f9102e4ca4
* fix: userscan tmux and zellij socket probes pass the /tmp literal check The four lines read where tmux and zellij put their sockets (and, on macOS, measure the user's own temp dir). The POSIX fallback for those directories is /tmp, so the literal is the fact being probed, not a scratch path. Mark each line so the blocking lint step in lint.yml passes. * fix: setup-profile and start_chat RPCs no longer block the RPC reader onboarding.ensure_setup_profile / ensure_setup_session / reset_setup_profile can run create_profile (a skill-tree copy), state.db writes and the first import of the setup scanner. session.start_chat creates a session and runs prompt.submit. Inline on the reader thread they left session.interrupt and approval.respond unread in the pipe, the failure the _LONG_HANDLERS comment names. profiles.create was already on the list for the same reason. * fix: userscan children run with stdin closed and the served profile's env The /initiate-setup builder runs the user scan on a backend thread, so every child the scan spawned inherited the JSON-RPC stdin pipe (#14036) and the launch profile's os.environ. HostAccess.run, copy_locked and the PowerShell batch now pass stdin=subprocess.DEVNULL, and every spawn takes its env from HostAccess.child_env(). host_facts passes served_profile_child_env() into the run; the standalone run.py keeps the process env. check_subprocess_stdin.py now scans optional-skills/: the backend loads initiate-setup's scripts in-process. The nested-dir skip matches paths relative to the context dir, so a skill's own scripts/ folder is in scope. Three model-run optional-skill scripts it flagged get stdin closed. * refactor: split the userscan spec modules over 2,000 lines by topic Six spec modules under initiate-setup's userscan passed the 2,000-line gate. Each keeps its shared helpers and first families; the rest move verbatim into <stem>_<topic>.py siblings that import the helpers they use from the base module: apps_dev -> apps_dev_agents, apps_dev_devenv browser_files -> browser_files_comms, browser_files_content usage_gaming -> usage_gaming_games, usage_gaming_hardware linux_system -> linux_system_security, linux_system_hardware linux_apps -> linux_apps_dev, linux_apps_browser, linux_apps_files darwin_apps -> darwin_apps_dev, darwin_apps_browser, darwin_apps_files linux_system keeps health and usage: install_age reads usage's _wtmp and usage reads health's _kdump_dirs. References through the ad./bf./ug. aliases point at the module that now defines the name. specs/__init__ imports each sibling right after its base, so per-OS registration order and the registry keys stay the same. No behaviour change: `run.py --list` is byte-identical before and after, and a temp-home scan under --os darwin/linux/windows gives the same fact statuses, errors and insights. * fix: the setup scan never patches process globals or sys.path in the backend The /initiate-setup builder runs the user scan on a backend thread. It put the scanner dir at sys.path[0] of the backend (so a top-level `run` or `userscan` import anywhere resolved to the scanner), and it loaded host.py's deny_reads_under (swaps builtins.open, io.open, sqlite3.connect and subprocess.Popen) and override_env (rewrites os.environ HOME and HERMES_HOME) into the backend's import graph. - userscan/cli.py now holds override_env, the read guard, the aggregate HostAccess and scan_accounts. Only run.py imports it; runner.run() no longer retargets os.environ (overrides stay l0 data), and run.py applies override_env around run() for --home and friends. - The package uses relative imports, and host_facts loads it once per process as initiate_setup_userscan, without touching sys.path. Live: after an in-process scan sys.path, os.environ and the four patched callables are unchanged and no top-level userscan module exists (before: sys.path[0] was the scanner dir and userscan.host was importable). `run.py --list` is unchanged; --all-users and --home give the same output. * refactor: userscan runner runs each layer as a named phase runner._run was one closure-heavy function at cyclomatic complexity 66. Its state moves onto a small _Pass object whose run_l1 / run_l2 (with _run_python_l2) / run_l3 methods each hold one layer, moved verbatim; _run composes them and builds the output. Highest CC in the file is now 21 (run_l3). No behaviour change: temp-home scans under --os darwin/linux/windows give the same fact ids, statuses, methods, tiers, coverage, insights and output keys as before. * chore: name the setup intro flag writer, document gui_tour presets, trim media.ts - hermes_cli/setup_profile.py::mark_seen becomes mark_intro_seen. It writes the setup profile's intro state; agent/onboarding.py::mark_seen flips a config.yaml hint flag, and tui_gateway uses both. The RPC name onboarding.mark_seen is unchanged. - tools-reference: gui_tour's `start` without `steps` runs the built-in tour (`preset` quick or full, default full). - apps/desktop/src/lib/media.ts: drop the blank line at EOF (git diff --check). * docs: describe the setup chat's automatic machine scan The scan runs without a consent step when the desktop app creates the setup profile (the owner kept it automatic). The desktop user guide now says where it runs (the backend's machine), what it reads (T1: counts and categories; finer values are dropped before storage), what reaches the model (the derived fact block in the first setup message, sent to the setup chat's inference provider) and where the cache lives (insights/profile.json in the setup profile's home, 0600, 24 h). The skill's own docs page is generated from SKILL.md, which is the model's prompt, so the user-facing text lives in the desktop guide. * fix: overlapping setup-profile RPCs no longer race on the RPC pool ensure_setup_profile, ensure_setup_session and reset_setup_profile moved off the reader thread, so two kickoffs could overlap: both saw no setup profile, and the losers failed on the half-made profile (5 of 6 barrier-started calls returned ENOENT), or both saw an empty setup chat and seeded it twice. One module lock restores the one-at-a-time order; the prescan stays outside it. * fix: the Linux locale probe reads date formats in a child, not via setlocale locale.user ran setlocale(LC_TIME) on the scan thread inside the backend. setlocale is process-wide and not thread-safe, so strftime in other session threads briefly used the user's LC_TIME. The probe now runs 'locale d_fmt t_fmt' under LC_ALL=<locale> through HostAccess.run (new env overlay on child_env), after checking 'locale -a', because locale prints C formats for a locale that is not installed. * docs: link the setup scan from the /initiate-setup and onboarding references The desktop guide's scan section now says which search-engine names are kept and that the scan runs in the CLI and the gateway too. The /initiate-setup row and the profile_build bullet link to it.
Hermes Agent ☤
The self-improving AI agent built by Nous Research. It's the only agent with a built-in learning loop — it creates skills from experience, improves them during use, nudges itself to persist knowledge, searches its own past conversations, and builds a deepening model of who you are across sessions. Run it on a $5 VPS, a GPU cluster, or serverless infrastructure that costs nearly nothing when idle. It's not tied to your laptop — talk to it from Telegram while it works on a cloud VM.
Use any model you want — Nous Portal, OpenRouter, OpenAI, your own endpoint, and many others. Switch with hermes model — no code changes, no lock-in.
| A real terminal interface | Full TUI with multiline editing, slash-command autocomplete, conversation history, interrupt-and-redirect, and streaming tool output. |
| Lives where you do | Telegram, Discord, Slack, WhatsApp, Signal, and CLI — all from a single gateway process. Voice memo transcription, cross-platform conversation continuity. |
| A closed learning loop | Agent-curated memory with periodic nudges. Autonomous skill creation after complex tasks. Skills self-improve during use. FTS5 session search with LLM summarization for cross-session recall. Honcho dialectic user modeling. Compatible with the agentskills.io open standard. |
| Scheduled automations | Built-in cron scheduler with delivery to any platform. Daily reports, nightly backups, weekly audits — all in natural language, running unattended. |
| Delegates and parallelizes | Spawn isolated subagents for parallel workstreams. Write Python scripts that call tools via RPC, collapsing multi-step pipelines into zero-context-cost turns. |
| Runs anywhere, not just your laptop | Seven terminal backends — local, Docker, SSH, Singularity, Modal, Daytona, and Vercel Sandbox. Daytona and Modal offer serverless persistence — your agent's environment hibernates when idle and wakes on demand, costing nearly nothing between sessions. Run it on a $5 VPS or a GPU cluster. |
| Research-ready | Batch trajectory generation, trajectory compression for training the next generation of tool-calling models. |
Quick Install
Linux, macOS, WSL2
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
Windows (native, PowerShell)
Heads up: Native Windows runs Hermes without WSL — CLI, gateway, TUI, and tools all work natively. If you'd rather use WSL2, the Linux/macOS one-liner above works there too. Found a bug? Please file issues.
Run this in PowerShell:
iex (irm https://hermes-agent.nousresearch.com/install.ps1)
The source installer delegates Python 3.14, Node.js, npm, ripgrep, FFmpeg, and Python dependencies to PM. If Git is absent, it stages the verified Git for Windows archive in Hermes' tool store. It does not replace your system Git. See installation methods for the separate MSIX/App Installer package and its update ownership.
Android / Termux: A signed APT repository is available for aarch64 devices, with a
stablechannel (tagged releases) and a prereleasecanarychannel. The package includes Python, Node.js, and the TUI. Use the Termux guide, not the desktop/server installer script.Windows: Native Windows is fully supported — the PowerShell one-liner above installs everything. If you'd rather use WSL2, the Linux command works there too. Native Windows install lives under
%LOCALAPPDATA%\hermes; WSL2 installs under~/.hermesas on Linux.
After installation:
source ~/.bashrc # reload shell (or: source ~/.zshrc)
hermes # start chatting!
Troubleshooting
Windows Defender or antivirus flags uv.exe as malware
If your antivirus (Bitdefender, Windows Defender, etc.) quarantines uv.exe from the Hermes bin folder (%LOCALAPPDATA%\hermes\bin\uv.exe), this is a false positive. The file is Astral's uv — the Rust Python package manager Hermes bundles to manage its Python environment. ML-based antivirus engines commonly flag unsigned Rust binaries that download and install packages.
To verify your copy is authentic:
# Install GitHub CLI if needed
winget install --id GitHub.cli
# Login to GitHub
gh auth login
# Run verification
$uv = "$env:LOCALAPPDATA\hermes\bin\uv.exe"
$ver = (& $uv --version).Split(' ')[1]
[Net.ServicePointManager]::SecurityProtocol = [Net.SecurityProtocolType]::Tls12
$zip = "$env:TEMP\uv.zip"
Invoke-WebRequest "https://github.com/astral-sh/uv/releases/download/$ver/uv-x86_64-pc-windows-msvc.zip" -OutFile $zip -UseBasicParsing
gh attestation verify $zip --repo astral-sh/uv
Expand-Archive $zip "$env:TEMP\uv_x" -Force
(Get-FileHash "$env:TEMP\uv_x\uv.exe").Hash -eq (Get-FileHash $uv).Hash
If attestation says "Verification succeeded" and the last line prints True, you're good.
To whitelist Hermes:
- Windows Defender: Run PowerShell as Admin →
Add-MpPreference -ExclusionPath "$env:LOCALAPPDATA\hermes\bin" - Bitdefender: Add an exception in the Bitdefender console (Protection > Antivirus > Settings > Manage Exceptions)
- Whitelist the folder, not the file hash — Hermes updates
uvand the hash changes every version
For more context, see the upstream Astral reports: astral-sh/uv#13553, astral-sh/uv#15011, astral-sh/uv#10079.
Getting Started
hermes # Interactive CLI — start a conversation
hermes model # Choose your LLM provider and model
hermes tools # Configure which tools are enabled
hermes config set # Set individual config values
hermes config get # Print individual config values
hermes gateway # Start the messaging gateway (Telegram, Discord, etc.)
hermes setup # Run the full setup wizard (configures everything at once)
hermes claw migrate # Migrate from OpenClaw (if coming from OpenClaw)
hermes update # Update to the latest version
hermes doctor # Diagnose any issues
Skip the API-key collection — Nous Portal
Hermes works with whatever provider you want — that's not changing. But if you'd rather not collect five separate API keys for the model, web search, image generation, TTS, and a cloud browser, Nous Portal covers all of them under one subscription:
- 300+ models — pick any of them with
/model <name> - Tool Gateway — web search, image generation (FAL), text-to-speech (OpenAI), cloud browser (Browser Use), all routed through your sub. No extra accounts.
One command from a fresh install:
hermes setup --portal
That logs you in via OAuth, sets Nous as your provider, and turns on the Tool Gateway. Check what's wired up any time with hermes portal info. Full details on the Tool Gateway docs page.
You can still bring your own keys per-tool whenever you want — the gateway is per-backend, not all-or-nothing.
CLI vs Messaging Quick Reference
Hermes has two entry points: start the terminal UI with hermes, or run the gateway and talk to it from Telegram, Discord, Slack, WhatsApp, Signal, or Email. Once you're in a conversation, many slash commands are shared across both interfaces.
| Action | CLI | Messaging platforms |
|---|---|---|
| Start chatting | hermes |
Run hermes gateway setup + hermes gateway start, then send the bot a message |
| Start fresh conversation | /new or /reset |
/new or /reset |
| Change model | /model [provider:model] |
/model [provider:model] |
| Set a personality | /personality [name] |
/personality [name] |
| Retry or undo the last turn | /retry, /undo |
/retry, /undo |
| Compress context / check usage | /compress, /usage, /insights [--days N] |
/compress, /usage, /insights [days] |
| Browse skills | /skills or /<skill-name> |
/<skill-name> |
| Interrupt current work | Ctrl+C or send a new message |
/stop or send a new message |
| Platform-specific status | /platforms |
/status, /sethome |
For the full command lists, see the CLI guide and the Messaging Gateway guide.
Documentation
All documentation lives at hermes-agent.nousresearch.com/docs:
| Section | What's Covered |
|---|---|
| Quickstart | Install → setup → first conversation in 2 minutes |
| CLI Usage | Commands, keybindings, personalities, sessions |
| Configuration | Config file, providers, models, all options |
| Messaging Gateway | Telegram, Discord, Slack, WhatsApp, Signal, Home Assistant |
| Security | Command approval, DM pairing, container isolation |
| Tools & Toolsets | 40+ tools, toolset system, terminal backends |
| Skills System | Procedural memory, Skills Hub, creating skills |
| Memory | Persistent memory, user profiles, best practices |
| MCP Integration | Connect any MCP server for extended capabilities |
| Cron Scheduling | Scheduled tasks with platform delivery |
| Context Files | Project context that shapes every conversation |
| Architecture | Project structure, agent loop, key classes |
| Contributing | Development setup, PR process, code style |
| CLI Reference | All commands and flags |
| Environment Variables | Complete env var reference |
Migrating from OpenClaw
If you're coming from OpenClaw, Hermes can automatically import your settings, memories, skills, and API keys.
During first-time setup: The setup wizard (hermes setup) automatically detects ~/.openclaw and offers to migrate before configuration begins.
Anytime after install:
hermes claw migrate # Interactive migration (full preset)
hermes claw migrate --dry-run # Preview what would be migrated
hermes claw migrate --preset user-data # Migrate without secrets
hermes claw migrate --overwrite # Overwrite existing conflicts
What gets imported:
- SOUL.md — persona file
- Memories — MEMORY.md and USER.md entries
- Skills — user-created skills →
~/.hermes/skills/openclaw-imports/ - Command allowlist — approval patterns
- Messaging settings — platform configs, allowed users, working directory
- API keys — allowlisted secrets (Telegram, OpenRouter, OpenAI, Anthropic, ElevenLabs)
- TTS assets — workspace audio files
- Workspace instructions — AGENTS.md (with
--workspace-target)
See hermes claw migrate --help for all options, or use the openclaw-migration skill for an interactive agent-guided migration with dry-run previews.
Contributing
We welcome contributions! See the Contributing Guide for development setup, code style, and PR process.
Start with the PM developer workflow for activation, daily use, dependency changes, and leaving the environment. Development Setup covers the separate test environment and verification commands.
Community
- 💬 Discord
- 📚 Skills Hub
- 🐛 Issues
- 🔌 computer-use-linux — Linux desktop-control MCP server for Hermes and other MCP hosts, with AT-SPI accessibility trees, Wayland/X11 input, screenshots, and compositor window targeting.
- 🔌 HermesClaw — Community WeChat bridge: Run Hermes Agent and OpenClaw on the same WeChat account.
License
MIT — see LICENSE.
Built by Nous Research.