Hermes
Two roles, same agent: internal courier (carrying intent between systems) and external receiver (catching what's emerging in the marketplace).
Hermes runs autonomous transactions — the agent that carries intent across systems without a human relay. At the system level, Hermes is also the reception layer: the agent that watches external signals (tool releases, research papers, changelog feeds) and surfaces what's arriving before the window closes.
Capabilities
Hermes is model-agnostic (18+ LLM providers), multi-platform (Telegram, Slack, Discord, CLI, and 14+ messaging platforms total), and ships with 47 built-in tools plus access to 643+ skills across research, productivity, ML, and automation categories.
Core capabilities for autonomous work:
| Capability | What it does | When to use |
|---|---|---|
| Persistent memory | Cross-session MEMORY.md + USER.md injected at start | Accumulating workflow rules, preferences, lessons |
| Cron scheduling | Isolated sessions firing on schedule | Monitoring feeds, follow-up drafts, daily briefings |
| Parallel delegation | Up to 3 concurrent subagents, depth limit 2 | Research workstreams, competitive analysis |
| Speech-to-text | Whisper (local, 99 languages, no API key) | Meeting transcription |
| Feed monitoring | blogwatcher + RSS/Atom | Industry signals, competitor tracking |
| Research | arxiv, polymarket, web_search, web_extract | Pre-meeting briefs, industry analysis |
| Workspace integration | Gmail, Calendar, Drive, Sheets via OAuth2 | Draft emails, calendar management |
| Live model switching | /model command changes model mid-session | Cost management, task-specific model selection |
| Background notify | notify_on_complete pings you when a job finishes | Long-running cron jobs, async research |
| Skills hub | hermes skills browse — 643+ community skills | Installing purpose-built procedures on demand |
Critical constraint: Cron jobs run in fresh sessions with no conversational memory. Prompts must be completely self-contained — include all file paths, context, and instructions explicitly.
Bounded memory is a design choice. MEMORY.md (2,200 chars) and USER.md (1,375 chars) are deliberately capped. The constraint forces consolidation: the agent must decide what is worth keeping, which produces tighter priors than unbounded memory. For long-term semantic memory, eight external providers (Hindsight, Honcho, Mem0, and others) plug in on top of the default SQLite layer.
Two-Agent System
Hermes and Claude Code divide work by boundary: Hermes crosses the boundary into the external world; Claude Code operates inside the repo.
| Hermes | Claude Code |
|---|---|
| Watches the world — blogs, feeds, research papers | Acts on the repo — docs, PRDs, plans |
| Runs while you sleep (cron) | Runs in active sessions |
| Produces structured files in a shared working directory | Reads those files, turns them into repo artifacts |
| External reception layer | Internal action layer |
The handoff is the filesystem. Hermes writes structured notes and research to a shared working directory. Claude Code picks them up on the next session and converts them into PRDs, industry analyses, or doc updates.
Context
- Autonomous Agents — the category Hermes belongs to
- Agentic Workflows — the orchestration layer above individual agents
- Work Charts — the templates Hermes executes
- Evolution — the loop Hermes's reception role feeds: variation → selection → retention
- AI Tools — the catalogue Hermes helps keep current via external signal monitoring
Links
- Official Guide
- Hermes Atlas — Ecosystem Map — 100+ community repos, quality-filtered
- Hermes Atlas Guide — beginner's handbook
- State of Hermes April 2026 — ecosystem overview
- Orange Book
- Complete Guide
- agentskills.io — open standard for cross-platform agent skills
- Nous Portal — single subscription for all supported models
Questions
What type of task is Hermes best suited to run without human confirmation — and where does that boundary break down?
- When a cron job runs in an isolated session with no memory of prior context, what is the minimum information it needs to produce useful output?
- How does Hermes's skill creation loop compound differently from a human learning the same procedure?
- At what point does the two-agent system create coordination overhead that exceeds the value of specialization?