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* fix(curator): authoritative absorbed_into declarations on skill delete Closes #18671. The classification pipeline that feeds cron-ref rewriting used to infer consolidation vs pruning from two brittle signals: the curator model's post-hoc YAML summary block, and a substring heuristic scanning other tool calls for the removed skill's name. Both miss in real consolidations — the model forgets the YAML under reasoning pressure, and the heuristic misses when the umbrella's patch content describes the absorbed behavior abstractly instead of naming the old slug. When both miss, the skill falls through to 'no-evidence fallback' pruned, and #18253's cron rewriter drops the cron ref entirely instead of mapping it to the umbrella. Same observable symptom as pre-#18253: 'Skill(s) not found and skipped' at the next cron run. The fix makes the model declare intent at the moment of deletion. skill_manage(action='delete') now accepts absorbed_into: - absorbed_into='<umbrella>' -> consolidated, target must exist on disk - absorbed_into='' -> explicit prune, no forwarding target - missing -> legacy path, falls through to heuristic/YAML The curator reconciler reads these declarations off llm_meta.tool_calls BEFORE either the YAML block or the substring heuristic. Declaration wins. Fallback logic stays intact for backward compat with any caller (human or older curator conversation) that doesn't populate the arg. Changes - tools/skill_manager_tool.py: add absorbed_into param to skill_manage + _delete_skill. Validate target exists when non-empty. Reject absorbed_into=<self>. Wire through dispatcher + registry + schema. - agent/curator.py: new _extract_absorbed_into_declarations() walks tool calls for skill_manage(delete) with the arg. _reconcile_classification accepts absorbed_declarations= and treats them as authoritative. Curator prompt updated to require the arg on every delete. - Tests: 7 new skill_manager tests covering the tool contract (valid target, empty string, nonexistent target, self-reference, whitespace, backward compat, dispatcher plumbing). 11 new curator tests covering the extractor + authoritative reconciler path + mixed-legacy-and- declared runs. Validation - 307/307 targeted tests pass (curator + cron + skill_manager suites). - E2E #18671 repro: 3 narrow skills, 1 umbrella, cron job referencing all 3. Model emits NO YAML block. Heuristic misses (patch prose doesn't name old slugs). Delete calls carry absorbed_into. Result: both PR skills correctly classified 'consolidated' + cron rewritten ['pr-review-format', 'pr-review-checklist', 'stale-junk'] -> ['hermes-agent-dev']; stale-junk pruned via absorbed_into=''. - E2E backward-compat: delete without absorbed_into, model emits YAML -> routed via existing 'model' source, cron still rewritten correctly. * feat(curator): capture + restore cron skill links across snapshot/rollback Before this, rolling back a curator run restored the skills tree but cron jobs still pointed at the umbrella skills the curator had rewritten them to. The user would see their old narrow skills back on disk but their cron jobs still configured with the merged umbrella — not actually 'back to how it was'. Snapshot side: snapshot_skills() now captures ~/.hermes/cron/jobs.json alongside the skills tarball, as cron-jobs.json. The manifest gets a new 'cron_jobs' block with {backed_up, jobs_count} so rollback (and the CLI confirm dialog) can surface what's in the snapshot. If jobs.json is missing/unreadable/malformed, snapshot proceeds without cron data — the skills backup is the core guarantee; cron is additive. Rollback side: after the skills extract succeeds, the new _restore_cron_skill_links() reconciles the backed-up jobs into the live jobs.json SURGICALLY. Only 'skills' and 'skill' fields are restored, and only on jobs matched by id. Everything else about a cron job — schedule, last_run_at, next_run_at, enabled, prompt, workdir, hooks — is live state the user or scheduler has modified since the snapshot; overwriting it would regress unrelated activity. Reconciliation rules: - Job in backup AND live, skills differ → skills restored. - Job in backup AND live, skills match → no-op. - Job in backup, NOT in live → skipped (user deleted it after snapshot; their choice is later than the snapshot). - Job in live, NOT in backup → untouched (user created it after snapshot). - Snapshot missing cron-jobs.json at all → rollback still succeeds, reports 'not captured' (older pre-feature snapshots keep working). Writes go through cron.jobs.save_jobs under the same _jobs_file_lock the scheduler uses, so rollback doesn't race tick(). Also: - hermes_cli/curator.py: rollback confirm dialog now shows 'cron jobs: N (will be restored for skill-link fields only)' when the snapshot has cron data, or 'not in snapshot (<reason>)' otherwise. - rollback()'s message string includes a 'cron links: ...' clause summarizing the reconciliation outcome. Tests - 9 new cases: snapshot-with-cron, snapshot-without-cron, malformed-json captured-as-raw, full rollback-restores-skills-and-cron, rollback touches only skill fields, rollback skips user-deleted jobs, rollback leaves user-created jobs untouched, rollback still works with pre-feature snapshot that has no cron-jobs.json, standalone unit test on _restore_cron_skill_links exercising the full report shape. Validation - 484/484 targeted tests pass (curator + cron + skill_manager suites). - E2E: real snapshot_skills, real cron rewrite, real rollback. Before: ['pr-review-format', 'pr-review-checklist', 'pr-triage-salvage']. After curator: ['hermes-agent-dev']. After rollback: ['pr-review-format', 'pr-review-checklist', 'pr-triage-salvage']. Non-skill fields (id, name, prompt) preserved across the round trip.
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 | 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, 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/) ships via theatroposlibandtinkerdependencies pulled in by.[all,dev]— no submodule setup required.
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.