Hermes vs OpenClaw — Full Comparison Tutorial¶

Walk through both stacks on your machine, compare architecture and skills, migrate from OpenClaw to Hermes if needed, and decide which runtime fits your workflow.

Repos: NousResearch/hermes-agent · openclaw/openclaw

Companion: Feature matrix · OpenClaw + Gemma + RAG · Awesome Hermes Agent

Part 1 — What problem do they solve?¶

Both projects answer: "How do I talk to an AI agent from Telegram/WhatsApp/Discord and have it use tools on my machine?"

They diverge on what happens after the first week:

	OpenClaw	Hermes
Product feel	Polished personal assistant — gateway, channels, dashboard	Research-grade agent platform — tools, memory, evolution
Skills	You install or write `SKILL.md`; ClawHub registry	Agent can author skills; Curator maintains quality
Stack	Node.js, TypeScript, npm global	Python CLI, bash installer
Sweet spot	"Message my assistant anywhere"	"My assistant gets better at my workflows over time"

Neither is a hosted SaaS. You run the gateway on your laptop, homelab, or VPS.

Part 2 — Architecture side by side¶

OpenClaw¶

flowchart LR
    A[User on Telegram] --> B[OpenClaw Gateway]
    B --> C[Session + agent runtime]
    C --> D[SKILL.md in workspace]
    C --> E[Tools cron webhooks]
    C --> F[LLM provider or Ollama]
    D --> C
    E --> C
    F --> C
    C --> B
    B --> A

Gateway = single control plane (default http://127.0.0.1:18789/)
Workspace = ~/.openclaw/workspace with AGENTS.md, SOUL.md, TOOLS.md
Skills = ~/.openclaw/workspace/skills/<name>/SKILL.md
Daemon = launchd/systemd user service after openclaw onboard --install-daemon

Docs: Architecture · Gateway

Hermes¶

flowchart LR
    A[User on Telegram] --> B[hermes gateway]
    B --> C[Agent + tools]
    C --> D[~/.hermes/skills]
    C --> E[Memory]
    E --> F[Curator loop]
    F --> D
    C --> G[MCP plugins]
    C --> H[LLM provider]
    H --> C
    C --> B
    B --> A

CLI + TUI = hermes, hermes --tui
Gateway = hermes gateway for messaging platforms
Skills = procedural memory in ~/.hermes/skills/
Curator (v0.12+) = periodic grading/pruning of learned skills

Docs: Hermes user guide

Shared pattern¶

Both normalize inbound chat JSON → agent message → tool/skill execution → outbound reply. Both use Markdown skills as the extension point for custom workflows.

Part 3 — Prerequisites¶

Requirement	OpenClaw	Hermes
OS	macOS, Linux, Windows (WSL2)	macOS, Linux, WSL
Runtime	Node 22.19+ or 24	Python (installer handles deps)
API key or local model	Yes	Yes
Disk	~500MB+ for Node + workspace	~1GB+ depending on browser tools

Check versions:

node -v          # v22.19+ or v24 for OpenClaw
which hermes     # after Hermes install
which openclaw   # after OpenClaw install

OpenClaw on Node 20 fails — use use-node22.sh from our OpenClaw guide if needed.

Part 4 — Install OpenClaw¶

npm install -g openclaw@latest
openclaw onboard --install-daemon

The onboarding wizard configures:

Gateway bind address and auth
LLM provider (or Ollama for local models)
At least one channel (Telegram is the fastest smoke test)
Workspace path and bundled skills

Verify:

openclaw doctor
openclaw status
# Dashboard (if gateway running):
# http://127.0.0.1:18789/

Local model (optional): follow the OpenClaw + Gemma + RAG tutorial to point OpenClaw at gemma4:e2b via Ollama.

OpenClaw skills smoke test¶

openclaw skills list
openclaw skills install <skill-from-clawhub>   # example — see clawhub.ai

Skills load from (highest priority first):

<workspace>/skills/
Project /.agents/skills
~/.agents/skills
~/.openclaw/skills
Bundled skills

See Skills docs.

Part 5 — Install Hermes¶

curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
source ~/.zshrc   # or ~/.bashrc
hermes setup --portal

hermes setup --portal is the fastest path to a working cloud model + tool gateway. For local-only, use hermes model and configure Ollama per Hermes docs.

Verify:

hermes doctor
hermes --tui

First TUI prompts to try:

"List tools you have access to"
"List skills in ~/.hermes/skills"
"What is the Curator and when does it run?"

Full Hermes depth: Awesome Hermes Agent tutorial.

Hermes gateway smoke test¶

hermes gateway

Configure channel tokens via hermes setup or config files. Run hermes doctor after any gateway change. Keep DM pairing / allowlists enabled until you trust exposure.

Part 6 — Feature comparison (hands-on)¶

Use the same three prompts on both systems and compare behavior.

Test prompt	What to observe
"What skills do you have?"	OpenClaw lists workspace/ClawHub skills; Hermes lists `~/.hermes/skills` + may mention learned skills
"Run a shell command: uname -a"	Tool permission / sandbox behavior
"Remember that my project codename is NEPTUNE"	Memory persistence on next session

Record results in a simple table:

Test	OpenClaw	Hermes
Skill list
Shell tool
Memory

Full static matrix: feature matrix.

Part 7 — Skills: same format, different lifecycle¶

OpenClaw skill anatomy¶

~/.openclaw/workspace/skills/my-skill/
├── SKILL.md          # YAML frontmatter + instructions
└── scripts/          # optional Python/shell helpers

Install from ClawHub:

openclaw skills install <skill-id>
openclaw skills verify <skill-id>    # trust envelope when available

Operator maintains skills — update via openclaw skills update or ClawHub sync.

Hermes skill anatomy¶

~/.hermes/skills/my-skill/
└── SKILL.md

Invoke explicitly: /skill my-skill or let the agent auto-select.

Learning loop: after repeated workflows, Hermes can draft new SKILL.md files from session traces. Curator (v0.12+) reviews and prunes them on a ~7-day cycle so quality does not drift.

Porting a skill between stacks¶

Copy the skill directory to the other runtime's skills path.
Adjust tool names in SKILL.md (OpenClaw vs Hermes tool schemas differ).
Update any script paths (~/.openclaw ↔ ~/.hermes).
Restart gateway / start a new session.

Example: our agentic-rag skill targets OpenClaw — a Hermes port would call the same LitServe RAG API with Hermes shell tool syntax.

Part 8 — Channels & gateway¶

Concern	OpenClaw	Hermes
Start daemon	Installed by onboard	`hermes gateway` (or systemd per your setup)
Multi-channel	One gateway, many channels	One gateway, 18+ platforms
Config	`openclaw.json` + wizard	Hermes config under `~/.hermes/`
Chat commands	`/status`, `/new`, `/restart`, …	Hermes TUI + channel-specific

Recommendation: enable one channel (Telegram) on both for comparison, then expand. Running both gateways on the same bot token will conflict — use separate bots or run one at a time.

Part 9 — Models: cloud vs local¶

OpenClaw + Ollama (this repo's pattern)¶

ollama pull gemma4:e2b
# Configure in openclaw.json — see openclaw-gemma-rag/config/
openclaw gateway restart

Hermes + local model¶

Configure via hermes model or provider section in Hermes docs. Cloud APIs remain the path of least resistance for tool-heavy tasks on modest hardware.

Workload	Suggestion
Phone assistant, mostly chat	Cloud model on either stack
Private docs, RAG, homelab	OpenClaw + Gemma RAG guide
Heavy browser automation	Hermes with sandbox backend (Modal/Daytona) or skip browser on small VPS

Part 10 — Memory & self-improvement¶

	OpenClaw	Hermes
Session history	Session tools (`sessions_history`, etc.)	Built-in session + TUI history
Long-term memory	Workspace files + operator-managed	Memory layer + ecosystem plugins (honcho, hindsight, plur)
Automatic skill growth	No	Yes — core differentiator
Quality control	Manual review, `openclaw skills verify`	Curator automated grading

Choose Hermes when you want the agent to accumulate procedural memory. Choose OpenClaw when you want predictable, curator-controlled skill sets from ClawHub.

Part 11 — Migrate OpenClaw → Hermes¶

Hermes ships a native migration path:

hermes claw migrate

This imports OpenClaw workspace layout, channel configuration, and compatible skills where possible.

After migration:

hermes doctor
hermes claw migrate --help   # inspect flags
# Compare cron + channel config manually
hermes gateway

Community fallback for older Hermes versions: openclaw-to-hermes.

Side-by-side cutover (recommended for production personal assistants):

Migrate with hermes claw migrate
Run Hermes gateway on a new Telegram bot
Keep OpenClaw on the old bot until Hermes passes your test checklist
Switch DNS/webhooks if applicable
Decommission OpenClaw daemon when satisfied

Part 12 — Security comparison¶

Risk	OpenClaw mitigation	Hermes mitigation
Malicious skill	`openclaw skills verify`, review scripts	Review `SKILL.md` + scripts before enabling
Shell/RCE	Docker sandbox (docs strongly recommend)	Remote sandboxes, minimal VPS install (`--skip-browser`)
Open gateway	Local bind, auth tokens	`hermes doctor`, pairing/allowlists
Prompt injection via chat	Model choice, tool allowlists	Same — use strongest model available

Rule for both: skills are code. Treat ClawHub and awesome-hermes-agent entries as untrusted until reviewed.

Part 13 — Run both side by side (this repo)¶

From the repo root:

cd guides/hermes-vs-openclaw
chmod +x verify-comparison.sh
./verify-comparison.sh

Optional full stack:

Terminal	Command
A	Start RAG API per qwen-agentic-rag
B	`openclaw gateway` (messaging assistant)
C	`hermes --tui` (compare tool/skill behavior)

OpenClaw consumes RAG via the agentic-rag skill. Hermes can call the same HTTP API via a custom skill or MCP wrapper.

Part 14 — Decision guide¶

flowchart TD
    Start[Need a self-hosted chat agent?] --> Q1{Want skills to evolve automatically?}
    Q1 -->|Yes| H[Hermes Agent]
    Q1 -->|No| Q2{Node.js shop + ClawHub?}
    Q2 -->|Yes| O[OpenClaw]
    Q2 -->|No| Q3{Migrating from OpenClaw?}
    Q3 -->|Yes| H
    Q3 -->|No| Q4{Local Gemma RAG on chat?}
    Q4 -->|Yes| O
    Q4 -->|No| Both[Try both — install takes ~10 min]

Profile	Pick
Indie hacker, Telegram/WhatsApp only, loves npm	OpenClaw
ML researcher, multi-agent, Nous ecosystem	Hermes
Existing OpenClaw user, curious about learning loop	Hermes via `hermes claw migrate`
Need reproducible skill catalog, not auto-writes	OpenClaw + ClawHub
Building on this repo's RAG guides	OpenClaw primary; Hermes optional second runtime

You can also run OpenClaw for channels and Hermes for batch/cron evolution against the same RAG API — they are not mutually exclusive at the API layer.

Part 15 — Troubleshooting¶

Symptom	OpenClaw fix	Hermes fix
CLI not found	`npm i -g openclaw@latest`; check `node -v`	`source ~/.zshrc`; re-run installer
Doctor fails	Re-run `openclaw onboard`	`hermes setup --portal`
Gateway won't start	`openclaw gateway restart`; check port 18789	`hermes doctor`; check channel tokens
Skills missing	`openclaw skills list`; workspace path	`ls ~/.hermes/skills`; new session
Node too old	nvm install 22; `use-node22.sh`	N/A
Migration incomplete	—	`hermes claw migrate`; compare cron/channels; try openclaw-to-hermes
Both fight for Telegram	Use two bot tokens	Use two bot tokens

Summary¶

Dimension	Winner (typical)
Channel polish + dashboard	OpenClaw
Self-improving skills	Hermes
npm / TypeScript ecosystem	OpenClaw
Multi-agent + research tooling	Hermes
Local Gemma + RAG (this repo)	OpenClaw
OpenClaw → Hermes migration	Hermes (`hermes claw migrate`)

Next steps:

Deep dive OpenClaw: openclaw-gemma-rag tutorial
Deep dive Hermes: awesome-hermes-agent tutorial
Feature reference: feature matrix

Blog / LinkedIn angle¶

Post: short GIF of the dual-gateway workflow + 2–3 sentence verdict ("OpenClaw for channel-first assistants, Hermes when you want skills that compound").

First comment: links to this guide's overview and tutorial.