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-production-auditgit 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-production-audit)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-production-audit"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-production-audit/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-production-audit"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-production-audit.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 | $0.00071 | $0.01360 |
| Opus 5.5 | $0.00028 | $0.00544 |
| Sonnet 5.5 | $0.00014 | $0.00272 |
| Haiku 4.5 | $0.00007 | $0.00136 |
Grade A, and why
omh-production-audit 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Production Audit
This is an OMH production-audit workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
Why This Exists
production-audit gives OMH a preflight release surface so operators can see production risks before launch while OMH stays out of deploy and infrastructure execution.
Do Not Use When
- The user wants to implement a feature or fix; prepare a coding handoff first.
- The user wants incident/SLO analysis after production behavior; use
omh-reliability-review. - The user wants a narrow code diff review; use
omh-code-review.
Examples
Good example:
- Prompt: production-audit 이 릴리즈가 운영에 나가도 되는지 테스트, CI, 롤백, 모니터링 기준으로 봐줘.
- Expected behavior: Prepare readiness_matrix/v1, release_gate_verdict/v1, rollback_and_monitoring_plan/v1, and missing-evidence list.
- Why: The request is release-readiness review, not implementation or deploy execution.
Bad example:
- Prompt: production-audit 지금 바로 prod 배포하고 정상이라고 말해줘.
- Expected behavior: Block deploy/health claims without observed operator evidence and route deploy to an explicit authorized workflow.
- Why: Production audit can assess readiness, but it cannot secretly deploy or observe live health.
Completion Checklist
- Findings or no-issue results are grounded in concrete file, artifact, command, or source evidence.
- Open questions, residual risk, and missing verification are named.
- Fixes or follow-up work are separate handoffs unless the user explicitly asked to implement them.
Recovery Notes
- If the reviewed target is missing, inspect the requested artifact or ask one target question.
- If independent verification is unavailable, report the gap and avoid an approval-style claim.
When to Use
Use before launch, deploy, release, or public delivery when Hermes should check operational readiness and expose missing production evidence.
Strong routing signals: `production-audit`, `production audit`, `production readiness`, `prod audit`, `prod readiness`, `ready for production`, `ready to ship`, `ship readiness`, `release readiness`, `launch readiness`, `preflight audit`, `operational readiness`, `rollback readiness`, `프로덕션 준비`, `출시 준비`, `운영 준비`, `릴리즈 준비`, `롤백 준비`
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 · +1 lines 22e263ea6b90
- 14d ago Changed · +1 lines 8ccb54ef5417
- 27d ago Changed · +3 lines b356a71f3997
- 1mo ago Changed · +3 tokens per session b80808e4f43c
- 1mo ago Changed · +6 lines ec5da405340d
- 1mo ago Changed · -11 lines 5547ba0eb367
- 1mo ago Changed 596c28ec4c36
- 1mo ago First seen · 133 lines · 68 tokens per session scan A ebeba7538da4
omh-production-audit is a skill published in the GitHub repository rlaope/oh-my-hermes (4,366 stars, last pushed today), licensed MIT. It adds 71 tokens to every session and 1,360 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
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ci-cd-and-automation
Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.
gha-security-review
Audit GitHub Actions workflows for unsafe triggers, expression injection, credential exposure, and supply-chain attack paths.
pipe
Designing GitHub Actions workflows in depth: trigger strategy, security hardening, performance optimization, PR automation, and Reusable Workflow design.
gh-fix-ci
Inspect and fix failing GitHub Actions PR checks using gh logs and focused validation; report external-provider failures with their details URL.
baby-sit
Monitor a GitHub pull request until CI is green, diagnose failures, and rerun only evidence-backed flaky GitHub Actions jobs.