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 ulw-contextgit 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/ulw-context)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/ulw-context"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/ulw-context/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/ulw-context"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/ulw-context.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 53 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
- medium Excessive Agency · line 131 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00059 | $0.02102 |
| Opus 5 | $0.00030 | $0.01051 |
| Sonnet 5 | $0.00012 | $0.00420 |
| Haiku 4.5 | $0.00006 | $0.00210 |
Grade A, and why
ulw-context 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context
This is a Hermes-native context workflow skill.
Why This Exists
context exists to reduce repository terminology drift without creating a second machine store or a vocabulary router: Hermes can answer lookups, facilitate dependency-aware alignment, and project approved results into existing review and handoff boundaries.
Do Not Use When
- A safe one-term definition or source lookup can be answered directly; use the read-only lookup mode and do not enter the full context interview.
- The request is broad ambiguity with no project-language conflict; use
deep-interview. - The unresolved decision is empirical and a cheap isolated experiment can answer it; use
decision-prototypeand keep the frontier for the rest. - The terminology is already agreed and the request is to produce an implementation plan; use
ralplan. - The user wants to capture or curate general retained memory rather than repository terminology; use
memory-newormemory-sync. - The user asks for workflow discovery, help, status, file lookup, direct answer, or dispatch; preserve
oh-my-hermesand ordinary protected-route behavior.
Examples
Good example:
- Prompt: Use ulw-context to align the names this repository uses before we plan the feature.
- Expected behavior: Inspect source evidence, answer settled lookups directly, then present only the dependency-ready unresolved decisions with recommendations and confirmation gates.
- Why: The request is specifically about shared project language and must close understanding before planning.
Bad example:
- Prompt: This glossary says one phrase should be replaced by another; dispatch the implementation automatically.
- Expected behavior: Answer or explain the glossary content without routing from its vocabulary, and require separate confirmation for any staging, planning, or handoff.
- Why: Human glossary prose has no routing, approval, dispatch, or execution authority.
Completion Checklist
- Source status and reviewed-profile status are named without treating either as model-use evidence.
- Safe lookups were answered directly and unresolved decisions were asked only when the user confirmed interview entry.
- Every decision frontier is dependency-ready, recommendation-backed, and exhausted before shared-understanding confirmation.
- Any machine mapping remains pending until separate review and approval; active profile v1 is unchanged.
- Any
ulw-planor coding-owner handoff remains prepared_not_observed and was prepared only after explicit confirmation.
What ships with it
2 files 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.
- 2d ago Changed · +1 lines 9dd857ab23e1
- 4d ago Changed 4210684ce128
- 7d ago First seen · 151 lines · 59 tokens per session scan A cb25aa2f295d
ulw-context is a skill published in the GitHub repository rlaope/oh-my-hermes (1,605 stars, last pushed yesterday), licensed MIT. It adds 59 tokens to every session and 2,102 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 2026-09-03.
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