404640a2b7
* feat(goals): /goal checklist + /subgoal user controls
Two-phase judge for /goal — Phase A decomposes the goal into a detailed
checklist on first turn; Phase B evaluates each pending item harshly
against the agent's most recent response. The goal completes only when
every item is in a terminal status (completed or impossible). Adds
/subgoal so the user can append, complete, mark impossible, undo,
remove, or clear items the judge missed or got wrong.
Mechanics:
- GoalState gains `checklist` and `decomposed` fields, both backwards
compatible (old state_meta rows load unchanged).
- Phase A: aux call writes a harsh, exhaustive checklist; biased toward
more items not fewer. Falls through to legacy freeform judge when
decompose fails.
- Phase B: judge gets the checklist + last-response snippet + path to
a per-session conversation dump at <HERMES_HOME>/goals/<sid>.json.
A bounded read_file tool (max 5 calls per turn, restricted to that
one file) lets the judge inspect history when the snippet is
ambiguous. Stickiness in code: terminal items are frozen, only the
user can revert via /subgoal undo.
- Continuation prompt shows checklist progress when non-empty;
reverts to old prompt when empty.
- Status line shows M/N done counts.
CLI + gateway + TUI gateway all pass the agent reference into
evaluate_after_turn so the dump can be written. Gateway-side
/subgoal is allowed mid-run since it only modifies the checklist
the judge consults at turn boundaries.
Tests: 24 new cases — backcompat round-trip, Phase A decompose,
Phase B updates + new_items + stickiness, user override flows,
conversation dump (incl. unsafe-sid sanitization), judge read_file
restriction. Existing freeform-mode tests updated to patch the
renamed `judge_goal_freeform` and skip Phase A explicitly.
* fix(goals): off-by-one in judge index, message-list plumbing, prompt tuning
Three live-test findings from running /goal end-to-end against
gemini-3-flash-preview as the judge:
1. Off-by-one bug — the judge sees the checklist rendered with 1-based
indices ('1. [ ] foo, 2. [ ] bar') but the apply layer indexed
state.checklist as 0-based. Result: every judge update landed on
the wrong item, evidence got attached to neighbouring rows, and
the genuine 'first pending' item (usually #1) never got marked.
Fix: convert 1 → 0 in _parse_evaluate_response. Also tightened the
user prompt to call out the 1-based scheme explicitly. New tests
cover the parser conversion + an end-to-end fake-judge round-trip.
2. Conversation dump never happened — _extract_agent_messages tried
common AIAgent attribute names (.messages, .conversation_history,
etc.) but AIAgent doesn't expose the message list as an instance
attribute; it lives inside run_conversation()'s scope. Result: the
judge's read_file tool always saw history_path=unavailable. Fix:
added an explicit messages= kwarg to evaluate_after_turn that all
three call sites (CLI, gateway, TUI gateway) now pass directly.
Agent-attribute extraction kept as back-compat fallback.
3. Prompt was too harsh on simple goals. The original 'be HARSH,
default to leaving items pending' wording made the judge refuse
to mark 'file exists' completed even after the agent ran ls,
test -f, os.path.isfile, and find — burning the entire 8-turn
budget on a fizzbuzz task. Softened to 'strict but not absurd'
with explicit guidance on what counts as evidence and a directive
not to require re-proving items already established earlier.
Re-tested live with the same fizzbuzz goal: now terminates in 2
turns with all 8 checklist items correctly attributed to their
own evidence. /subgoal user-action flow (add / complete / undo /
impossible) verified live as well.
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 (200+ models), NVIDIA NIM (Nemotron), Xiaomi MiMo, z.ai/GLM, Kimi/Moonshot, MiniMax, Hugging Face, OpenAI, or your own endpoint. 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, Atropos RL environments, trajectory compression for training the next generation of tool-calling models. |
Quick Install
Linux, macOS, WSL2, Termux
curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
Windows (native, PowerShell) — Early Beta
Heads up: Native Windows support is early beta. It installs and runs, but hasn't been road-tested as broadly as our Linux/macOS/WSL2 paths. Please file issues when you hit rough edges. For the most battle-tested Windows setup today, run the Linux/macOS one-liner above inside WSL2.
Run this in PowerShell:
irm https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.ps1 | iex
The installer handles everything: uv, Python 3.11, Node.js, ripgrep, ffmpeg, and a portable Git Bash (MinGit, unpacked to %LOCALAPPDATA%\hermes\git — no admin required, completely isolated from any system Git install). Hermes uses this bundled Git Bash to run shell commands.
If you already have Git installed, the installer detects it and uses that instead. Otherwise a ~45MB MinGit download is all you need — it won't touch or interfere with any system Git.
Android / Termux: The tested manual path is documented in the Termux guide. On Termux, Hermes installs a curated
.[termux]extra because the full.[all]extra currently pulls Android-incompatible voice dependencies.Windows: Native Windows is supported as an early beta — the PowerShell one-liner above installs everything, but expect rough edges and please file issues when you hit them. If you'd rather use WSL2 (our most battle-tested Windows path), the Linux command works there too. Native Windows install lives under
%LOCALAPPDATA%\hermes; WSL2 installs under~/.hermesas on Linux. The only Hermes feature that currently needs WSL2 specifically is the browser-based dashboard chat pane (it uses a POSIX PTY — classic CLI and gateway both run natively).
After installation:
source ~/.bashrc # reload shell (or: source ~/.zshrc)
hermes # start chatting!
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 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
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.
Quick start for contributors — clone and go with setup-hermes.sh:
git clone https://github.com/NousResearch/hermes-agent.git
cd hermes-agent
./setup-hermes.sh # installs uv, creates venv, installs .[all], symlinks ~/.local/bin/hermes
./hermes # auto-detects the venv, no need to `source` first
Manual path (equivalent to the above):
curl -LsSf https://astral.sh/uv/install.sh | sh
uv venv .venv --python 3.11
source .venv/bin/activate
uv pip install -e ".[all,dev]"
scripts/run_tests.sh
RL Training (optional): The RL/Atropos integration (
environments/) — seeCONTRIBUTING.mdfor the full setup.
Community
- 💬 Discord
- 📚 Skills Hub
- 🐛 Issues
- 🔌 HermesClaw — Community WeChat bridge: Run Hermes Agent and OpenClaw on the same WeChat account.
License
MIT — see LICENSE.
Built by Nous Research.