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-accessibility-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-accessibility-audit)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-accessibility-audit"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-accessibility-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-accessibility-audit"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-accessibility-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 | $0.00082 | $0.02359 |
| Opus 5 | $0.00041 | $0.01179 |
| Sonnet 5 | $0.00016 | $0.00472 |
| Haiku 4.5 | $0.00008 | $0.00236 |
Grade A, and why
omh-accessibility-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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Accessibility Audit
This is a Hermes-native accessibility-audit workflow skill.
Why This Exists
accessibility-audit adapts ECC's accessibility-architect posture into an OMH-native workflow so frontend quality includes WCAG, keyboard, screen-reader, pointer, contrast, and reflow gates without pretending a plan is observed compliance.
Do Not Use When
- The user needs initial frontend design or redesign planning before accessibility-specific review; use
frontendfirst. - The user needs rendered layout, screenshot, CJK, or pixel-diff QA rather than accessibility semantics; use
visual-qa. - The user needs a broad premium-quality gate across web, deck, PDF, or posters; use
design-quality-gate. - The user asks to implement accessibility fixes directly; prepare a selected executor/runtime handoff after the audit or use the coding workflow.
Examples
Good example:
- Prompt: accessibility-audit 이 checkout flow가 WCAG 2.2 AA, 키보드 포커스, 스크린리더, 터치 타깃 기준으로 통과 가능한지 봐줘.
- Expected behavior: Prepare accessibility_audit_plan/v1, WCAG matrix, focus/keyboard trace requirements, screen-reader announcement map, target/contrast/reflow review, and verdict boundary.
- Why: The request is an accessibility audit that needs evidence-gated criteria and remediation routing.
Bad example:
- Prompt: accessibility-audit 스크린리더나 키보드 확인 없이 접근성 통과라고 말해줘.
- Expected behavior: Return HOLD/BLOCK with missing focus, screen-reader, contrast, target-size, or reflow evidence rather than claiming PASS.
- Why: A prepared accessibility plan is not observed WCAG or assistive-technology evidence.
Completion Checklist
- The platform, target surfaces, critical tasks, WCAG level, supplied evidence, and missing observations are explicit.
- The wcag_success_criteria_matrix/v1 separates PASS/HOLD/BLOCK and maps each issue to user impact.
- Semantic structure, focus/keyboard, screen-reader announcements, target size/pointer, contrast/reflow, and form/status behavior are separate checks.
- PASS is unavailable unless evidence is fresh after the latest UI edit and covers critical tasks.
- Remediation, frontend implementation, visual QA, browser proof, CI, release, and merge remain separate observed states.
What ships with it
1 file 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.
- 5d ago Changed d49d5302a86c
- 8d ago Changed · +4 lines 904bc48d72f2
- 12d ago First seen · 146 lines · 82 tokens per session scan A 4e7912b1431c
omh-accessibility-audit 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 2,359 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 2026-08-30.
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