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-skill-healthgit 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-skill-health)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-skill-health"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-skill-health/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-skill-health"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-skill-health.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 | $0.00072 | $0.01210 |
| Opus 5 | $0.00036 | $0.00605 |
| Sonnet 5 | $0.00014 | $0.00242 |
| Haiku 4.5 | $0.00007 | $0.00121 |
Grade A, and why
omh-skill-health 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Health
This is a Hermes-native skill-health workflow skill.
Why This Exists
skill-health 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: skill-health show the OMH skill portfolio dashboard with stale surfaces, failure patterns, pending amendments, and top improvement actions.
- Expected behavior: Produce
prepare_skill_healthwith 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: skill-health claim every skill is working and patch the failures automatically without observed signals or 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
- Dashboard scope, source surfaces, stale/duplicate criteria, and stop condition are explicit.
- Install/setup health is routed to doctor; catalog operations are routed to skill; failure retrospectives are routed to workflow-learning.
- No skill, prompt, doc, memory, or model behavior is claimed changed until a reviewed implementation records evidence.
Recovery Notes
- If the request is about OMH setup, install, stale package paths, or command availability, route to doctor.
- If the request is a missed-route or self-improvement trace, route to workflow-learning before adding health actions.
Workflow Lane
- Current lane: Automation and status (
achievements,workspace-audit,production-audit,automation-blueprint,github-event-ops,github-issue-intake,buzz,agent-board,+35 more) - schedules, status, health, and ops review. - If intent belongs to another lane, hand back to
oh-my-hermesor name the adjacent workflow. - Shared product, routing, compatibility, and evidence rules:
omh-routing/references/skill-common-rail.md.
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 e8d8416fada0
- 9d ago First seen · 120 lines · 72 tokens per session scan A 582ee3195c3d
omh-skill-health is a skill published in the GitHub repository rlaope/oh-my-hermes (1,677 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 1,210 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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