6a320e8bfe
* fix: prevent infinite 400 failure loop on context overflow (#1630) When a gateway session exceeds the model's context window, Anthropic may return a generic 400 invalid_request_error with just 'Error' as the message. This bypassed the phrase-based context-length detection, causing the agent to treat it as a non-retryable client error. Worse, the failed user message was still persisted to the transcript, making the session even larger on each attempt — creating an infinite loop. Three-layer fix: 1. run_agent.py — Fallback heuristic: when a 400 error has a very short generic message AND the session is large (>40% of context or >80 messages), treat it as a probable context overflow and trigger compression instead of aborting. 2. run_agent.py + gateway/run.py — Don't persist failed messages: when the agent returns failed=True before generating any response, skip writing the user's message to the transcript/DB. This prevents the session from growing on each failure. 3. gateway/run.py — Smarter error messages: detect context-overflow failures and suggest /compact or /reset specifically, instead of a generic 'try again' that will fail identically. * fix(skills): detect prompt injection patterns and block cache file reads Adds two security layers to prevent prompt injection via skills hub cache files (#1558): 1. read_file: blocks direct reads of ~/.hermes/skills/.hub/ directory (index-cache, catalog files). The 3.5MB clawhub_catalog_v1.json was the original injection vector — untrusted skill descriptions in the catalog contained adversarial text that the model executed. 2. skill_view: warns when skills are loaded from outside the trusted ~/.hermes/skills/ directory, and detects common injection patterns in skill content ("ignore previous instructions", "<system>", etc.). Cherry-picked from PR #1562 by ygd58. * fix(tools): chunk long messages in send_message_tool before dispatch (#1552) Long messages sent via send_message tool or cron delivery silently failed when exceeding platform limits. Gateway adapters handle this via truncate_message(), but the standalone senders in send_message_tool bypassed that entirely. - Apply truncate_message() chunking in _send_to_platform() before dispatching to individual platform senders - Remove naive message[i:i+2000] character split in _send_discord() in favor of centralized smart splitting - Attach media files to last chunk only for Telegram - Add regression tests for chunking and media placement Cherry-picked from PR #1557 by llbn. * fix(approval): show full command in dangerous command approval (#1553) Previously the command was truncated to 80 chars in CLI (with a [v]iew full option), 500 chars in Discord embeds, and missing entirely in Telegram/Slack approval messages. Now the full command is always displayed everywhere: - CLI: removed 80-char truncation and [v]iew full menu option - Gateway (TG/Slack): approval_required message includes full command in a code block - Discord: embed shows full command up to 4096-char limit - Windows: skip SIGALRM-based test timeout (Unix-only) - Updated tests: replaced view-flow tests with direct approval tests Cherry-picked from PR #1566 by crazywriter1. * fix(cli): flush stdout during agent loop to prevent macOS display freeze (#1624) The interrupt polling loop in chat() waited on the queue without invalidating the prompt_toolkit renderer. On macOS, the StdoutProxy buffer only flushed on input events, causing the CLI to appear frozen during tool execution until the user typed a key. Fix: call _invalidate() on each queue timeout (every ~100ms, throttled to 150ms) to force the renderer to flush buffered agent output. * fix(claw): warn when API keys are skipped during OpenClaw migration (#1580) When --migrate-secrets is not passed (the default), API keys like OPENROUTER_API_KEY are silently skipped with no warning. Users don't realize their keys weren't migrated until the agent fails to connect. Add a post-migration warning with actionable instructions: either re-run with --migrate-secrets or add the key manually via hermes config set. Cherry-picked from PR #1593 by ygd58. * fix(security): block sandbox backend creds from subprocess env (#1264) Add Modal and Daytona sandbox credentials to the subprocess env blocklist so they're not leaked to agent terminal sessions via printenv/env. Cherry-picked from PR #1571 by ygd58. --------- Co-authored-by: buray <ygd58@users.noreply.github.com> Co-authored-by: lbn <llbn@users.noreply.github.com> Co-authored-by: crazywriter1 <53251494+crazywriter1@users.noreply.github.com>
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), z.ai/GLM, Kimi/Moonshot, MiniMax, 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 | Six terminal backends — local, Docker, SSH, Daytona, Singularity, and Modal. 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
curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
Works on Linux, macOS, and WSL2. The installer handles everything — Python, Node.js, dependencies, and the hermes command. No prerequisites except git.
Windows: Native Windows is not supported. Please install WSL2 and run the command above.
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> |
/skills or /<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:
git clone https://github.com/NousResearch/hermes-agent.git
cd hermes-agent
git submodule update --init mini-swe-agent # required terminal backend
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]"
uv pip install -e "./mini-swe-agent"
python -m pytest tests/ -q
RL Training (optional): To work on the RL/Tinker-Atropos integration, also run:
git submodule update --init tinker-atropos uv pip install -e "./tinker-atropos"
Community
- 💬 Discord
- 📚 Skills Hub
- 🐛 Issues
- 💡 Discussions
License
MIT — see LICENSE.
Built by Nous Research.