.00019 | $0.00305 |
| Haiku 4.5 | $0.00009 | $0.00152 |
Grade A, and why
omh-content-operator 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 5d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Operator
This is a Hermes-native content-operator workflow skill.
Why This Exists
content-operator exists so Hermes users can ask for this workflow in chat and receive a structured, evidence-bounded OMH operating surface instead of ad hoc narration.
Do Not Use When
- The request is already handled by a narrower explicit skill with stronger evidence.
- The user asks OMH to secretly run external platforms, connectors, schedulers, file exports, or runtime agents.
- The only safe answer is to ask for missing authority, credentials, target, or observed evidence first.
Examples
Good example:
- Prompt: content-operator draft publish-ready release notes with audience, tone, source scope, review gates, and hallucination checks.
- Expected behavior: Produce
prepare_content_operator_cardwith required context, wrapper actions, and not-evidence boundaries. - Why: The prompt names a real workflow surface that Hermes can orchestrate without hiding execution.
Bad example:
- Prompt: content-operator invent missing facts and claim the customer announcement was sent.
- Expected behavior: Report the missing observed evidence or authority instead of claiming the external step happened.
- Why: Prepared OMH guidance is not platform, runtime, connector, file, memory, or delivery evidence.
Completion Checklist
- Audience, channel, language, tone, style guide, length, source scope, fact-risk, review owner, and stop condition are explicit.
- Missing facts, source gaps, claims needing citations, legal/compliance needs, approval, publish/send authority, and file-export needs are gated or marked missing.
- Published, sent, exported, approved, and fact-verified claims are reported only from observed evidence.
Recovery Notes
- If the request asks for citations, current facts, or source-backed evidence gathering, route to research or source-finder before drafting.
- If the request asks to send, post, invite, ticket, or mutate an external app, route to connector-operator before claiming delivery.
- If the request asks for PDF, PPT, DOCX, HWP, spreadsheet, or attachment packaging, route to materials-package or deliverable-package.
- If the request is a simple one-off sentence or paragraph transformation, answer directly instead of opening a workflow.
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.
- 5d ago Changed 691331e56b0a
- 7d ago Changed dd4ee194a72c
- 11d ago First seen · 130 lines · 94 tokens per session scan A 57cf048b9410
omh-content-operator is a skill published in the GitHub repository rlaope/oh-my-hermes (1,648 stars, last pushed today), licensed MIT. It adds 94 tokens to every session and 1,524 once invoked, about $0.0005 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 2026-08-30.
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