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-plangit 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-plan)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/ulw-plan"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/ulw-plan/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-plan"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/ulw-plan.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 | $0.00051 | $0.02090 |
| Opus 5 | $0.00026 | $0.01045 |
| Sonnet 5 | $0.00010 | $0.00418 |
| Haiku 4.5 | $0.00005 | $0.00209 |
Grade A, and why
ulw-plan 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ralplan
This is a Hermes-native ralplan workflow skill.
Why This Exists
ralplan exists to make planning reviewable before execution: Hermes should gather codebase/source facts, compare options, expose risks, define acceptance criteria, and prepare a handoff without pretending implementation already happened.
Do Not Use When
- The request is still too ambiguous to name requirements, non-goals, or acceptance criteria; use
deep-interviewfirst. - The user asks for one full research-plan-implementation-review-PR cycle; use
ultrawork(itsdelivery_boundarycapability) and keep ralplan as the planning stage. - The change is a small local refactor or cleanup with no architectural or regression risk; use
ultrawork, orai-slop-cleanerwhen observable behavior must stay identical. - The refactor's direction is already decided and what is missing is its execution shape - which files move in which phase, what verifies each phase, where each phase rolls back to; use
refactor-plan. - One plan-blocking choice still needs behavior evidence rather than argument; run
decision-prototypefirst and consume its decision receipt without transcript replay. - The user wants a pure source lookup, citation check, or paper explanation with no implementation plan.
- The unresolved work is repository terminology alignment or a project-language decision frontier; use
contextbefore planning.
Examples
Good example:
- Prompt: $ralplan turn this risky refactor into a reviewable plan with acceptance criteria and verification commands.
- Expected behavior: Produce repo/source facts, alternatives, risk review, acceptance criteria, exact verification commands, and handoff readiness without editing code.
- Why: The request is clear enough to plan but risky enough to require consensus-style review before execution.
Bad example:
- Prompt: $ralplan implement the refactor now and open the PR.
- Expected behavior: Stop at the reviewed plan or route the full delivery cycle to
ultraworkafter plan acceptance. - Why: Ralplan is a planning gate, not implementation, review, CI, or PR 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.
- 4d ago Changed · +1 lines ad7f130b32e8
- 9d ago First seen · 143 lines · 51 tokens per session scan A 7521ff50aba0
ulw-plan is a skill published in the GitHub repository rlaope/oh-my-hermes (1,677 stars, last pushed today), licensed MIT. It adds 51 tokens to every session and 2,090 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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