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-web-researchgit 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-web-research)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-web-research"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-web-research/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-web-research"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-web-research.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 | $0.00075 | $0.01623 |
| Opus 5 | $0.00037 | $0.00812 |
| Sonnet 5 | $0.00015 | $0.00325 |
| Haiku 4.5 | $0.00007 | $0.00162 |
Grade A, and why
omh-web-research 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 4d 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.
Web Research
This is a Hermes-native web-research workflow skill.
Why This Exists
web-research exists so a current-facts question returns a cited answer in one retrieval round, without the declared depth budget, reference-implementation study, and dossier that research requires.
Do Not Use When
- The decision needs reference-implementation study, a declared depth budget, or a decision-grounding dossier; use
research. - Correctness turns on one technology's versioned official or upstream guidance; use
best-practice-research. - The output is a typed candidate inventory and acquisition status rather than an answer; use
source-finder. - The ask is a market, competitor, pricing, or customer decision brief; use
research-brief. - The user wants recurring monitoring, a source inbox, or Scout/Analyst/Briefer operations; use
research-department. - The user wants to configure or cheapen web search itself, such as a scraper API key or an auxiliary extract model; use
websearch-setup. - The study target is this repository rather than the open web; use
codebase-onboarding.
Examples
Good example:
- Prompt: 이번 주 기준으로 그 API 요금제 어떻게 바뀌었는지 웹서치해서 알려줘.
- Expected behavior: Retrieve current pricing from the vendor's own page, cite it with the retrieval date, and name what the page does not state.
- Why: A current-facts question that one cited retrieval round settles.
Bad example:
- Prompt: 스펙 잡기 전에 오픈소스 구현들 깊게 보고 근거 만들어줘.
- Expected behavior: Route to
research, which declares a depth budget and studies reference implementations with pinned refs. - Why: Pre-spec grounding needs the engine's dossier rather than a single lookup.
Completion Checklist
- The research question, source boundaries, recency assumptions, and confidence level are named.
- Observed sources, inference, synthesis, and unresolved retrieval gaps are separated.
- Follow-up planning or handoff uses the research summary without calling it execution evidence.
Recovery Notes
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.
- 4d ago Changed · +5 lines 26978ecc8939
- 7d ago Changed 2bc3ab0cdd7d
- 9d ago First seen · 131 lines · 75 tokens per session scan A 68fdb26f0c8b
omh-web-research is a skill published in the GitHub repository rlaope/oh-my-hermes (1,677 stars, last pushed today), licensed MIT. It adds 75 tokens to every session and 1,623 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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