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-loopgit 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-loop)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/ulw-loop"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/ulw-loop/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-loop"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/ulw-loop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 167 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 | $0.00063 | $0.03687 |
| Opus 5 | $0.00032 | $0.01843 |
| Sonnet 5 | $0.00013 | $0.00737 |
| Haiku 4.5 | $0.00006 | $0.00369 |
Grade A, and why
ulw-loop 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 yesterday.
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 — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loop
This is a Hermes-native loop workflow skill.
Why This Exists
loop exists for goals whose correct implementation cannot be known upfront but can be discovered through bounded cycles of definition, action, verification, and revision without confusing planned cycles with observed progress.
Do Not Use When
- The user asks for one bounded delivery cycle; use
ultrawork's delivery-boundary capability instead. - Scope and milestones are already known and only durable checkpoint/resume tracking is needed; use
ultrawork's durable-checkpoint capability. - The user gives only a north-star outcome such as revenue, stars, or adoption and has not accepted a bounded first loop goal.
- The goal is too vague to name an observable problem, next artifact, verification signal, or stop condition.
- The goal depends mainly on external waiting, adoption, revenue, or community response without observable local next actions.
- The permission profile does not allow repeated research, handoff, queue, or feedback cycles.
Examples
Good example:
- Prompt: ./loop make OMH a credible Hermes workflow pack with install, docs, QA, and feedback cycles.
- Expected behavior: Start a permission-scoped loop, maintain loop_cycle/v1 state, choose the next concrete task, and keep external outcomes as waiting states.
- Why: The request is long-horizon and needs repeated discovery, verification, feedback, and resume decisions.
Bad example:
- Prompt: ./loop merge this already reviewed one-line README fix.
- Expected behavior: Use a direct delivery or PR workflow instead of starting a persistent loop.
- Why: The task is bounded and should stop after merge evidence rather than create ongoing cycles.
Completion Checklist
- The request is classified as task, project, north-star ambition, external-wait, or unclear before a loop starts.
- The current loop_status_card/v1 names the queue item, tick status, verification_plan, and next action.
- failure_mode_summary checks verification_gap, comprehension_debt, and cognitive_surrender before progress advances.
- Completion is backed by linked goal/runtime evidence; queued loop ticks alone are not observed work.
- Native
/goalactivation and continuation are backed by loop_goal_driver_observation/v1, and each observed role advance is backed by loop_phase_transition/v1.
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.
- yesterday Changed e5b4aa9e333c
- 3d ago Changed · +1 lines eabf40b96e8e
- 5d ago First seen · 212 lines · 63 tokens per session scan A 725fef521735
ulw-loop is a skill published in the GitHub repository rlaope/oh-my-hermes (1,582 stars, last pushed yesterday), licensed MIT. It adds 63 tokens to every session and 3,687 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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