4.2 KiB
4.2 KiB
Hermes Agent Masterclass — Tonbi Studio
Source: @tonbistudio tweet 2095877834409644064
Captured: 2026-09-13
Topic: Hermes configuration, workflow, optimization
Tags: #hermes #masterclass #workflow #skills #agents #configuration
Overview
Tonbi Studio's Hermes Agent Masterclass is a 10-part video course (5h 14m) taking Hermes from fresh install to hardened multi-agent team. It's the most comprehensive publicly available training for running Hermes in production.
- hermesatlas.com/masterclass — video + transcript notes
- hermesbible.com — unofficial docs companion
- hermesatlas.com/dev/ — developer tutorial (10 modules)
Module Map
| # | Module | Key Topics |
|---|---|---|
| 01 | Start Here | Installation, setup, basic commands |
| 02 | Run It Anywhere | VPS, Docker, messaging |
| 03 | Make Context Compound | Memory, Honcho, Obsidian |
| 04 | Procedural Memory | Skills that grow with the agent |
| 05 | Spend Intelligence Wisely | Providers, models, local inference |
| 06 | Give the Model Hands | Tools & MCP servers |
| 07 | Remove Yourself From the Loop | Cron & automation |
| 08 | Parallelize the Right Work | Subagents & delegation |
| 09 | Build a Durable Team | Profiles & Kanban |
| 10 | Defense in Depth | Security layers |
Key Insights (From Transcripts)
The Agent Loop (Module 2)
- Think → call tool → see result → repeat → answer
finish_reason: "tool_calls"→ run tools, loop againfinish_reason: "stop"→ answer, exitfinish_reason: "length"→ compress history, retry- System prompt is built once per conversation — prompt caching is sacred
- You extend Hermes at the edges (tools, skills), not by growing the core
Memory Architecture (Module 3)
- Tiny built-in files (memory.md, user.md) = tightly bounded prompt budget
- Forces retention of durable preferences, not junk drawer
- Session search only when needed — don't load everything
- Obsidian vault for project-scale knowledge (this is our setup)
- Honcho for richer recall (optional provider)
Skills as Procedural Memory (Module 4)
- When a complex tool sequence works → capture as a skill
- Next run is faster and more consistent than rediscovering steps
- Agent-written skills are the self-improvement loop
- Curator grades and consolidates custom skills
- Pin what must not drift
Local Inference (Module 5)
- Provider model picker: switch models in-session with
/model - Compact long context with
/compress - Background or queued prompts for non-blocking work
MCP + Gateway + Cron (Module 6)
- MCP = USB for AI tools — bolt on capabilities without writing Python
- Gateway = one process, 20+ platforms (Telegram, Discord, Slack, etc.)
- Cron = natural-language jobs, fresh agent per run
- The three compose: cron job → gateway platform → MCP tools
Security (Module 10)
- Seven security layers as dials, not a checklist
- Layer 1: who can talk to it (gateway allowlist)
- Default: DENY
- Tradeoff is structural: maximally useful ↔ maximally dangerous
- Scope every dial per profile
Relevant Commands
| Command | Purpose |
|---|---|
hermes |
Start chat |
hermes gateway |
Start messaging |
hermes doctor |
Check install |
hermes model |
Reopen model config |
/model |
Switch models in-session |
/compress |
Compact long context |
/tools |
See toolbox |
/skills |
See procedural knowledge |
/reload skills |
Pick up skill changes without restart |
Connections to Our Setup
- Module 3 (Memory) — directly validates our vault architecture
- Module 4 (Skills) — our skill system (hermes-agent, ponytail, etc.) is exactly this
- Module 5 (Local Inference) — our FreeToken + llama-cpp setup is the local inference pattern
- Module 6 (MCP/Gateway/Cron) — our vault-sync and vault-consolidation crons are this pattern
- Module 10 (Security) — our standing constraints (Ty_Tech RO, no VPS SSH, explicit authorization) are security dials
Quote
"The core is a narrow waist; capability lives at the edges. Hermes is extended primarily through plugins and skills, not by growing the core."