Skip to main content

Documentation Index

Fetch the complete documentation index at: https://www.rumus.ai/docs/llms.txt

Use this file to discover all available pages before exploring further.

The Rumus AI isn’t just a chat box that replies in words — it’s an agent that can take actions on your behalf. When you ask “find the largest files under /var/log”, the agent doesn’t just suggest a command, it proposes one and runs it (with your approval), then reads the output and answers based on what it actually saw.

​
What the agent can do

The agent’s core toolkit:
ToolWhat it does
Run commandExecute a shell command in your active terminal — local or remote
Read fileOpen a file and put its contents into the conversation
Write fileCreate or overwrite a file with new content
Edit fileMake targeted edits to existing files
Web fetchPull a specific URL — see Web search for broader search
Web searchQuery the web for information — see Web search
MCP toolsAnything you’ve connected via Model Context Protocol — see MCP
Create planAuto-draft a multi-step plan for larger jobs — see Plan mode
Spawn sub-agentFan out independent work in parallel — see Sub-agents

​
The execution loop

When you send a prompt, the agent:
  1. Reads your message and any context (active terminal, attached files, your rules and skills).
  2. Decides what to do — answer directly, or call a tool.
  3. If a tool is called, requests approval if needed (see Command approval), runs the tool, and reads the result.
  4. Loops back — keeps calling tools until the job is done or it hits the iteration cap.
  5. Replies to you with what it learned and did.
The iteration cap (default 20 tool calls per turn) prevents runaway loops. You can adjust it under Settings → AI → Conversation.

​
How tool calls render in the sidebar

Each tool call shows up inline in the conversation as a collapsible block:
  • The tool name and arguments at the top.
  • The status: pending → running → succeeded / failed.
  • The result — for commands, the captured stdout / stderr; for file reads, the contents; for web fetches, the page text.
  • A small info icon with token / timing details.
Click the block header to expand or collapse. Long results auto-collapse to keep the conversation scannable.

​
Cancelling

If a tool call is taking too long, or the agent is heading the wrong way, hit Stop generating. The agent finishes the current tool call and stops; partial work is preserved in the conversation.

​
Approval gates

The agent’s tools fall into three approval categories:
  • Always allowed — read-only or low-risk operations (read file, web fetch).
  • Approval-required — anything that changes state by default (run command, write file, edit file). You can pre-approve patterns; see Command approval.
  • Blocked — explicitly forbidden patterns the agent will not run, even if you click approve. Configure under Settings → AI → Conversation → Command Control.

​
Where the agent runs commands

The “active terminal” is whichever terminal you most recently focused before opening / interacting with the AI sidebar. If you have prod and staging tabs open and you ask the agent to run restart, double-check which tab is focused — the agent runs in that one. For multi-host fan-out, use multi-terminal broadcast directly rather than asking the agent to do it; broadcast is purpose-built for that case.

​
Tips for getting the most out of the agent

  • Be specific about scope. “Find why my service is failing” is fine, but “Find why nginx is failing on prod-web-1; check /var/log/nginx/error.log for the last hour” gets you there faster.
  • Tell it to plan first when the job is bigger than a single command. Or just give it a complex job and let plan mode trigger automatically.
  • Use skills to encode the multi-step procedures you do regularly — the agent invokes them by name when relevant.
  • Switch models per task. Reasoning-heavy work (debugging tricky failures) often benefits from a stronger model; high-volume routine ops can run on a faster, cheaper one. The picker remembers your choice per conversation.

​
Next steps

Plan mode

What auto-planning does and how to read the resulting checklist.

Command approval

Pre-approve safe patterns so the agent doesn’t pause for ls.

Sub-agents

When the agent spawns parallel workers for independent tasks.

MCP

Give the agent access to your own tools.