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-performance-goalgit 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-performance-goal)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-performance-goal"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-performance-goal/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-performance-goal"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-performance-goal.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 | $0.00036 | $0.00939 |
| Opus 5 | $0.00018 | $0.00469 |
| Sonnet 5 | $0.00007 | $0.00188 |
| Haiku 4.5 | $0.00004 | $0.00094 |
Grade A, and why
omh-performance-goal 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Goal
This is a Hermes-native performance-goal workflow skill.
Why This Exists
performance-goal exists to keep optimization work explicit, evidence-backed, and inside the Hermes/executor boundary instead of relying on ad hoc chat narration.
Do Not Use When
- The ask is to find where performance problems are, or to fix multiple unscoped hotspots across domains; use
ultraperf.
Examples
Good example:
- Prompt: performance-goal: benchmark recommendation latency, optimize hot paths safely, and prove no regressions.
- Expected behavior: Create a measurement-led optimization loop with baseline, change, verification, and regression evidence.
- Why: The request is performance optimization and needs measured before/after proof.
Bad example:
- Prompt: performance-goal: 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
performance-goal. - Why: The request lacks the required inputs or would overclaim work that Hermes did not observe.
Completion Checklist
- Confirm the workflow target, evidence boundary, and stop condition are named.
- Report which outputs are prepared, observed, blocked, or missing.
- Name the smallest next verification or handoff instead of claiming completion from narration.
Recovery Notes
- If required context is missing, ask one blocking question or route back to the narrower workflow.
- If runtime or wrapper evidence is unavailable, keep the status as not_observed and expose the next observable action.
Workflow Lane
- Current lane: Intent -> plan (
oh-my-hermes,meta-router,deep-interview,context,plan,ralplan,adversarial-consensus,codebase-onboarding,+9 more) - clarify, plan, ship, or loop goals. - 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 e9663c50badf
- 9d ago First seen · 118 lines · 36 tokens per session scan A ca69ccde7d75
omh-performance-goal is a skill published in the GitHub repository rlaope/oh-my-hermes (1,677 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 939 once invoked, about $0.0002 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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