Hermes Quick Start — Install, Memory Setup & First Long-Running Task

Prerequisites

• Node.js 22.16+ or Node 24 — check with node --version
• A model with a long context window — Hermes works with any provider, but its value shows most with models that can hold large contexts. Recommended: Claude Opus 4.6 (200K context), Claude Sonnet 4.6 (200K), or GPT-4.1 (128K). See the model selection guide below.
• At least 500 MB disk space for the SQLite memory store. Heavy use over months can grow to several GB — plan accordingly or use the PostgreSQL backend.
• Linux or macOS recommended. Windows works; WSL2 is preferred for the daemon mode.

Step 1 — Install Hermes

npm install -g hermes-agent

# Verify
hermes --version
# hermes/0.9.3 linux-x64 node/22.16.0

Unlike OpenClaw and IronClaw, Hermes installs as both a CLI tool (hermes) and a background daemon. The daemon is what maintains persistent memory and scheduled tasks when you're not actively using it.

Step 2 — Run the Setup Wizard

hermes init

The wizard asks seven questions:

After the wizard, Hermes creates:

~/.hermes/
  hermes.json          # main config
  memory.db            # SQLite memory store
  workspace/
    PERSONA.md         # who Hermes is (equivalent of OpenClaw's SOUL.md)
    TASKS.md           # scheduled and active tasks
    REFLECTIONS.md     # self-reflection log (written by Hermes)
    MEMORY.md          # manual memory entries (you write these)
  logs/
    daemon.log         # daemon activity log
    tasks.log          # task execution log

Step 3 — Start the Daemon

hermes start

# Output:
# [hermes] daemon v0.9.3 starting
# [hermes] memory store: sqlite (~/.hermes/memory.db) — 0 episodes
# [hermes] indexer: ready
# [hermes] scheduler: ready — 0 tasks queued
# [hermes] daemon running (PID 45821)

# Verify it's running
hermes status
# daemon: running (PID 45821)
# memory: 0 episodes, 0 facts, 0 reflections
# tasks: 0 queued, 0 running, 0 completed

The daemon runs in the background and survives terminal closures. To stop it:

hermes stop

Run as a System Service (recommended)

sudo tee /etc/systemd/system/hermes.service << 'EOF'
[Unit]
Description=Hermes Agent Daemon
After=network.target

[Service]
Type=forking
PIDFile=/home/YOUR_USERNAME/.hermes/daemon.pid
User=YOUR_USERNAME
ExecStart=/usr/local/bin/hermes start
ExecStop=/usr/local/bin/hermes stop
Restart=on-failure
RestartSec=10
EnvironmentFile=/home/YOUR_USERNAME/.hermes/.env

[Install]
WantedBy=multi-user.target
EOF

sudo systemctl enable hermes
sudo systemctl start hermes

Model Selection for Hermes

Hermes's memory compression means it can work with shorter context windows than you'd expect — the compression layer summarises old episodes before injecting them. But the model's reasoning quality matters more for long-horizon tasks than for quick Q&A. Choose based on task complexity:

The recommended setup: use Sonnet as the default with Opus as an escalation for tasks Hermes explicitly flags as high-complexity. Configure this in the config:

{
  "model": {
    "primary":   "anthropic/claude-sonnet-4-6",
    "heavy":     "anthropic/claude-opus-4-6",
    "light":     "anthropic/claude-haiku-4-5",
    "autoEscalate": {
      "enabled":      true,
      "triggerTokens": 50000,  // escalate to heavy model when task exceeds this
      "triggerScore":  0.8     // or when complexity score exceeds this threshold
    }
  }
}

Step 4 — Your First Task

Give Hermes a task through the CLI:

# A simple immediate task
hermes run "Summarise the top 5 AI news stories from this week and save to workspace/weekly-brief.md"

# A scheduled task
hermes run --at "tomorrow 8am" "Check my GitHub notifications and send me a Telegram summary"

# A recurring task
hermes run --every "monday 9am" "Run a weekly project status check and update TASKS.md with blockers"

# A long-horizon task (Hermes breaks it into steps autonomously)
hermes run "Over the next week, research the current state of AI agent frameworks, compare them on 10 dimensions, and produce a 2000-word report. Check in with me at the halfway point."

Monitor task progress:

hermes tasks list
# ID       STATUS    SCHEDULED     DESCRIPTION
# t-001    running   now           Summarise AI news...
# t-002    queued    2026-04-07    Check GitHub notifications...
# t-003    queued    2026-04-13    Weekly status check (recurring)

hermes tasks log t-001   # see execution log for a task
hermes tasks cancel t-002  # cancel a queued task

Step 5 — Verify Memory Is Working

After your first task completes, Hermes automatically stores an episode in its memory database. Check it:

hermes memory status
# Episodes:    1
# Facts:       4
# Reflections: 1
# DB size:     128 KB

hermes memory search "AI news"
# [episode:001] 2026-04-06 — Summarised top 5 AI stories...
# [fact:003] Claude Opus 4.6 released April 2026 with 200K context

If memory shows 0 episodes after a completed task, your version is likely below v0.9.3. Upgrade immediately.

CLI Quick Reference