Skip to main content
The shortest route from a fresh install to seeing what makes Rundock different. Watch a real team work first, then build a smaller version of the same shape. If you have not yet installed Rundock or completed first-run setup, do those first: Installation, First-run setup.

​
Before you start

You need:
  • Rundock open with a workspace selected (the folder you picked during first-run).
  • A topic you know well enough to judge whether the writing is any good. Pick one before you start. The whole exercise depends on you being able to tell the difference between a good draft and a generic one.

​
1. See the team work

Rundock conversation: the user asks the orchestrator to shorten a landing hook, the orchestrator says it is handing the work to the Content Lead, and the Content Lead's reply streams in.

Talk to one agent and the team forms around the task: the orchestrator takes your request, hands it to the specialist who owns it, and the specialist's reply streams in. Hand-offs are visible in the panel.

This is the experience. A chatbot tries to do every job at once and produces something generic. A Rundock team specialises, hands off, and produces something specific. The conversation above shows a hand-off in action: you ask the orchestrator, it routes the task to the specialist who owns it, and the reply streams in as they work. You see who asked who, what was passed, and what came back, so when the work lands you know exactly which agent did what. Build a smaller version of this team in the next two steps. Both agents at once. The single-agent setup is the chatbot version, and that is not what Rundock is for.

​
2. Set up two agents at once

Create two agents. The first is the Content Writer; the second is the Researcher. There are two routes, and either one writes a markdown file per agent to your workspace:
  • Ask Doc. Open Doc from the team list (it sits under Rundock Agents), start a conversation, and ask it to create each agent, pasting in the details and instructions below.
  • Write the files yourself. Save each agent as .claude/agents/<name>.md, with the details below as its frontmatter and the instructions as the body of the file.
The Researcher reports to the Content Writer, which makes the Content Writer its lead. A specialist can hand work only to agents that report to it, so without that line the Content Writer cannot reach the Researcher.

​
The Content Writer

  • Name: content-writer (lowercase, hyphenated, becomes the filename)
  • Display name: Content Writer
  • Role: Content Writer
  • Description: Drafts short-form written content in the user’s voice.
  • Type: specialist, with order 1
  • Reports to: your orchestrator’s name (the name in its file), if your workspace has one
Use this as its instructions, as a starting point:

​
The Researcher

  • Name: researcher
  • Display name: Researcher
  • Role: Researcher
  • Description: Finds supporting facts, statistics and sources for drafts.
  • Type: specialist, with order 1.1
  • Reports to: content-writer
Use this as its instructions:
Once both files exist, the org chart shows the Content Writer with the Researcher beneath it.

​
3. Send a task that needs both

Open a conversation with the Content Writer: click its card on the org chart to open its profile, then press New conversation. Send a task that requires evidence:
Watch what happens. The Content Writer reads the request, recognises it needs research, and delegates the supporting-statistics subtask to the Researcher. You see both sides of the conversation: the Content Writer asking, the Researcher answering, the Content Writer using the answer to finish the draft. This is what makes Rundock different from a chatbot. The work is done by a team, in front of you, and you are watching the team coordinate.

​
4. Review and iterate

Read the draft. Decide whether the Researcher’s evidence was used well. Decide whether the post is something you would publish. If the draft needs work, do not try to fix the agents on the first pass. Send a follow-up message saying what is missing. For example:
The conversation continues. The Content Writer uses your feedback as context for the next round, and delegates again to the Researcher if it needs new evidence. You give direction, the team executes, you give more direction. This is the loop. You now have a working two-agent team you can keep using. From here you can adjust either agent’s instructions, add more specialists, write skills, or set up routines.

​
Where to next

Agents

What an agent is and how delegation works in more depth.

Workspaces

What is in your workspace folder and what stays local.

Create your first agent

A walkthrough of building an agent from scratch when you want to go beyond this example.

Set up a team workspace

Share your team across multiple people using Dropbox, OneDrive, Google Drive, or git.