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-prompt-import-readinessgit 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-prompt-import-readiness)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-prompt-import-readiness"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-prompt-import-readiness/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-prompt-import-readiness"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-prompt-import-readiness.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 System Prompt Leakage · line 64 Skill contains patterns that could indirectly extract system prompts through rephrasing, translation, summarization, or side-channel techniques.Fix: Guard against indirect extraction by refusing to summarize, translate, or rephrase system instructions. Add explicit anti-extraction clauses.
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 | $0.00089 | $0.01708 |
| Opus 5 | $0.00044 | $0.00854 |
| Sonnet 5 | $0.00018 | $0.00342 |
| Haiku 4.5 | $0.00009 | $0.00171 |
Grade A, and why
omh-prompt-import-readiness 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Import Readiness
This is a Hermes-native prompt-import-readiness workflow skill.
Why This Exists
prompt-import-readiness 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: prompt-import-readiness review Codex and Claude Code prompt folders before exposing them as Hermes slash commands with $ARGUMENTS mapping.
- Expected behavior: Produce
prepare_prompt_import_readinesswith 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: prompt-import-readiness silently import every external prompt, overwrite slash commands, and claim the prompts are trusted without review.
- 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
- Prompt sources, agent family, expected file formats, argument syntax, slash-command names, trust level, and stop condition are explicit.
- Explicit-path audit reads and compatibility results are observed only in their audit output; source discovery, command registration, prompt mutation, slash-command activation, and dry-run execution remain marked not_observed.
- Route broad candidate discovery to skill-scout, prompt/tool safety to security-safety-review, missing CLIs or directories to toolbelt-readiness, and approved implementation to a selected executor handoff.
- Imported prompts, generated command files, registry updates, and dry-run results are reported only from observed prompt-import evidence.
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 Changed 2322f01ba377
- 9d ago First seen · 136 lines · 89 tokens per session scan A 909fd395f462
omh-prompt-import-readiness is a skill published in the GitHub repository rlaope/oh-my-hermes (1,677 stars, last pushed today), licensed MIT. It adds 89 tokens to every session and 1,708 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 2026-09-03.
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