Models, Reasoning Effort, and Cost

Choose a model connection, primary model, and reasoning effort, and understand what drives usage

An agent runs on your own model provider account. You pick a model tier and a reasoning effort per agent, and those choices, together with how long conversations run, shape both quality and cost.

Model connections

A model connection is an API key for your provider account. Add one under Settings > Connections > Models.

Providers	OpenRouter and OpenAI
Billing	Your provider account is billed for all agent usage
Key handling	Encrypted and used only on the server. Agents never see the key.
Multiple accounts	Add several connections per provider, for example one per team or budget
Rotation	Replace a key to rotate it, or revoke it to cut off access

Each agent uses one model connection. Subagents share their parent’s connection.

Primary model

Model	Best for
Astra	Complex reasoning and coordination
Terra	Balanced execution
Luna	Lightweight, focused tasks

Start with Terra for most channels. Choose Astra for channels that handle open-ended investigation or coordinate subagents. Choose Luna for narrow, high-volume work such as answering routine questions from the knowledge base.

Reasoning effort

Reasoning effort sets how much the model thinks before it answers: Low, Medium, High, or Extra high. Higher effort generally gives better answers on hard problems and uses more tokens and time per reply. Lower effort keeps simple exchanges fast and inexpensive.

Compaction threshold

The compaction threshold is the conversation size at which the agent summarizes older messages to make room. It applies to each session separately.

Default	64,000 tokens
Range	8,192 to 200,000 tokens

A lower threshold keeps each request smaller and compacts sooner. A higher threshold keeps more of the conversation verbatim before summarizing. The threshold is about conversation size; it is separate from the model’s maximum context window and from spending limits.

Subagents

With Allow subagents on, the agent can delegate parts of a request to helper agents. A typical setup is Astra coordinating several Terra helpers.

Setting	What it controls
Helper models	Which models helpers may use
Default helper model and effort	What a helper uses unless the agent picks otherwise
Max concurrent helpers	1 to 3 helpers running at once
Model-request budget	4 to 128 model requests per turn

Helpers share the parent’s model connection, Moxn identity, connector grants, and files. One request budget and one four-minute execution deadline cover the parent and all of its helpers together.

Keeping usage predictable

• Match the model to the channel. A Luna or Terra agent at Low or Medium effort is enough for most question-answering channels.
• Use task for independent work. A fresh session starts small instead of carrying the channel’s full history. See Working with the agent in Slack.
• Tune the compaction threshold. Lower it for busy channels where old conversation matters less.
• Bound subagents. Keep concurrency and the request budget low until you see the agent needs more.
• Use a dedicated connection. A separate key per agent or team makes usage easy to attribute in your provider’s dashboard.

Spending limits live in your provider account. The compaction threshold and the subagent limits shape how much work a turn does, but they are safety limits, not a dollar cap.