Want to level up your (@NousResearch) Hermes Agent’s intelligence?

Meet oh-my-hermes.

It’s the ultimate all-in-one suite: memory management, coding orchestration, wiki building, domain expertise harnesses, and more.

Stop juggling multiple plugins—this is your single all-in-one solution. Just install it and you’re good to go.

https://github.com/rlaope/oh-my-hermes…

#hermes #agent #ai

rlaope/oh-my-hermes

Source: https://github.com/rlaope/oh-my-hermes

Hermes Desktop, with oh-my-hermes. Pick a workflow; Hermes clarifies before it builds.	Hermes CLI, with oh-my-hermes. The same workflows, in your terminal.
Hermes messenger app, with oh-my-hermes. Ask in a thread; the run reports back there.	omh setup, one command. Installs the workflows and connects them to Hermes.

oh-my-hermes

English | 한국어 | 日本語 | 中文

Install once. Keep Hermes. Add a stronger operating layer.
Planning, research, creation, coding handoffs, operations, and project memory with explicit evidence boundaries.

oh-my-hermes (OMH) turns a normal request in Hermes Agent into a clear capability, a useful next step, and an honest statement of what has or has not happened. It strengthens the Hermes workflow you already use instead of replacing Hermes or hiding a coding executor behind it.

OMH is the operating layer above individual Hermes-native skills: it frames the problem, selects the workflow and evidence gates, and uses native skills as capabilities within that governed path rather than as competing top-level owners.

Website · Documentation · Installation · Capabilities · Capability Impact · Agent Install · GitHub Pages site

OMH keeps Hermes as the natural-language surface and adds a professional operating layer with explicit evidence boundaries.

Quick Start

Install the local command and managed skills:

curl -fsSL https://raw.githubusercontent.com/rlaope/oh-my-hermes/main/install.sh | sh
omh setup

Hermes skill tap path:

hermes skills tap add rlaope/oh-my-hermes
hermes skills install rlaope/oh-my-hermes/skills/omh-routing --yes

or ask Your AI Agent:

Hey Agent, Install this >> https://github.com/rlaope/oh-my-hermes <<

Update and health check:

omh update
omh doctor

Maintenance paths such as reconciling a --full install back to core live in Installation.

What OMH Adds

OMH packages 92 installable workflow skills behind six human-readable capability families. The family is the front door; exact skill names remain available when a wrapper or operator needs precise control.

Ten of them are workflow engines - deep-interview, loop, ralph, ralplan, team, ultragoal, ultraprocess, ultraqa, ultrawork, web-research - and render a ulw- label so a status line says which kind of skill is running. The other 82 render omh-. Canonical names are unchanged either way.

The full generated catalog, triggers, harnesses, and evidence rules live in Workflow Reference.

Highlights

Built For Real Work

OMH (Oh-My-Hermes) — Anyone can use hermes-agent professionally.
The powerful intelligence harness for your AI Agent.

🧭 A stronger router, not a command dump. English, Korean, Japanese, Chinese, Spanish, French, German, and Hindi operator requests can be classified locally without a translation API. OMH returns the recommended family, skill, owner, next action, and what is still not evidence.

🤝 Better coding handoffs. OMH can include repository constraints, accepted scope, worktree and session-isolation guidance, locally available skills, acceptance criteria, review expectations, and verification gates. Codex, Claude Code, Hermes, and generic executors remain explicit owners rather than hidden defaults.

🎨 Quality-aware creation. Frontend, accessibility, image, report, slide, document, spreadsheet, PDF, poster, and shareable-package requests are routed through specialized production and QA guidance. A prepared brief is never presented as a generated or visually verified artifact.

🔍 Evidence before claims. OMH separates prepared intent, observed runtime events, and verified results. A handoff can be ready without claiming that an executor ran, a review passed, CI succeeded, a deployment completed, or a PR was merged.

🧠 Review-first project memory. OMH keeps project-memory candidates separate from approved records and recalls only reviewed, prepared context into future handoffs. It does not pretend to read or mutate opaque Hermes memory.

🔌 Provider-neutral operations. Metric, wiki, browser, image, video, and connector systems sit behind explicit external-provider contracts. OMH can validate and analyze supplied data without pretending that a provider was connected or called.

🏛️ Hermes-native, executor-neutral architecture. Hermes remains the chat, clarification, planning, research, and status surface. The selected executor owns implementation, while OMH supplies the local contracts, routing, memory, quality gates, and evidence boundaries around that work.

🧱 Local-first control plane. Core OMH routing, catalogs, manifests, and claim rules are deterministic local surfaces. External calls and provider access stay explicit integrations rather than hidden behavior inside the core.

Evidence Before Claims

OMH separates useful preparation from observed results:

prepared_not_observed is not execution, provider access, artifact generation, review, CI, deployment, merge readiness, or a merge. Capability impact is reported across separate dimensions rather than collapsed into one marketing score. See Capability Impact.

Documentation

• Documentation map
• Installation and updates
• Product direction and boundaries
• Architecture
• Capability manifests
• Workflow reference
• Roles
• Application cases
• Release and development

Development

For a source checkout:

PYTHONPATH=tests uv run python -m unittest discover -s tests -v
uv run python -m compileall -q src tests
uv run python -m omh.cli docs workflows --check
git diff --check

OMH is developed in the open as part of Team Art & Engineering. Follow @rlaope for project updates.