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-product-briefgit 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-product-brief)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-product-brief"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-product-brief/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-product-brief"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-product-brief.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 | $0.00063 | $0.01344 |
| Opus 5 | $0.00032 | $0.00672 |
| Sonnet 5 | $0.00013 | $0.00269 |
| Haiku 4.5 | $0.00006 | $0.00134 |
Grade A, and why
omh-product-brief 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Brief
This is a Hermes-native product-brief workflow skill.
Why This Exists
product-brief turns product evidence into a reviewable PRD and prioritization frame before delivery planning without treating a draft as an accepted roadmap commitment.
Do Not Use When
- The input is unprocessed feedback, bug reports, or feature asks that first need clustering and evidence boundaries; use
feedback-triage. - The product evidence is unvalidated, synthetic, or a founder belief and the problem gate has not returned validated; use
product-discovery-validationbefore a PRD. - The input is a growth hypothesis that still needs an experiment and readout before it becomes a product requirement; use
lifecycle-growth. - The user needs a company or product strategy decision across high-level options rather than a requirements or roadmap artifact; use
strategy-brief. - The request is an accepted, code-ready change with repository constraints and verification needs; use
ralplanorultraworkrather than recreating a PRD. - The user asks to create or update Jira, Linear, Aha!, or a roadmap system directly; use
connector-operatorwith explicit target, approval, and observed evidence.
Examples
Good example:
- Prompt: Create a PRD and prioritization options for reducing first-time user drop-off in onboarding.
- Expected behavior: Prepare the product problem, user and metric brief, PRD, roadmap options, tradeoffs, and downstream prerequisites.
- Why: The request needs a decision-ready requirements and prioritization artifact before delivery planning.
Bad example:
- Prompt: Implement the accepted onboarding PRD and open a PR.
- Expected behavior: Route to
ultraworkorralplan, notproduct-brief. - Why: Accepted implementation work should move into planning or delivery rather than recreate a PRD.
Completion Checklist
- The plan names goals, non-goals, assumptions, acceptance criteria, and verification shape.
- Draft recommendations, accepted decisions, and executor handoffs are separate states.
- Rejected options or unresolved tradeoffs are recorded before handoff.
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 · +2 lines 9d5b433661c6
- 9d ago First seen · 126 lines · 63 tokens per session scan A 4529da989081
omh-product-brief is a skill published in the GitHub repository rlaope/oh-my-hermes (1,677 stars, last pushed today), licensed MIT. It adds 63 tokens to every session and 1,344 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.
Other skills, from other repositories
starting-a-new-project
Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead.
configuration
Use when a Project Agent reads or changes managed presets, game modules, automations, Skills, or Agent profiles through configread and configapply.
incident-commander
Coordinate active incidents through severity assessment, roles, mitigation, communications, recovery verification, and postmortem handoff.
interview-system-designer
Design hiring interviews, competency matrices, question banks, scoring rubrics, and interviewer calibration for a specified role.
lark-task
A task-management skill for Lark, the collaboration platform, covering tasks, checklists, subtasks, assignments, attachments, and task-focused agents.
linear
A skill for managing Linear, a project-management tool for software teams, through its API. It works with issues, projects, teams, and collaboration data.