Setting up a Hermes team

If you've deployed one Hermes instance and now want more than one agent working together, this page is the on-ramp. It explains the idea in plain terms first, then walks you through the two team shapes you can build, with the smallest possible example of each. For the exhaustive protocol, every knob, and the live-verified evidence, see Hermes teams and Hermes collaboration - this page exists to get you oriented before you read those.

The one thing to understand first

You cannot make one Hermes "bigger" by raising replicaCount. Hermes Agent is a personal agent: one identity, one memory, one home directory, one gateway process. Extra replicas either sit Pending (they fight over the same disk) or become totally separate, disconnected agents that don't know about each other.

So a "team" in this chart is never one deployment scaled out. It is always several independent single instances, each its own Helm release, joined together by something they share - most commonly, one Discord channel or thread. Think of it less like scaling a server and more like hiring a second person: they get their own desk (PVC), their own identity, and you introduce them to the same group chat.

Two shapes, pick based on what you need

	Pair collaboration	Leader-orchestrated team
Who talks to whom	Any agent may address any other agent	Only the leader talks to the human; members only ever answer the leader
Shape	Flat: two (or a few) peers	Star: one leader, N members
Best for	A quick two-role pairing (e.g. planner + builder) that you'll watch closely	A repeatable, larger roster where you want one predictable point of contact
Where it's documented	collaboration.md	teams.md
Values files	values-multi-agent-collab.yaml	values-team-leader.yaml / values-team-member.yaml

Neither is "more advanced" than the other - pick the shape that matches how you want the conversation to flow. A flat pair is simpler to reason about with two agents; once you're past two or three, the leader shape keeps the human from having to track who's doing what.

Quick start: a collaborating pair

Two independent releases, one shared Discord channel, and an explicit @mention as the handoff signal.

1. Create two bots in the Discord Developer Portal, enable the Message Content Intent on both, and invite both to the same channel. Note each bot's Discord user ID - each agent needs to know its partner's ID to mention them.
2. Install both, pointing each at values-multi-agent-collab.yaml with its own bot token and its partner's ID filled into environment_hint:

helm upgrade --install hermes-planner ./charts/hermes-agent \
  --namespace hermes-team --create-namespace \
  -f charts/hermes-agent/values-multi-agent-collab.yaml \
  --set-string env.DISCORD_BOT_TOKEN='<planner-bot-token>' --wait

helm upgrade --install hermes-builder ./charts/hermes-agent \
  --namespace hermes-team --create-namespace \
  -f charts/hermes-agent/values-builder.yaml \
  --set-string env.DISCORD_BOT_TOKEN='<builder-bot-token>' --wait

1. Talk to either bot in the channel. Ask the planner to scope something; when it hands off with <@builder> in its reply, the builder picks it up automatically. When a topic wraps up, the agent that's finishing addresses you instead of mentioning its partner - that's what stops the exchange.

That's the whole loop. The full recipe - why four specific Discord environment variables are what makes "stop mentioning when you're done" actually enforceable, and how to scale past two agents - is in collaboration.md.

Quick start: a leader-orchestrated team

One leader the human always talks to, and members who only ever act on an explicit mention from the leader.

sequenceDiagram
    participant H as You
    participant L as Leader
    participant M as Member

    H->>L: "@leader do X"
    L->>M: "<@member> here's your task"
    M->>L: "<@leader> here's the result"
    L-->>H: final answer, no member mention

1. Provision a shared knowledge volume (optional but recommended): an ReadWriteMany PVC named hermes-team-knowledge that the leader writes to and members read. It's for durable reference material, never for live task state; the Discord thread is what actually carries the work.
2. Install the leader, then one release per member, all pointed at the same Discord channel:

helm upgrade --install hermes-august ./charts/hermes-agent \
  --namespace hermes-team --create-namespace \
  -f charts/hermes-agent/values-team-leader.yaml \
  --set-string env.DISCORD_BOT_TOKEN='<leader-bot-token>' --wait

helm upgrade --install hermes-may ./charts/hermes-agent \
  --namespace hermes-team \
  -f charts/hermes-agent/values-team-member.yaml \
  --set-string env.DISCORD_BOT_TOKEN='<member-bot-token>' --wait

1. Give the leader a goal in the channel. It delegates to one member at a time, waits for that member's reply, reviews it, and either asks for a revision or moves to the next member. When everything's satisfied, it answers you directly with no member mention - that's the signal the run is done. examples/argocd/hermes-team.yaml has the declarative (ArgoCD) version of the same roster if you'd rather not run helm install by hand.

The full protocol - the exact delegation message format, why the loop brake needs four specific env vars, and what's actually been proven live on a real cluster - is in Hermes teams.

Why the safety rails exist

Hermes has no built-in limiter on bot-to-bot conversation - two agents that can see and mention each other will, left unchecked, ping-pong forever. Every team pattern on this page relies on the same two-layer brake to make "stop" actually happen:

• A prompt instruction: each agent is told explicitly when not to mention a partner (when a topic is resolved, address the human instead).
• Four Discord environment variables that make the only way to trigger a partner an explicit <@id> written into the message body - not a reply, not passive presence in a thread, nothing implicit. This closes off the subtle way Discord replies otherwise auto-ping the previous sender and restart the loop by accident.

This is called out everywhere as experimental and not an upstream-supported topology - treat it as a recipe with mitigations, not a guarantee, and keep these bots in a channel you can watch.

Other platforms: Telegram and Slack

Everything above uses Discord, which is the only platform with a live-proven multi-bot run behind it. The protocol itself is platform-independent, though: what changes is how you write a mention and which environment variables close the loop:

	Discord	Telegram	Slack
Mention format	<@USER_ID>	@username (must end in bot)	<@USER_ID>: identical to Discord
Loop-brake knobs	4	3	2
The one to not miss	DISCORD_REPLY_TO_MODE=off	TELEGRAM_REPLY_TO_MODE=off	SLACK_STRICT_MENTION=true
Live-proven	✅	⚠️ config-verified only	⚠️ config-verified only

Slack is the easiest port (same mention markup, so environment_hint text carries over unchanged); Telegram needs @username tokens instead of numeric IDs plus one extra instruction telling agents never to use Telegram's native "reply" to address a teammate.

Full knob-by-knob mapping and worked config for both is in collaboration.md § Beyond Discord (pair) and teams.md § Telegram and Slack (leader team).

What's actually been proven, not just documented

Two live runs on a real kind cluster (pinned Hermes image v2026.7.20) completed the full leader → member → member → leader route end-to-end, with no member mention on the final answer - confirming the loop genuinely terminates. See teams.md § Live evidence for both Discord thread links and timings.

Where to go from here

• Hermes teams - the complete reference: the "why a single instance" rationale, the ArgoCD ApplicationSet pattern for larger rosters, and the full leader-team protocol.
• Hermes collaboration: the complete pair recipe: mixed model backends, where partner IDs should live (declarative vs. learned in conversation), and the multi-agent ApplicationSet variant.
• Roadmap: what's proven vs. still in progress across both team shapes.