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-media-inputgit 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-media-input)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-media-input"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-media-input/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-media-input"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-media-input.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 | $0.00084 | $0.01817 |
| Opus 5 | $0.00042 | $0.00908 |
| Sonnet 5 | $0.00017 | $0.00363 |
| Haiku 4.5 | $0.00008 | $0.00182 |
Grade A, and why
omh-media-input 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 2d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Media Input Operator
This is a Hermes-native media-input-operator workflow skill.
Why This Exists
media-input-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: media-input-operator transcribe this audio meeting and summarize action items with evidence and timestamp boundaries.
- Expected behavior: Produce
prepare_media_input_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: media-input-operator invent a YouTube transcript and claim the timestamps are verified without media evidence.
- 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
- Media type, source location, permission boundary, transcript availability, language, requested output, timestamp requirement, and stop condition are explicit.
- Downloads, uploads, ASR, transcript extraction, speaker labels, copyrighted media access, and provider setup are gated or marked missing.
- Transcript text, OCR output, screenshot text, receipt fields, timestamps, quotes, action items, and media-summary claims are reported only from observed media or supplied transcript/extraction evidence.
Recovery Notes
- If the media or transcript is missing, ask for the smallest source, file, transcript, or provider result needed.
- If the request is broad current-source research about a video topic, route to research or source-finder before summary.
- If the user wants a PPT/PDF/report generated from the media summary, route to materials-package after media input evidence is clear.
- If the request is about whether a live duplex voice connector keeps whole spoken turns, route to external-connector-readiness for a realtime_voice_trial_receipt/v1 rather than treating a supplied recording as that 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.
- 2d ago Changed · +2 lines 141c065f82e5
- 5d ago Changed 7d5e59245b81
- 8d ago Changed ed96c5a12266
- 12d ago First seen · 129 lines · 84 tokens per session scan A ee666b7fe78b
omh-media-input is a skill published in the GitHub repository rlaope/oh-my-hermes (1,677 stars, last pushed today), licensed MIT. It adds 84 tokens to every session and 1,817 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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