24d48ffb82
* feat(kanban): add `specify` — auxiliary LLM fleshes out triage tasks
The Triage column shipped with a placeholder 'a specifier will flesh
out the spec', but the specifier itself was never built. This wires
it up as a dedicated CLI verb.
`hermes kanban specify <id>` calls the auxiliary LLM (configured under
`auxiliary.triage_specifier`) to expand a rough one-liner into a
concrete spec — tightened title plus a body with Goal / Approach /
Acceptance criteria / Out-of-scope sections — then atomically flips
`status: triage -> todo` and recomputes ready so parent-free tasks
go straight to the dispatcher on the same tick.
Surface:
hermes kanban specify <task_id> # single task
hermes kanban specify --all [--tenant T] # sweep triage column
hermes kanban specify ... --author NAME # audit-comment author
hermes kanban specify ... --json # one JSON line per task
Design choices:
- Parent gating is preserved. specify_triage_task flips to 'todo',
then recompute_ready promotes to 'ready' only when parents are
done — same rule as a normal parent-gated todo.
- No daemon, no background watcher. Every invocation is explicit —
keeps cost predictable and doesn't fight the dispatcher loop.
- Response parse is lenient: strict JSON preferred, markdown-fence
tolerated, raw-body fallback on malformed JSON so the LLM can't
strand a task in triage.
- All failure modes (no aux client, API error, task moved out of
triage mid-call) return SpecifyOutcome(ok=False, reason=...) so
--all continues past individual failures.
Changes:
hermes_cli/kanban_db.py + specify_triage_task()
hermes_cli/kanban_specify.py NEW (~220 LOC — prompt, parse, call)
hermes_cli/kanban.py + specify subcommand + _cmd_specify
hermes_cli/config.py + auxiliary.triage_specifier task slot
website/docs/user-guide/features/kanban.md specify + config notes
website/docs/reference/cli-commands.md CLI reference entry
tests/hermes_cli/test_kanban_specify_db.py NEW (10 tests)
tests/hermes_cli/test_kanban_specify.py NEW (20 tests)
Validation: 30/30 targeted tests pass. E2E: triage task -> specify ->
ends in 'ready' with events [created, specified, promoted] and the
audit comment recorded under the configured author.
* feat(kanban): wire specifier into dashboard and gateway slash
Follow-ups to the initial PR #21435 — closes the two gaps I'd left as
post-merge: dashboard button and first-class gateway surface.
Dashboard (plugins/kanban/dashboard/)
- POST /tasks/:id/specify NEW endpoint. Thin wrapper around
kanban_specify.specify_task(). Returns the CLI outcome shape
({ok, task_id, reason, new_title}); ok=false with a human reason
is a 200, not a 4xx, so the UI can render it inline without
treating 'no aux client configured' as a crash.
- Runs sync in FastAPI's threadpool because the LLM call can take
tens of seconds on reasoning models.
- Pins HERMES_KANBAN_BOARD around the specify call so the module's
argless kb.connect() lands on the right board.
- dist/index.js: doSpecify callback threaded through the drawer →
TaskDetail → StatusActions prop chain. ✨ Specify button appears
ONLY when task.status === 'triage' (elsewhere the backend would
reject anyway — hide the button to keep the action row clean).
Busy state (Specifying…) + inline success/error banner under the
button using the response.reason text.
- dist/style.css: tiny hermes-kanban-msg-ok / -err classes using
existing --color vars so themes reskin cleanly.
Gateway slash (/kanban specify)
- Already works via the existing run_slash → build_parser →
kanban_command pipeline. No code change needed — slash commands
inherit the argparse tree automatically. Added coverage:
test_run_slash_specify_end_to_end (create --triage, specify, verify
promotion + retitle) and test_run_slash_specify_help_is_reachable.
Tests
- tests/plugins/test_kanban_dashboard_plugin.py: 3 new tests for the
REST endpoint — happy path, non-triage rejection as ok=false 200,
missing aux client as ok=false 200.
- tests/hermes_cli/test_kanban_cli.py: 2 new slash-surface tests.
Docs
- website/docs/user-guide/features/kanban.md: dashboard action row
description mentions ✨ Specify + all three surfaces. REST table
gains /tasks/:id/specify. Slash examples include /kanban specify.
Validation: 340/340 targeted tests pass. E2E via TestClient: create a
triage task over REST → POST /specify with mocked aux client → task
moves to 'ready' column on /board with new title and body applied.
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
curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
Works on Linux, macOS, WSL2, and Android via Termux. The installer handles the platform-specific setup for you.
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 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> |
/<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.