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-best-practice-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-best-practice-research)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-best-practice-research"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-best-practice-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-best-practice-research"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-best-practice-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 | $0.00053 | $0.01003 |
| Opus 5 | $0.00026 | $0.00502 |
| Sonnet 5 | $0.00011 | $0.00201 |
| Haiku 4.5 | $0.00005 | $0.00100 |
Grade A, and why
omh-best-practice-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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Best Practice Research
This is a Hermes-native best-practice-research workflow skill.
Why This Exists
best-practice-research exists to keep research work explicit, evidence-backed, and inside the Hermes/executor boundary instead of relying on ad hoc chat narration.
Do Not Use When
- The work needs a market or literature comparison, or a decision-grounding dossier, rather than one technology's upstream guidance; use
research. - The question is a current-facts lookup one cited retrieval round settles rather than a versioned guidance question; use
web-research.
Examples
Good example:
- Prompt: best-practice-research: check official docs and upstream examples before we choose the plugin packaging pattern.
- Expected behavior: Gather primary-source guidance, compare options, and separate evidence from recommendation.
- Why: The request needs citation-backed best-practice research before implementation.
Bad example:
- Prompt: best-practice-research: treat casual chat or unaccepted work as if this workflow already produced verified results.
- Expected behavior: Ask a clarification question or route to a narrower workflow instead of forcing
best-practice-research. - Why: The request lacks the required inputs or would overclaim work that Hermes did not observe.
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
- If sources cannot be accessed, state the retrieval gap and use only observed local context.
- If evidence is thin or one-sided, lower confidence and ask for a narrower source boundary.
Workflow Lane
- Current lane: Research and company ops (
product-docs,source-finder,web-research,research,best-practice-research,autoresearch-goal,model-optimization,inference-serving,+19 more) - research, signals, ops, and briefings. - 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.
- 4d ago Changed ba2c21c86760
- 7d ago Changed c3a5844aefcf
- 9d ago Changed · +1 lines de0c4adc7873
- 13d ago First seen · 118 lines · 53 tokens per session scan A 9519fd2a6503
omh-best-practice-research is a skill published in the GitHub repository rlaope/oh-my-hermes (1,677 stars, last pushed today), licensed MIT. It adds 53 tokens to every session and 1,003 once invoked, about $0.0003 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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